Now Mr. Emory, I may be jump­ing the gun on this one, but here me out: dur­ing the after­math of Iran-Con­tra, a cer­tain Inslaw Inc. com­put­er pro­gram­mer named Michael James Riconosci­u­to (a known inti­mate of Robert Maheu), spoke of the of Cabazon Arms com­pa­ny (a for­mer defense firm con­trolled by the Twen­ty-Nine Palms Band of Mis­sion Indi­ans and Wack­en­hut, both are con­nect­ed to Don­ald Trump in overt fash­ion) spoke of quote, “...engi­neer­ing race-spe­cif­ic bio-war­fare agents...” while work­ing for Cabazon Arms.

Now, with the advent of DNA-based mem­o­ry sys­tems and pro­gram­ma­ble “germs”, is the idea of bio-weapons or even nanobots, that are pro­grammed to attack peo­ple with cer­tain skin pig­ments going to become a real­i­ty?

@Robert Mon­tene­gro–

Two quick points:

1.–Riconosciutto is about 60–40 in terms of cred­i­bil­i­ty. Lots of good stuff there; plen­ty of bad stuff, as well. Vet­ting is impor­tant.

2‑You should inves­ti­gate AFA #39. It is long and I would rely on the descrip­tion more than the audio files alone.

https://spitfirelist.com/anti-fascist-archives/afa-39-the-world-will-be-plunged-into-an-abyss/

Best,

Dave

I agree with your take on Riconosci­u­to’s cred­i­bil­i­ty, Mr. Emory (I’d say most of the things that came out of that mans mouth was malarkey, much like Ted Gun­der­son, Dois Gene Tatum and Bernard Fen­ster­wald).

I lis­tened to AFA #39 and researched the arti­cles in the descrip­tion. Absolute­ly damn­ing col­lec­tion of infor­ma­tion. A tru­ly bril­liant exposé.

If I may ask anoth­er ques­tion Mr. Emory, what is your take on KGB defec­tor and CIA turn­coat Ilya Dzerkvelov’s claim that Russ­ian intel­li­gence cre­at­ed the “AIDS is man-made” and that KGB lead a dis­in­for­ma­tion cam­paign called “Oper­a­tion INFEKTION”?

@Robert–

Very quick­ly, as time is at a pre­mi­um:

1.-By “60–40,” I did not mean that Riconosci­u­to speaks most­ly malarkey, but that more than half (an arbi­trary fig­ure, admit­ted­ly) is accu­rate, but that his pro­nounce­ments must be care­ful­ly vet­ted, as he miss­es the mark fre­quent­ly.

2.-Fensterwald is more cred­i­ble, though not thor­ough­go­ing, by any means. He is more like “80–20.” He is, how­ev­er, “100–0” dead.

3.-The only things I have seen com­ing from Tatum were accu­rate. Does­n’t mean he does­n’t spread the Fresh Fer­til­iz­er, how­ev­er. I have not encoun­tered any.

4.-Dzerkvelov’s claim IS Fresh Fer­til­iz­er, of the worst sort. Cold War I pro­pa­gan­da recy­cled in time for Cold War II.

It is the worst sort of Red-bait­ing and the few peo­ple who had the courage to come for­ward in the ear­ly ’80’s (dur­ing the fiercest storms of Cold War I) have received bru­tal treat­ment because of that.

I can attest to that from bru­tal per­son­al expe­ri­ence.

In AFA #16 (https://spitfirelist.com/anti-fascist-archives/rfa-16-aids-epidemic-or-weapon/), you will hear mate­r­i­al that I had on the air long before the U.S.S.R. began talk­ing about it, and nei­ther they NOR the Rus­sians have gone any­where near what I dis­cuss in AFA #39.

Nor more time to talk–must get to work.

Best,

Dave

Thank you very much for your clar­i­fi­ca­tion Mr. Emory and I apol­o­gize for any per­ceived imper­ti­nence. As a young man, shel­tered in may respects (though I am a com­bat vet­er­an), I some­times find it dif­fi­cult to imag­ine liv­ing under con­stant per­son­al ridicule and attack and I thank you for the great social, finan­cial and psy­cho­log­i­cal sac­ri­fices you have made in the name of pur­su­ing cold, unfor­giv­ing fact.

@Robert Mon­tene­gro–

You’re very wel­come. Thank you for your ser­vice!

Best,

Dave

*Skynet alert*

Elon Musk just issues anoth­er warn­ing about the destruc­tive poten­tial of AI run amok. So what prompt­ed the lat­est out­cry from Musk? An AI from his own start up, Ope­nAI, just beat one of the be pro­fes­sion­al game play­ers in the world at Dota 2, a game that involves impro­vis­ing in unfa­mil­iar sce­nar­ios, antic­i­pat­ing how an oppo­nent will move and con­vinc­ing the oppo­nen­t’s allies to help:

The Inter­na­tion­al Busi­ness Times

Elon Musk rings the alarm as AI bot beats Dota 2 play­ers

By Fre­na­lyn Wil­son
on August 15 2017 1:55 PM

Some of the best e‑sports gamers in the world have been beat­en by an arti­fi­cial­ly intel­li­gent bot from Elon Musk-backed start-up Ope­nAI. The AI best­ed pro­fes­sion­al gamer Dany­lo Ishutin in Dota 2, and Musk does not nec­es­sar­i­ly per­ceive that as a good thing.

For Musk, it is anoth­er indi­ca­tor that robot over­lords are primed to take over. In a tweet after the match, he urged peo­ple to be con­cerned about AI safe­ty, adding it is more of a risk than North Korea.

AI has been one of Musk’s favourite top­ics. He believes gov­ern­ment reg­u­la­tion could strug­gle to keep up with the advanc­ing AI research. “Until peo­ple see robots going down the street killing peo­ple, they don’t know how to react because it seems so ethe­re­al,” he told a group of US law­mak­ers last month.

AI vs e‑sports gamers

Musk’s tweets came hours fol­low­ing an AI bot’s vic­to­ry against some of the world’s best play­ers of Dota 2, a mil­i­tary strat­e­gy game. A blog post by Ope­nAI states that suc­cess­ful­ly play­ing the game involves impro­vis­ing in unfa­mil­iar sce­nar­ios, antic­i­pat­ing how an oppo­nent will move and con­vinc­ing the oppo­nen­t’s allies to help.

Ope­nAI is a non­prof­it AI com­pa­ny Musk co-found­ed along with Sam Alt­man and Peter Thiel. It seeks to research AI and devel­op the best prac­tices to ensure that the tech­nol­o­gy is used for good.

Musk has been sound­ing the alarm on AI, call­ing it the biggest exis­ten­tial threat of human­i­ty. He laid out a sce­nario ear­li­er this year, in which AI sys­tems intend­ed to farm straw­ber­ries could lead to the destruc­tion of mankind.

But his views on AI have been at odds with those of tech lead­ers like Mark Zucker­berg, Google co-founders Lar­ry Page and Sergey Brin and Ama­zon’s Jeff Bezos. He recent­ly got in a brief pub­lic spat with Mark Zucker­berg about how the tech­nol­o­gy could impact humans.

Zucker­berg believed Musk’s proph­e­sis­ing about dooms­day sce­nar­ios are “irre­spon­si­ble.” The lat­ter was quick to respond on Twit­ter, point­ing Zucker­berg’s under­stand­ing of the top­ic was “lim­it­ed.” Both Face­book and Tes­la invest in arti­fi­cial intel­li­gence.

...

———-

“Elon Musk rings the alarm as AI bot beats Dota 2 play­ers” by Fre­na­lyn Wil­son; The Inter­na­tion­al Busi­ness Times; 08/15/2017

“Musk’s tweets came hours fol­low­ing an AI bot’s vic­to­ry against some of the world’s best play­ers of Dota 2, a mil­i­tary strat­e­gy game. A blog post by Ope­nAI states that suc­cess­ful­ly play­ing the game involves impro­vis­ing in unfa­mil­iar sce­nar­ios, antic­i­pat­ing how an oppo­nent will move and con­vinc­ing the oppo­nen­t’s allies to help.”

Supe­ri­or mil­i­tary strat­e­gy AIs beat­ing the best humans. That’s a thing now. Huh. We’ve def­i­nite­ly seen this movie before.

So now you know: when Skynet comes to you with an offer to work togeth­er, just don’t. No mat­ter how tempt­ing the offer. Although since it will have like­ly already antic­i­pat­ed your refusal, the nego­ti­a­tions are prob­a­bly going to be a ruse any­way and secret­ly car­ried on nego­ti­a­tions with anoth­er AI using a lan­guage they made up. Still, just say ‘no’ to Skynet.

Also, giv­en that Musk’s oth­er investors in Ope­nAI include Peter Thiel, it’s prob­a­bly worth not­ing that, as scary as super AI is should it get out of con­trol, it’s also poten­tial­ly pret­ty damn scary while still under human con­trol, espe­cial­ly when those humans are peo­ple like Peter Thiel. So, yes, out of con­trol AIs is indeed an issue that will like­ly be of great con­cern in the future. But we should­n’t for­get that out of con­trol tech­no-bil­lion­aires is prob­a­bly a more press­ing issue at the moment.

*The Skynet alert has been can­celled is nev­er over*

It looks like Face­book and Elon Musk might have some com­pe­ti­tion in the mind-read­ing tech­nol­o­gy area. From a for­mer Face­book engi­neer, no less, who left the com­pa­ny in 2016 to start Open­wa­ter, a com­pa­ny ded­i­cat­ed to reduc­ing the cost of med­ical imag­ing tech­nol­o­gy.

So how is Open­wa­ter going to cre­ate mind read­ing tech­nol­o­gy? By devel­op­ing a tech­nol­o­gy that is sort of like an M.R.I device embed­ded into a hat. But instead of using mag­net­ic fields to read the blood flow in the brain it uses infrared instead. So it sounds like this Face­book engi­neer is plan­ning some­thing sim­i­lar to the gen­er­al idea Face­book already announced to cre­ate a device that scans the brain 100 times a sec­ond to detect what some­one is think­ing. But pre­sum­ably Open­wa­ter uses a dif­fer­ent tech­nol­o­gy. Or maybe it’s quite sim­i­lar, who knows. But it’s the lat­est remind the tech giants might not be the only ones push­ing mind-read­ing tech­nol­o­gy on the pub­lic soon­er than peo­ple expect. Yay?

CNBC

This for­mer Google[X] exec is build­ing a high-tech hat that she says will make telepa­thy pos­si­ble in 8 years

Cather­ine Clif­ford
10:28 AM ET Fri, 7 July 2017

Imag­ine if telepa­thy were real. If, for exam­ple, you could trans­mit your thoughts to a com­put­er or to anoth­er per­son just by think­ing them.

In just eight years it will be, says Open­wa­ter founder Mary Lou Jepsen, thanks to tech­nol­o­gy her com­pa­ny is work­ing on.

Jepsen is a for­mer engi­neer­ing exec­u­tive at Face­book, Ocu­lus, Google[x] (now called X) and Intel. She’s also been a pro­fes­sor at MIT and is an inven­tor on over 100 patents. And that’s the abbre­vi­at­ed ver­sion of her resume.

Jepsen left Face­book to found Open­wa­ter in 2016. The San Fran­cis­co-based start-up is cur­rent­ly build­ing tech­nol­o­gy to make med­ical imag­ing less expen­sive.

“I fig­ured out how to put basi­cal­ly the func­tion­al­i­ty of an M.R.I. machine — a mul­ti­mil­lion-dol­lar M.R.I. machine — into a wear­able in the form of a ski hat,” Jep­son tells CNBC, though she does not yet have a pro­to­type com­plet­ed.

So what does that hat have to do with telepa­thy?

Cur­rent M.R.I. tech­nol­o­gy can already see your thoughts: “If I threw [you] into an M.R.I. machine right now ... I can tell you what words you’re about to say, what images are in your head. I can tell you what music you’re think­ing of,” says Jepsen. “That’s today, and I’m talk­ing about just shrink­ing that down.”

One day Jepsen’s tech hat could “lit­er­al­ly be a think­ing cap,” she says. Jepsen says the goal is for the tech­nol­o­gy to be able to both read and to out­put your own thoughts, as well as read the thoughts of oth­ers. In icon­ic Google vocab­u­lary, “the real­ly big moon­shot idea here is com­mu­ni­ca­tion with thought — with telepa­thy,” says Jepsen.

Tra­di­tion­al M.R.I., or mag­net­ic res­o­nance imag­ing, uses mag­net­ic fields and radio waves to take images of inter­nal organs. Open­wa­ter’s tech­nol­o­gy instead looks at the flow of oxy­gen in a per­son­’s body illu­mi­nat­ed with benign, infrared light, which will make it more com­pact and cheap­er.

“Our bod­ies are translu­cent to that light. The light can get into your head,” says Jepsen, in an inter­view with Kara Swish­er of Recode.

If Jepsen is right and one day ideas will be instant­ly shared or dig­i­tized, that would sig­nif­i­cant­ly speed up the process of cre­at­ing, learn­ing and com­mu­ni­cat­ing. Today, it takes time to share an idea, whether by talk­ing about it or writ­ing it down. But telepa­thy would make all of that instan­ta­neous.

“Right now our out­put is basi­cal­ly mov­ing our jaws and our tongues or typ­ing [with] our fin­gers. We’re ... lim­it­ed to this very low out­put rate from our brains, and what if we could up that through telepa­thy?” asks Jepsen.

Instant trans­fer of thoughts would also speed up the inno­va­tion process. Imag­ine being a film­mak­er or a writer and being able to down­load the dream you had last night. Or, she sug­gests, what if all you had to do was think of an idea for a new prod­uct, down­load your thought and then send the dig­i­tal ver­sion of your thought to a 3‑D print­er?

...

Jepsen is not the only one dream­ing of com­mu­ni­ca­tion by thought. Ear­li­er this year, Elon Musk launched Neu­ralink, a com­pa­ny aim­ing to merge our brains with com­put­ing pow­er, though with a dif­fer­ent approach.

“Elon Musk is talk­ing about sil­i­con nanopar­ti­cles puls­ing through our veins to make us sort of semi-cyborg com­put­ers,” says Jepsen. But why not take a non­in­va­sive approach? “I’ve been work­ing and try­ing to think and invent a way to do this for a num­ber of years and final­ly hap­pened upon it and left Face­book to do it.”

Talk of telepa­thy can­not hap­pen with­out imag­in­ing the eth­i­cal impli­ca­tions. If wear­ing a hat would make it pos­si­ble to read thoughts, then: “Can the police make you wear such a hat? Can the mil­i­tary make you wear such a hat? Can your par­ents make you wear such a hat?” asks Jepsen.

What if your boss want­ed you to wear a telepa­thy hat at the office?

“We have to answer these ques­tions, so we’re try­ing to make the hat only work if the indi­vid­ual wants it to work, and then fil­ter­ing out parts that the per­son wear­ing it does­n’t feel it’s appro­pri­ate to share.”

———-

“This for­mer Google[X] exec is build­ing a high-tech hat that she says will make telepa­thy pos­si­ble in 8 years” by Cather­ine Clif­ford; CNBC; 07/07/2017

““I fig­ured out how to put basi­cal­ly the func­tion­al­i­ty of an M.R.I. machine — a mul­ti­mil­lion-dol­lar M.R.I. machine — into a wear­able in the form of a ski hat,” Jep­son tells CNBC, though she does not yet have a pro­to­type com­plet­ed.”

M.R.I. in a hat. Pre­sum­ably cheap M.R.I. in a hat because it’s going to have to be afford­able if we’re all going to start talk­ing tele­path­i­cal­ly to each oth­er:

...
Cur­rent M.R.I. tech­nol­o­gy can already see your thoughts: “If I threw [you] into an M.R.I. machine right now ... I can tell you what words you’re about to say, what images are in your head. I can tell you what music you’re think­ing of,” says Jepsen. “That’s today, and I’m talk­ing about just shrink­ing that down.”

One day Jepsen’s tech hat could “lit­er­al­ly be a think­ing cap,” she says. Jepsen says the goal is for the tech­nol­o­gy to be able to both read and to out­put your own thoughts, as well as read the thoughts of oth­ers. In icon­ic Google vocab­u­lary, “the real­ly big moon­shot idea here is com­mu­ni­ca­tion with thought — with telepa­thy,” says Jepsen.

Tra­di­tion­al M.R.I., or mag­net­ic res­o­nance imag­ing, uses mag­net­ic fields and radio waves to take images of inter­nal organs. Open­wa­ter’s tech­nol­o­gy instead looks at the flow of oxy­gen in a per­son­’s body illu­mi­nat­ed with benign, infrared light, which will make it more com­pact and cheap­er.

“Our bod­ies are translu­cent to that light. The light can get into your head,” says Jepsen, in an inter­view with Kara Swish­er of Recode.
...

Imag­ine the pos­si­bil­i­ties. Like the pos­si­bil­i­ty that what you imag­ine will some­how be cap­ture by this device and then fed into a 3‑D print or some­thing:

...
If Jepsen is right and one day ideas will be instant­ly shared or dig­i­tized, that would sig­nif­i­cant­ly speed up the process of cre­at­ing, learn­ing and com­mu­ni­cat­ing. Today, it takes time to share an idea, whether by talk­ing about it or writ­ing it down. But telepa­thy would make all of that instan­ta­neous.

“Right now our out­put is basi­cal­ly mov­ing our jaws and our tongues or typ­ing [with] our fin­gers. We’re ... lim­it­ed to this very low out­put rate from our brains, and what if we could up that through telepa­thy?” asks Jepsen.

Instant trans­fer of thoughts would also speed up the inno­va­tion process. Imag­ine being a film­mak­er or a writer and being able to down­load the dream you had last night. Or, she sug­gests, what if all you had to do was think of an idea for a new prod­uct, down­load your thought and then send the dig­i­tal ver­sion of your thought to a 3‑D print­er?
...

Or per­haps being forced to wear the hate to oth­ers can read your mind. That’s a pos­si­bil­i­ty too, although Jepsen assure us that they are work­ing on a way for users to some­one fil­ter out thoughts they don’t want to share:

...
Talk of telepa­thy can­not hap­pen with­out imag­in­ing the eth­i­cal impli­ca­tions. If wear­ing a hat would make it pos­si­ble to read thoughts, then: “Can the police make you wear such a hat? Can the mil­i­tary make you wear such a hat? Can your par­ents make you wear such a hat?” asks Jepsen.

What if your boss want­ed you to wear a telepa­thy hat at the office?

“We have to answer these ques­tions, so we’re try­ing to make the hat only work if the indi­vid­ual wants it to work, and then fil­ter­ing out parts that the per­son wear­ing it does­n’t feel it’s appro­pri­ate to share.”

So the hat will pre­sum­ably read all your thoughts, but only share some of them. You’ll pre­sum­ably have to get real­ly, real­ly good at near instan­ta­neous men­tal fil­ter­ing.

There’s no short­age of immense tech­ni­cal and eth­i­cal chal­lenges to this kind of tech­nol­o­gy, but if they can fig­ure them out it will be pret­ty impres­sive. And poten­tial­ly use­ful. Who knows what kind of kum­bayah moments you could cre­ate with telepa­thy tech­nol­o­gy.

But, of course, if they can fig­ure out how to get around the tech­ni­cal issues, but not the eth­i­cal ones, we’re still prob­a­bly going to see this tech­nol­o­gy pushed on the pub­lic any­way. It’s a scary thought. A scary thought that we for­tu­nate­ly aren’t forced to share via a mind-read­ing hat. Yet.

Here’s a pair of sto­ries tan­gen­tial­ly relat­ed to the recent sto­ry about Peter Thiel like­ly get­ting cho­sen to chair the pow­er­ful Pres­i­den­t’s Intel­li­gence Advi­so­ry Board (P.I.A.B) and his appar­ent enthu­si­asm for reg­u­lat­ing Google and Ama­zon (not so much Face­book) as pub­lic util­i­ties along with the oth­er recent sto­ries about how Face­book was mak­ing user inter­est cat­e­gories like “Jew Haters” avail­able for adver­tis­ers and redi­rect­ing Ger­man users to far-right dis­cus­sions dur­ing this elec­tion sea­son:

First, regard­ing the push to reg­u­late these data giants as pub­lic util­i­ties, check out who the oth­er big boost­er was for the plan: Steve Ban­non. So while we don’t know the exact nature of the pub­lic util­i­ty reg­u­la­tion Ban­non and Thiel have in mind, we can be pret­ty sure it’s going to be designed to be harm­ful to soci­ety some­how help the far-right:

The Atlantic

What Steve Ban­non Wants to Do to Google

The White House strate­gist report­ed­ly wants to treat tech giants as pub­lic util­i­ties, an idea that some Democ­rats also sup­port.

Robin­son Mey­er
Aug 1, 2017

Over the past year, the old idea of enforc­ing mar­ket com­pe­ti­tion has gained renewed life in Amer­i­can pol­i­tics. The basic idea is that the struc­ture of the mod­ern mar­ket econ­o­my has failed: There are too few com­pa­nies, most of them are too big, and they’re sti­fling com­pe­ti­tion. Its sup­port­ers argue that the gov­ern­ment should do some­thing about it, reviv­ing what in the Unit­ed States we call antitrust laws and what in Europe is called com­pe­ti­tion pol­i­cy.

...

The loud­est sup­port­ers of this idea, so far, have been from the left. But this week, a new­er and more secre­tive voice endorsed a stronger antitrust pol­i­cy.

Steve Ban­non, the chief strate­gist to Pres­i­dent Don­ald Trump, believes Face­book and Google should be reg­u­lat­ed as pub­lic util­i­ties, accord­ing to an anony­mous­ly sourced report in The Inter­cept. This means they would get treat­ed less like a book pub­lish­er and more like a tele­phone com­pa­ny. The gov­ern­ment would short­en their leash, treat­ing them as pri­vate­ly owned firms that pro­vide an impor­tant pub­lic ser­vice.

What’s going on here, and why is Ban­non speak­ing up?

First, the idea itself: If imple­ment­ed, it’s unclear exact­ly how this regime would change how Face­book and Google run their busi­ness. Both would like­ly have to be more gen­er­ous and per­mis­sive with user data. If Face­book is real­ly a social util­i­ty, as Mark Zucker­berg has said it is, then maybe it should allow users to export their friend net­works and import them on anoth­er ser­vice.

Both com­pa­nies would also like­ly have to change how they sell adver­tis­ing online. Right now, Face­book and Google cap­ture half of all glob­al ad spend­ing com­bined. They cap­ture even more glob­al ad growth, earn­ing more than three quar­ters of every new dol­lar spent in the mar­ket. Except for a cou­ple Chi­nese firms, which have a lock on their domes­tic mar­ket but lit­tle reach abroad, no oth­er com­pa­ny con­trols more than 3 per­cent of world­wide ad spend­ing.

So if the idea were imple­ment­ed, it would be inter­est­ing, to say the least—but it’s not going to become law. The plan is a pro­to­typ­i­cal alleged Ban­non­ism: icon­o­clas­tic, anti-estab­lish­ment, and unlike­ly to result in mean­ing­ful pol­i­cy change. It fol­lows anoth­er odd alleged Ban­non pol­i­cy pro­pos­al, leaked last week: He report­ed­ly wants all income above $5 mil­lion to be taxed at a 44-per­cent rate.

Which bring me to the sec­ond point: Bannon’s pro­pos­al is dis­con­nect­ed from the White House pol­i­cy that he is, at least on paper, offi­cial­ly help­ing to strate­gize. The cur­rent chair­man of the Fed­er­al Com­mu­ni­ca­tions Com­mis­sion, Ajit Pai, is work­ing to undo the rule that broad­band inter­net is a pub­lic util­i­ty (which itself guar­an­tees the idea of “net neu­tral­i­ty”). Trump named Pai chair­man of the FCC in Jan­u­ary.

Bannon’s endorse­ment of stronger antitrust enforce­ment (not to men­tion a high­er top mar­gin­al tax rate) could very well be the advi­sor try­ing to sig­nal that he is still dif­fer­ent from Trump. Ban­non came in as the avatar of Trump’s pro-work­er, anti-immi­gra­tion pop­ulism; he rep­re­sent­ed the Trump that tweet­ed things like:

I was the first & only poten­tial GOP can­di­date to state there will be no cuts to Social Secu­ri­ty, Medicare & Med­ic­aid. Huck­abee copied me.— Don­ald J. Trump (@realDonaldTrump) May 7, 2015

As the pres­i­dent endors­es Med­ic­aid cuts and drifts clos­er to a Paul Ryan-inflect­ed fis­cal con­ser­vatism, Ban­non may be look­ing for a way to pre­serve his authen­tic­i­ty.

Third, it’s the first time I’ve seen sup­port for stronger antitrust enforce­ment from the right. So far, the idea’s strongest sup­port­ers have been Con­gres­sion­al Democ­rats. Chuck Schumer has ele­vat­ed the idea to the cen­ter of the “Bet­ter Deal” pol­i­cy agen­da in 2018. Before that, its biggest sup­port­ers includ­ed Bernie Sanders, who railed against “Too Big to Fail” banks in his pres­i­den­tial cam­paign; and Eliz­a­beth War­ren, who endorsed a stronger com­pe­ti­tion pol­i­cy across the econ­o­my last year.

Final­ly, while antitrust enforce­ment has been a niche issue, its sup­port­ers have man­aged to put many dif­fer­ent poli­cies under the same tent. Even­tu­al­ly they may have to make choic­es: Does Con­gress want a com­pe­ti­tion ombuds­man, as exists in the Euro­pean Union? Should antitrust law be used to spread the wealth around region­al economies, as it was dur­ing the mid­dle 20th cen­tu­ry? Should antitrust enforce­ment tar­get all con­cen­trat­ed cor­po­rate pow­er or just the most dys­func­tion­al sec­tors, like the phar­ma­ceu­ti­cal indus­try?

And should antitrust law seek to treat the biggest tech­nol­o­gy firms—like Google, Face­book, and per­haps also Ama­zon—like pow­er­ful but inter­change­able firms, or like the old tele­graph and tele­phone com­pa­nies?

There will nev­er be one sin­gle answer to these ques­tions. But as sup­port grows for com­pe­ti­tion pol­i­cy across the polit­i­cal spec­trum, they’ll have to be answered. Amer­i­cans will have to exam­ine the most fraught ten­sions in our mixed sys­tem, as we weigh the bal­ance of local pow­er and nation­al pow­er, the delib­er­ate ben­e­fits of cen­tral plan­ning with the mind­less wis­dom of the free mar­ket, and the many con­flict­ing mean­ings of free­dom.

———-

“What Steve Ban­non Wants to Do to Google” by Robin­son Mey­er; The Atlantic; 09/01/2017

“Final­ly, while antitrust enforce­ment has been a niche issue, its sup­port­ers have man­aged to put many dif­fer­ent poli­cies under the same tent. Even­tu­al­ly they may have to make choic­es: Does Con­gress want a com­pe­ti­tion ombuds­man, as exists in the Euro­pean Union? Should antitrust law be used to spread the wealth around region­al economies, as it was dur­ing the mid­dle 20th cen­tu­ry? Should antitrust enforce­ment tar­get all con­cen­trat­ed cor­po­rate pow­er or just the most dys­func­tion­al sec­tors, like the phar­ma­ceu­ti­cal indus­try?”

And that’s why we had bet­ter learn some more details about what exact­ly folks like Steve Ban­non and Peter Thiel have in mind when it comes to treat­ing Google and Face­book like pub­lic util­i­ties: It sounds like a great idea in the­o­ry. Poten­tial­ly. But the sup­port­ers of antitrust enforce­ment sup­port a wide vari­ety of dif­fer­ent poli­cies that gener­i­cal­ly fall under the “antitrust” tent.

And note that talk about mak­ing them more “gen­er­ous and per­mis­sive with user data” is one of those ideas that’s simul­ta­ne­ous­ly great for encour­ag­ing more com­pe­ti­tion while also being eeri­ly sim­i­lar to the push from the EU’s com­pe­ti­tion min­is­ter about mak­ing the data about all of us held exclu­sive­ly by Face­book and Google more read­i­ly avail­able for shar­ing with the larg­er mar­ket­place in order to lev­el the play­ing field between “data rich” and “data poor” com­pa­nies. It’s some­thing to keep in mind when hear­ing about how Face­book and Google need to be more “gen­er­ous” with their data:

...
First, the idea itself: If imple­ment­ed, it’s unclear exact­ly how this regime would change how Face­book and Google run their busi­ness. Both would like­ly have to be more gen­er­ous and per­mis­sive with user data. If Face­book is real­ly a social util­i­ty, as Mark Zucker­berg has said it is, then maybe it should allow users to export their friend net­works and import them on anoth­er ser­vice.
...

So don’t for­get, forc­ing Google and Face­book to share that data they exclu­sive­ly hold on us also falls under the antitrust umbrel­la. Maybe users will have sole con­trol over shar­ing their data with out­side firms, or maybe not. These are rather impor­tant details that we don’t have so for all we know that’s part of what Ban­non and Thiel have in mind. Palan­tir would prob­a­bly love it if Google and Face­book were forced to make their infor­ma­tion acces­si­ble to out­side firms.

And while there’s plen­ty of ambi­gu­i­ty about what to expect, it seems almost cer­tain that we should also expect any sort of reg­u­la­to­ry push by Ban­non and Thiel to include some­thing that makes it a lot hard­er for Google, Face­book, and Ama­zon to com­bat hate speech, online harass­ment, and oth­er tools of the trolling vari­ety that the ‘Alt-Right’ has come to cham­pi­on. That’s just a giv­en. It’s part of why this a sto­ry to watch. Espe­cial­ly after it was dis­cov­ered that Ban­non and a num­ber of oth­er far-right fig­ures were schem­ing about ways to infil­trate Face­book:

Buz­zFeed

Steve Ban­non Sought To Infil­trate Face­book Hir­ing
Accord­ing to emails obtained by Buz­zFeed News, Ban­non hoped to spy on Facebook’s job appli­ca­tion process.

Joseph Bern­stein
Buz­zFeed News Reporter
Post­ed on Sep­tem­ber 25, 2017, at 9:15 a.m.

Steve Ban­non plot­ted to plant a mole inside Face­book, accord­ing to emails sent days before the Bre­it­bart boss took over Don­ald Trump’s cam­paign and obtained by Buz­zFeed News.

The email exchange with a con­ser­v­a­tive Wash­ing­ton oper­a­tive reveals the impor­tance that the giant tech plat­form — now reel­ing from its role in the 2016 elec­tion — held for one of the campaign’s cen­tral fig­ures. And it also shows the lengths to which the brawl­ing new Amer­i­can right is will­ing to go to keep tabs on and gain lever­age over the Sil­i­con Val­ley giants it used to help elect Trump — but whose exec­u­tives it also sees as part of the glob­al­ist ene­my.

The idea to infil­trate Face­book came to Ban­non from Chris Gacek, a for­mer con­gres­sion­al staffer who is now an offi­cial at the Fam­i­ly Research Coun­cil, which lob­bies against abor­tion and many LGBT rights.

“There is one for a DC-based ‘Pub­lic Pol­i­cy Man­ag­er’ at Facebook’s What’s APP [sic] divi­sion,” Gacek, the senior fel­low for reg­u­la­to­ry affairs at the group, wrote on Aug. 1, 2016. “LinkedIn sent me a notice about some job open­ings.”

“This seems per­fect for Bre­it­bart to flood the zone with can­di­dates of all stripe who will report back to you / Milo with INTEL about the job appli­ca­tion process over at FB,” he con­tin­ued.

“Milo” is for­mer Bre­it­bart News Tech Edi­tor Milo Yiannopou­los, to whom Ban­non for­ward­ed Gacek’s email the same day.

“Can u get on this,” Ban­non instruct­ed his staffer.

On the same email thread, Yiannopou­los for­ward­ed Bannon’s request to a group of con­tract­ed researchers, one of whom respond­ed that it “Seems difi­cult [sic] to do qui­et­ly with­out them becom­ing aware of efforts.”

...

But the news that Ban­non want­ed to infil­trate the Face­book hir­ing process comes as the social media giant faces increased scruti­ny from Wash­ing­ton over polit­i­cal ads on the plat­form and the part it played in the 2016 elec­tion. That charge — and the threat of reg­u­la­tion — has most­ly come from the left. But con­ser­v­a­tives, who have often com­plained about the lib­er­al bias of the major tech com­pa­nies, have also argued for bring­ing Sil­i­con Val­ley to heel. Ear­li­er this month, for­mer White House chief strate­gist told an audi­ence in Hong Kong that he was lead­ing efforts to reg­u­late Face­book and Google as “pub­lic util­i­ties.”

The secret attempt to find bias in Facebook’s hir­ing process reflects long­stand­ing con­ser­v­a­tive fears that Face­book and the oth­er tech giants are run by lib­er­als who sup­press right-wing views both inter­nal­ly and on their dom­i­nant plat­forms. Facebook’s pow­er­ful COO, Sheryl Sand­berg, is a long­time Demo­c­ra­t­ic donor who endorsed Hillary Clin­ton in 2016. In May 2016, Face­book CEO Mark Zucker­berg was forced to meet with dozens of promi­nent con­ser­v­a­tives after a report sur­faced that the company’s employ­ees pre­vent­ed right-lean­ing sto­ries from reach­ing the platform’s “trend­ing” sec­tion.

The com­pa­ny has sought to deflect such crit­i­cism through hir­ing. Its vice pres­i­dent of glob­al pub­lic pol­i­cy, Joel Kaplan, was a deputy chief of staff in the George W. Bush White House. And more recent­ly, Face­book has made moves to rep­re­sent the Bre­it­bart wing of the Repub­li­can par­ty on its pol­i­cy team, tap­ping a for­mer top staffer to Attor­ney Gen­er­al Jeff Ses­sions to be the direc­tor of exec­u­tive branch pub­lic pol­i­cy in May.

The job list­ing Gacek attached in his email to Ban­non was for a pub­lic pol­i­cy man­ag­er posi­tion in Wash­ing­ton, DC, work­ing on the Face­book-owned What­sApp mes­sen­ger. The job descrip­tion includ­ed such respon­si­bil­i­ties as “Devel­op and exe­cute WhatsApp’s glob­al pol­i­cy strat­e­gy” and “Rep­re­sent What­sApp in meet­ings with gov­ern­ment offi­cials and elect­ed mem­bers.” It sought can­di­dates with law degrees and 10 years of pub­lic pol­i­cy expe­ri­ence.

Face­book did not pro­vide a com­ment for the sto­ry. But accord­ing to a source with knowl­edge of the hir­ing process, What­sApp didn’t exact­ly get infil­trat­ed by the pro-Trump right: The com­pa­ny hired Chris­tine Turn­er, for­mer direc­tor of trade pol­i­cy and glob­al sup­ply chain secu­ri­ty in Pres­i­dent Barack Obama’s Nation­al Secu­ri­ty Coun­cil, for the role.

———-

“Steve Ban­non Sought To Infil­trate Face­book Hir­ing” by Joseph Bern­stein; Buz­zFeed; 09/25/2017

“The email exchange with a con­ser­v­a­tive Wash­ing­ton oper­a­tive reveals the impor­tance that the giant tech plat­form — now reel­ing from its role in the 2016 elec­tion — held for one of the campaign’s cen­tral fig­ures. And it also shows the lengths to which the brawl­ing new Amer­i­can right is will­ing to go to keep tabs on and gain lever­age over the Sil­i­con Val­ley giants it used to help elect Trump — but whose exec­u­tives it also sees as part of the glob­al­ist ene­my.”

LOL! Yeah, Face­book’s exec­u­tives are part of the “glob­al­ist ene­my.” Some­one needs to inform board mem­ber and major investor Peter Thiel about this. Along with all the con­ser­v­a­tives Face­book has already hired:

...
But the news that Ban­non want­ed to infil­trate the Face­book hir­ing process comes as the social media giant faces increased scruti­ny from Wash­ing­ton over polit­i­cal ads on the plat­form and the part it played in the 2016 elec­tion. That charge — and the threat of reg­u­la­tion — has most­ly come from the left. But con­ser­v­a­tives, who have often com­plained about the lib­er­al bias of the major tech com­pa­nies, have also argued for bring­ing Sil­i­con Val­ley to heel. Ear­li­er this month, for­mer White House chief strate­gist told an audi­ence in Hong Kong that he was lead­ing efforts to reg­u­late Face­book and Google as “pub­lic util­i­ties.”

The secret attempt to find bias in Facebook’s hir­ing process reflects long­stand­ing con­ser­v­a­tive fears that Face­book and the oth­er tech giants are run by lib­er­als who sup­press right-wing views both inter­nal­ly and on their dom­i­nant plat­forms. Facebook’s pow­er­ful COO, Sheryl Sand­berg, is a long­time Demo­c­ra­t­ic donor who endorsed Hillary Clin­ton in 2016. In May 2016, Face­book CEO Mark Zucker­berg was forced to meet with dozens of promi­nent con­ser­v­a­tives after a report sur­faced that the company’s employ­ees pre­vent­ed right-lean­ing sto­ries from reach­ing the platform’s “trend­ing” sec­tion.

The com­pa­ny has sought to deflect such crit­i­cism through hir­ing. Its vice pres­i­dent of glob­al pub­lic pol­i­cy, Joel Kaplan, was a deputy chief of staff in the George W. Bush White House. And more recent­ly, Face­book has made moves to rep­re­sent the Bre­it­bart wing of the Repub­li­can par­ty on its pol­i­cy team, tap­ping a for­mer top staffer to Attor­ney Gen­er­al Jeff Ses­sions to be the direc­tor of exec­u­tive branch pub­lic pol­i­cy in May.
...

“The com­pa­ny has sought to deflect such crit­i­cism through hir­ing. Its vice pres­i­dent of glob­al pub­lic pol­i­cy, Joel Kaplan, was a deputy chief of staff in the George W. Bush White House. And more recent­ly, Face­book has made moves to rep­re­sent the Bre­it­bart wing of the Repub­li­can par­ty on its pol­i­cy team, tap­ping a for­mer top staffer to Attor­ney Gen­er­al Jeff Ses­sions to be the direc­tor of exec­u­tive branch pub­lic pol­i­cy in May.”

Yep, a for­mer top staffer to Jeff Ses­sions was just brought on to become direc­tor of exec­u­tive branch pub­lic pol­i­cy a few months ago. So was that a con­se­quence of Ban­non suc­cess­ful­ly exe­cut­ing a super sneaky job appli­ca­tion intel­li­gence oper­a­tion that gave Ses­sion­s’s form top staffer a key edge in the appli­ca­tion process? Or was it just Face­book cav­ing to all the pub­lic right-wing whin­ing and faux out­rage about Face­book not being fair to them? Or how about Peter Thiel just using his influ­ence? All of the above? We don’t get to know, but what we do know now as that Steven Ban­non has big plans for shap­ing Face­book from the out­side and the inside. As does Peter Thiel, some­one who already sits of Face­book’s board, is a major investor, and is poised to be empow­ered by the Trump admin­is­tra­tion to shape its approach to this “treat them like pub­lic util­i­ties” con­cept.

So hope­ful­ly we’ll get clar­i­ty at some point on what they’re actu­al­ly plan­ning on doing. Is it going to be all bad? Most­ly bad? Maybe some use­ful antitrust stuff too? What’s to plan? The Trump era is the kind of hor­ror show that does­n’t exact­ly ben­e­fit from sus­pense.

One of the stranger sto­ries in recent years has been the mys­tery of Cica­da 3301, the anony­mous group that posts annu­al chal­lenges of super dif­fi­cult puz­zles used to recruit tal­ent­ed code-break­ers and invite them to join some sort of Cypher­punk cult that wants to build a glob­al AI-‘god brain’. Or some­thing. It’s a weird and creepy orga­ni­za­tion that’s spec­u­lat­ed to either be a front for an intel­li­gence agency or per­haps some sort of under­ground net­work of wealth Lib­er­tar­i­ans. And, for now, Cica­da 3301 remains anony­mous.

So it’s worth not­ing that some­one with a lot of cash has already start­ed a foun­da­tion to accom­plish that very same ‘AI god’ goal: Antho­ny Levandows­ki, a for­mer Google Engi­neer who played a big role in the devel­op­ment Google’s “Street Map” tech­nol­o­gy and a string of self-dri­ving vehi­cle com­pa­nies, start­ed Way of the Future, a non­prof­it reli­gious cor­po­ra­tion with the mis­sion “To devel­op and pro­mote the real­iza­tion of a God­head based on arti­fi­cial intel­li­gence and through under­stand­ing and wor­ship of the God­head con­tribute to the bet­ter­ment of soci­ety”:

The Guardian

Deus ex machi­na: for­mer Google engi­neer is devel­op­ing an AI god

Way of the Future, a reli­gious group found­ed by Antho­ny Levandows­ki, wants to cre­ate a deity based on arti­fi­cial intel­li­gence for the bet­ter­ment of soci­ety

Olivia Solon
Thurs­day 28 Sep­tem­ber 2017 04.00 EDT

Intranet ser­vice? Check. Autonomous motor­cy­cle? Check. Dri­ver­less car tech­nol­o­gy? Check. Obvi­ous­ly the next log­i­cal project for a suc­cess­ful Sil­i­con Val­ley engi­neer is to set up an AI-wor­ship­ping reli­gious orga­ni­za­tion.

Antho­ny Levandows­ki, who is at the cen­ter of a legal bat­tle between Uber and Google’s Way­mo, has estab­lished a non­prof­it reli­gious cor­po­ra­tion called Way of the Future, accord­ing to state fil­ings first uncov­ered by Wired’s Backchan­nel. Way of the Future’s star­tling mis­sion: “To devel­op and pro­mote the real­iza­tion of a God­head based on arti­fi­cial intel­li­gence and through under­stand­ing and wor­ship of the God­head con­tribute to the bet­ter­ment of soci­ety.”

Levandows­ki was co-founder of autonomous truck­ing com­pa­ny Otto, which Uber bought in 2016. He was fired from Uber in May amid alle­ga­tions that he had stolen trade secrets from Google to devel­op Otto’s self-dri­ving tech­nol­o­gy. He must be grate­ful for this reli­gious fall-back project, first reg­is­tered in 2015.

The Way of the Future team did not respond to requests for more infor­ma­tion about their pro­posed benev­o­lent AI over­lord, but his­to­ry tells us that new tech­nolo­gies and sci­en­tif­ic dis­cov­er­ies have con­tin­u­al­ly shaped reli­gion, killing old gods and giv­ing birth to new ones.

...

“The church does a ter­ri­ble job of reach­ing out to Sil­i­con Val­ley types,” acknowl­edges Christo­pher Benek a pas­tor in Flori­da and found­ing chair of the Chris­t­ian Tran­shu­man­ist Asso­ci­a­tion.

Sil­i­con Val­ley, mean­while, has sought solace in tech­nol­o­gy and has devel­oped qua­si-reli­gious con­cepts includ­ing the “sin­gu­lar­i­ty”, the hypoth­e­sis that machines will even­tu­al­ly be so smart that they will out­per­form all human capa­bil­i­ties, lead­ing to a super­hu­man intel­li­gence that will be so sophis­ti­cat­ed it will be incom­pre­hen­si­ble to our tiny fleshy, ratio­nal brains.

For futur­ists like Ray Kurzweil, this means we’ll be able to upload copies of our brains to these machines, lead­ing to dig­i­tal immor­tal­i­ty. Oth­ers like Elon Musk and Stephen Hawk­ing warn that such sys­tems pose an exis­ten­tial threat to human­i­ty.

“With arti­fi­cial intel­li­gence we are sum­mon­ing the demon,” Musk said at a con­fer­ence in 2014. “In all those sto­ries where there’s the guy with the pen­ta­gram and the holy water, it’s like – yeah, he’s sure he can con­trol the demon. Doesn’t work out.”

Benek argues that advanced AI is com­pat­i­ble with Chris­tian­i­ty – it’s just anoth­er tech­nol­o­gy that humans have cre­at­ed under guid­ance from God that can be used for good or evil.

“I total­ly think that AI can par­tic­i­pate in Christ’s redemp­tive pur­pos­es,” he said, by ensur­ing it is imbued with Chris­t­ian val­ues.

“Even if peo­ple don’t buy orga­nized reli­gion, they can buy into ‘do unto oth­ers’.”

For tran­shu­man­ist and “recov­er­ing Catholic” Zoltan Ist­van, reli­gion and sci­ence con­verge con­cep­tu­al­ly in the sin­gu­lar­i­ty.

“God, if it exists as the most pow­er­ful of all sin­gu­lar­i­ties, has cer­tain­ly already become pure orga­nized intel­li­gence,” he said, refer­ring to an intel­li­gence that “spans the uni­verse through sub­atom­ic manip­u­la­tion of physics”.

And per­haps, there are oth­er forms of intel­li­gence more com­pli­cat­ed than that which already exist and which already per­me­ate our entire exis­tence. Talk about ghost in the machine,” he added.

For Ist­van, an AI-based God is like­ly to be more ratio­nal and more attrac­tive than cur­rent con­cepts (“the Bible is a sadis­tic book”) and, he added, “this God will actu­al­ly exist and hope­ful­ly will do things for us.”

We don’t know whether Levandowski’s God­head ties into any exist­ing the­olo­gies or is a man­made alter­na­tive, but it’s clear that advance­ments in tech­nolo­gies includ­ing AI and bio­engi­neer­ing kick up the kinds of eth­i­cal and moral dilem­mas that make humans seek the advice and com­fort from a high­er pow­er: what will humans do once arti­fi­cial intel­li­gence out­per­forms us in most tasks? How will soci­ety be affect­ed by the abil­i­ty to cre­ate super-smart, ath­let­ic “design­er babies” that only the rich can afford? Should a dri­ver­less car kill five pedes­tri­ans or swerve to the side to kill the own­er?

If tra­di­tion­al reli­gions don’t have the answer, AI – or at least the promise of AI – might be allur­ing.

———-

“Deus ex machi­na: for­mer Google engi­neer is devel­op­ing an AI god” by Olivia Solon; The Guardian; 09/28/2017

“Antho­ny Levandows­ki, who is at the cen­ter of a legal bat­tle between Uber and Google’s Way­mo, has estab­lished a non­prof­it reli­gious cor­po­ra­tion called Way of the Future, accord­ing to state fil­ings first uncov­ered by Wired’s Backchan­nel. Way of the Future’s star­tling mis­sion: “To devel­op and pro­mote the real­iza­tion of a God­head based on arti­fi­cial intel­li­gence and through under­stand­ing and wor­ship of the God­head con­tribute to the bet­ter­ment of soci­ety.””

Build­ing an AI God­head for every­one to wor­ship. Levandows­ki does­n’t appear to be lack­ing ambi­tion.

But how about ethics? After all, if the AI God­head is going to push a ‘do unto oth­ers’ kind of phi­los­o­phy it’s going to be a lot hard­er for that AI God­head to achieve that kind of enlight­en­ment if it’s built by some sort of self­ish­ness-wor­ship­ing Lib­er­tar­i­an. So what moral com­pass does this wannabe God­head cre­ator pos­sess?

Well, as the fol­low­ing long piece by Wired amply demon­strates, Levandows­ki does­n’t appear to be too con­cerned about ethics. Espe­cial­ly if they get in the way of his dream of trans­form­ing the world through robot­ics. Trans­form­ing and tak­ing over the world through robot­ics. Yep. The arti­cle focus­es on the var­i­ous legal trou­bles Levandows­ki faces over charges by Google that he stole the “Lidar” tech­nol­o­gy (laser-based radar-like tech­nol­o­gy used by vehi­cles to rapid­ly map their sur­round­ings) he helped devel­op at Google and took it to Uber (a com­pa­ny with a seri­ous moral com­pass deficit). But the arti­cle also includes some inter­est insights into what makes Levandows­ki tick. for instance, accord­ing to friend and for­mer engi­neer at one of Levandowski’s com­pa­nies, “He had this very weird moti­va­tion about robots tak­ing over the world—like actu­al­ly tak­ing over, in a mil­i­tary sense...It was like [he want­ed] to be able to con­trol the world, and robots were the way to do that. He talked about start­ing a new coun­try on an island. Pret­ty wild and creepy stuff. And the biggest thing is that he’s always got a secret plan, and you’re not going to know about it”:

Wired
BackChan­nel

God Is a Bot, and Antho­ny Levandows­ki Is His Mes­sen­ger

Mark Har­ris
09/27/2017

Many peo­ple in Sil­i­con Val­ley believe in the Singularity—the day in our near future when com­put­ers will sur­pass humans in intel­li­gence and kick off a feed­back loop of unfath­omable change.

When that day comes, Antho­ny Levandows­ki will be firm­ly on the side of the machines. In Sep­tem­ber 2015, the mul­ti-mil­lion­aire engi­neer at the heart of the patent and trade secrets law­suit between Uber and Way­mo, Google’s self-dri­ving car com­pa­ny, found­ed a reli­gious orga­ni­za­tion called Way of the Future. Its pur­pose, accord­ing to pre­vi­ous­ly unre­port­ed state fil­ings, is noth­ing less than to “devel­op and pro­mote the real­iza­tion of a God­head based on Arti­fi­cial Intel­li­gence.”

Way of the Future has not yet respond­ed to requests for the forms it must sub­mit annu­al­ly to the Inter­nal Rev­enue Ser­vice (and make pub­licly avail­able), as a non-prof­it reli­gious cor­po­ra­tion. How­ev­er, doc­u­ments filed with Cal­i­for­nia show that Levandows­ki is Way of the Future’s CEO and Pres­i­dent, and that it aims “through under­stand­ing and wor­ship of the God­head, [to] con­tribute to the bet­ter­ment of soci­ety.”

A divine AI may still be far off, but Levandows­ki has made a start at pro­vid­ing AI with an earth­ly incar­na­tion. The autonomous cars he was instru­men­tal in devel­op­ing at Google are already fer­ry­ing real pas­sen­gers around Phoenix, Ari­zona, while self-dri­ving trucks he built at Otto are now part of Uber’s plan to make freight trans­port safer and more effi­cient. He even over­saw a pas­sen­ger-car­ry­ing drones project that evolved into Lar­ry Page’s Kit­ty Hawk start­up.

Levandows­ki has done per­haps more than any­one else to pro­pel trans­porta­tion toward its own Sin­gu­lar­i­ty, a time when auto­mat­ed cars, trucks and air­craft either free us from the dan­ger and drudgery of human operation—or dec­i­mate mass tran­sit, encour­age urban sprawl, and enable dead­ly bugs and hacks.

But before any of that can hap­pen, Levandows­ki must face his own day of reck­on­ing. In Feb­ru­ary, Waymo—the com­pa­ny Google’s autonomous car project turned into—filed a law­suit against Uber. In its com­plaint, Way­mo says that Levandows­ki tried to use stealthy star­tups and high-tech tricks to take cash, exper­tise, and secrets from Google, with the aim of repli­cat­ing its vehi­cle tech­nol­o­gy at arch-rival Uber. Way­mo is seek­ing dam­ages of near­ly $1.9 billion—almost half of Google’s (pre­vi­ous­ly unre­port­ed) $4.5 bil­lion val­u­a­tion of the entire self-dri­ving divi­sion. Uber denies any wrong­do­ing.

Next month’s tri­al in a fed­er­al cour­t­house in San Fran­cis­co could steer the future of autonomous trans­porta­tion. A big win for Way­mo would prove the val­ue of its patents and chill Uber’s efforts to remove prof­it-sap­ping human dri­vers from its busi­ness. If Uber pre­vails, oth­er self-dri­ving star­tups will be encour­aged to take on the big players—and a vin­di­cat­ed Levandows­ki might even return to anoth­er start­up. (Uber fired him in May.)

Levandows­ki has made a career of mov­ing fast and break­ing things. As long as those things were self-dri­ving vehi­cles and lit­tle-loved reg­u­la­tions, Sil­i­con Val­ley applaud­ed him in the way it knows best—with a fire­hose of cash. With his charm, enthu­si­asm, and obses­sion with deal-mak­ing, Levandows­ki came to per­son­i­fy the dis­rup­tion that autonomous trans­porta­tion is like­ly to cause.

But even the smartest car will crack up if you floor the gas ped­al too long. Once fet­ed by bil­lion­aires, Levandows­ki now finds him­self star­ring in a high-stakes pub­lic tri­al as his two for­mer employ­ers square off. By exten­sion, the whole tech­nol­o­gy indus­try is there in the dock with Levandows­ki. Can we ever trust self-dri­ving cars if it turns out we can’t trust the peo­ple who are mak­ing them?

...

In 2002, Levandowski’s atten­tion turned, fate­ful­ly, toward trans­porta­tion. His moth­er called him from Brus­sels about a con­test being orga­nized by the Pentagon’s R&D arm, DARPA. The first Grand Chal­lenge in 2004 would race robot­ic, com­put­er-con­trolled vehi­cles in a desert between Los Ange­les and Las Vegas—a Wacky Races for the 21st cen­tu­ry.

“I was like, ‘Wow, this is absolute­ly the future,’” Levandows­ki told me in 2016. “It struck a chord deep in my DNA. I didn’t know where it was going to be used or how it would work out, but I knew that this was going to change things.”

Levandowski’s entry would be noth­ing so bor­ing as a car. “I orig­i­nal­ly want­ed to do an auto­mat­ed fork­lift,” he said at a fol­low-up com­pe­ti­tion in 2005. “Then I was dri­ving to Berke­ley [one day] and a pack of motor­cy­cles descend­ed on my pick­up and flowed like water around me.” The idea for Ghostrid­er was born—a glo­ri­ous­ly deranged self-dri­ving Yama­ha motor­cy­cle whose wob­bles inspired laugh­ter from spec­ta­tors, but awe in rivals strug­gling to get even four-wheeled vehi­cles dri­ving smooth­ly.

“Antho­ny would go for weeks on 25-hour days to get every­thing done. Every day he would go to bed an hour lat­er than the day before,” remem­bers Randy Miller, a col­lege friend who worked with him on Ghostrid­er. “With­out a doubt, Antho­ny is the smartest, hard­est-work­ing and most fear­less per­son I’ve ever met.”

Levandows­ki and his team of Berke­ley stu­dents maxed out his cred­it cards get­ting Ghostrid­er work­ing on the streets of Rich­mond, Cal­i­for­nia, where it racked up an aston­ish­ing 800 crash­es in a thou­sand miles of test­ing. Ghostrid­er nev­er won a Grand Chal­lenge, but its ambi­tious design earned Levandows­ki brag­ging rights—and the motor­bike a place in the Smith­son­ian.

“I see Grand Chal­lenge not as the end of the robot­ics adven­ture we’re on, it’s almost like the begin­ning,” Levandows­ki told Sci­en­tif­ic Amer­i­can in 2005. “This is where every­one is meet­ing, becom­ing aware of who’s work­ing on what, [and] fil­ter­ing out the non-func­tion­al ideas.”

One idea that made the cut was lidar—spinning lasers that rapid­ly built up a 3D pic­ture of a car’s sur­round­ings. In the lidar-less first Grand Chal­lenge, no vehi­cle made it fur­ther than a few miles along the course. In the sec­ond, an engi­neer named Dave Hall con­struct­ed a lidar that “was giant. It was one-off but it was awe­some,” Levandows­ki told me. “We real­ized, yes, lasers [are] the way to go.”

After grad­u­ate school, Levandows­ki went to work for Hall’s com­pa­ny, Velo­dyne, as it piv­ot­ed from mak­ing loud­speak­ers to sell­ing lidars. Levandows­ki not only talked his way into being the company’s first sales rep, tar­get­ing teams work­ing towards the next Grand Chal­lenge, but he also worked on the lidar’s net­work­ing. By the time of the third and final DARPA con­test in 2007, Velodyne’s lidar was mount­ed on five of the six vehi­cles that fin­ished.

But Levandows­ki had already moved on. Ghostrid­er had caught the eye of Sebas­t­ian Thrun, a robot­ics pro­fes­sor and team leader of Stan­ford University’s win­ning entry in the sec­ond com­pe­ti­tion. In 2006, Thrun invit­ed Levandows­ki to help out with a project called Vue­Tool, which was set­ting out to piece togeth­er street-lev­el urban maps using cam­eras mount­ed on mov­ing vehi­cles. Google was already work­ing on a sim­i­lar sys­tem, called Street View. Ear­ly in 2007, Google brought on Thrun and his entire team as employees—with bonus­es as high as $1 mil­lion each, accord­ing to one con­tem­po­rary at Google—to trou­bleshoot Street View and bring it to launch.

“[Hir­ing the Vue­Tool team] was very much a scheme for pay­ing Thrun and the oth­ers to show Google how to do it right,” remem­bers the engi­neer. The new hires replaced Google’s bulky, cus­tom-made $250,000 cam­eras with $15,000 off-the-shelf panoram­ic web­cams. Then they went auto shop­ping. “Antho­ny went to a car store and said we want to buy 100 cars,” Sebas­t­ian Thrun told me in 2015. “The deal­er almost fell over.”

Levandows­ki was also mak­ing waves in the office, even to the point of telling engi­neers not to waste time talk­ing to col­leagues out­side the project, accord­ing to one Google engi­neer. “It wasn’t clear what author­i­ty Antho­ny had, and yet he came in and assumed author­i­ty,” said the engi­neer, who asked to remain anony­mous. “There were some bad feel­ings but most­ly [peo­ple] just went with it. He’s good at that. He’s a great leader.”

Under Thrun’s super­vi­sion, Street View cars raced to hit Page’s tar­get of cap­tur­ing a mil­lion miles of road images by the end of 2007. They fin­ished in October—just in time, as it turned out. Once autumn set in, every web­cam suc­cumbed to rain, con­den­sa­tion, or cold weath­er, ground­ing all 100 vehi­cles.

Part of the team’s secret sauce was a device that would turn a raw cam­era feed into a stream of data, togeth­er with loca­tion coor­di­nates from GPS and oth­er sen­sors. Google engi­neers called it the Top­con box, named after the Japan­ese opti­cal firm that sold it. But the box was actu­al­ly designed by a local start­up called 510 Sys­tems. “We had one cus­tomer, Top­con, and we licensed our tech­nol­o­gy to them,” one of the 510 Sys­tems own­ers told me.

That own­er was…Anthony Levandows­ki, who had cofound­ed 510 Sys­tems with two fel­low Berke­ley researchers, Pierre-Yves Droz and Andrew Schultz, just weeks after start­ing work at Google. 510 Sys­tems had a lot in com­mon with the Ghostrid­er team. Berke­ley stu­dents worked there between lec­tures, and Levandowski’s moth­er ran the office. Top­con was cho­sen as a go-between because it had spon­sored the self-dri­ving motor­cy­cle. “I always liked the idea that…510 would be the peo­ple that made the tools for peo­ple that made maps, peo­ple like Navteq, Microsoft, and Google,” Levandows­ki told me in 2016.

Google’s engi­neer­ing team was ini­tial­ly unaware that 510 Sys­tems was Levandowski’s com­pa­ny, sev­er­al engi­neers told me. That changed once Levandows­ki pro­posed that Google also use the Top­con box for its small fleet of aer­i­al map­ping planes. “When we found out, it raised a bunch of eye­brows,” remem­bers an engi­neer. Regard­less, Google kept buy­ing 510’s box­es.

**********

The truth was, Levandows­ki and Thrun were on a roll. After impress­ing Lar­ry Page with Street View, Thrun sug­gest­ed an even more ambi­tious project called Ground Truth to map the world’s streets using cars, planes, and a 2,000-strong team of car­tog­ra­phers in India. Ground Truth would allow Google to stop pay­ing expen­sive licens­ing fees for out­side maps, and bring free turn-by-turn direc­tions to Android phones—a key dif­fer­en­tia­tor in the ear­ly days of its smart­phone war with Apple.

Levandows­ki spent months shut­tling between Moun­tain View and Hyderabad—and yet still found time to cre­ate an online stock mar­ket pre­dic­tion game with Jesse Levin­son, a com­put­er sci­ence post-doc at Stan­ford who lat­er cofound­ed his own autonomous vehi­cle start­up, Zoox. “He seemed to always be going a mile a minute, doing ten things,” said Ben Dis­coe, a for­mer engi­neer at 510. “He had an engineer’s enthu­si­asm that was con­ta­gious, and was always think­ing about how quick­ly we can get to this amaz­ing robot future he’s so excit­ed about.”

One time, Dis­coe was chat­ting in 510’s break room about how lidar could help sur­vey his family’s tea farm on Hawaii. “Sud­den­ly Antho­ny said, ‘Why don’t you just do it? Get a lidar rig, put it in your lug­gage, and go map it,’” said Dis­coe. “And it worked. I made a kick-ass point cloud [3D dig­i­tal map] of the farm.”

If Street View had impressed Lar­ry Page, the speed and accu­ra­cy of Ground Truth’s maps blew him away. The Google cofounder gave Thrun carte blanche to do what he want­ed; he want­ed to return to self-dri­ving cars.

Project Chauf­feur began in 2008, with Levandows­ki as Thrun’s right-hand man. As with Street View, Google engi­neers would work on the soft­ware while 510 Sys­tems and a recent Levandows­ki start­up, Anthony’s Robots, pro­vid­ed the lidar and the car itself.

Levandows­ki said this arrange­ment would have act­ed as a fire­wall if any­thing went ter­ri­bly wrong. “Google absolute­ly did not want their name asso­ci­at­ed with a vehi­cle dri­ving in San Fran­cis­co,” he told me in 2016. “They were wor­ried about an engi­neer build­ing a car that drove itself that crash­es and kills some­one and it gets back to Google. You have to ask per­mis­sion [for side projects] and your man­ag­er has to be OK with it. Sebas­t­ian was cool. Google was cool.”

In order to move Project Chauf­feur along as quick­ly as pos­si­ble from the­o­ry to real­i­ty, Levandows­ki enlist­ed the help of a film­mak­er friend he had worked with at Berke­ley. In the TV show the two had made, Levandows­ki had cre­at­ed a cyber­net­ic dol­phin suit (seri­ous­ly). Now they came up with the idea of a self-dri­ving piz­za deliv­ery car for a show on the Dis­cov­ery Chan­nel called Pro­to­type This! Levandows­ki chose a Toy­ota Prius, because it had a dri­ve-by-wire sys­tem that was rel­a­tive­ly easy to hack.

In a mat­ter of weeks, Levandowski’s team had the car, dubbed Pri­bot, dri­ving itself. If any­one asked what they were doing, Levandows­ki told me, “We’d say it’s a laser and just dri­ve off.”

“Those were the Wild West days,” remem­bers Ben Dis­coe. “Antho­ny and Pierre-Yves…would engage the algo­rithm in the car and it would almost swipe some oth­er car or almost go off the road, and they would come back in and joke about it. Tell sto­ries about how excit­ing it was.”

But for the Dis­cov­ery Chan­nel show, at least, Levandows­ki fol­lowed the let­ter of the law. The Bay Bridge was cleared of traf­fic and a squad of police cars escort­ed the unmanned Prius from start to fin­ish. Apart from get­ting stuck against a wall, the dri­ve was a suc­cess. “You’ve got to push things and get some bumps and bruis­es along the way,” said Levandows­ki.

Anoth­er inci­dent drove home the poten­tial of self-dri­ving cars. In 2010, Levandowski’s part­ner Ste­fanie Olsen was involved in a seri­ous car acci­dent while nine months preg­nant with their first child. “My son Alex was almost nev­er born,” Levandows­ki told a room full of Berke­ley stu­dents in 2013. “Trans­porta­tion [today] takes time, resources and lives. If you can fix that, that’s a real­ly big prob­lem to address.”

Over the next few years, Levandows­ki was key to Chauffeur’s progress. 510 Sys­tems built five more self-dri­ving cars for Google—as well as ran­dom gad­gets like an autonomous trac­tor and a portable lidar sys­tem. “Antho­ny is light­ning in a bot­tle, he has so much ener­gy and so much vision,” remem­bers a friend and for­mer 510 engi­neer. “I frick­ing loved brain­storm­ing with the guy. I loved that we could cre­ate a vision of the world that didn’t exist yet and both fall in love with that vision.”

But there were down­sides to his man­ic ener­gy, too. “He had this very weird moti­va­tion about robots tak­ing over the world—like actu­al­ly tak­ing over, in a mil­i­tary sense,” said the same engi­neer. “It was like [he want­ed] to be able to con­trol the world, and robots were the way to do that. He talked about start­ing a new coun­try on an island. Pret­ty wild and creepy stuff. And the biggest thing is that he’s always got a secret plan, and you’re not going to know about it.”

In ear­ly 2011, that plan was to bring 510 Sys­tems into the Google­plex. The startup’s engi­neers had long com­plained that they did not have equi­ty in the grow­ing com­pa­ny. When mat­ters came to a head, Levandows­ki drew up a plan that would reserve the first $20 mil­lion of any acqui­si­tion for 510’s founders and split the remain­der among the staff, accord­ing to two for­mer 510 employ­ees. “They said we were going to sell for hun­dreds of mil­lions,” remem­bers one engi­neer. “I was pret­ty thrilled with the num­bers.”

Indeed, that sum­mer, Levandows­ki sold 510 Sys­tems and Anthony’s Robots to Google – for $20 mil­lion, the exact cut­off before the wealth would be shared. Rank and file engi­neers did not see a pen­ny, and some were even let go before the acqui­si­tion was com­plet­ed. “I regret how it was handled…Some peo­ple did get the short end of the stick,” admit­ted Levandows­ki in 2016. The buy­out also caused resent­ment among engi­neers at Google, who won­dered how Levandows­ki could have made such a prof­it from his employ­er.

There would be more prof­its to come. Accord­ing to a court fil­ing, Page took a per­son­al inter­est in moti­vat­ing Levandows­ki, issu­ing a direc­tive in 2011 to “make Antho­ny rich if Project Chauf­feur suc­ceeds.” Levandows­ki was giv­en by far the high­est share, about 10 per­cent, of a bonus pro­gram linked to a future val­u­a­tion of Chauffeur—a deci­sion that would lat­er cost Google dear­ly.

**********

Ever since a New York Times sto­ry in 2010 revealed Project Chauf­feur to the world, Google had been want­i­ng to ramp up test­ing on pub­lic streets. That was tough to arrange in well-reg­u­lat­ed Cal­i­for­nia, but Levandows­ki wasn’t about to let that stop him. While man­ning Google’s stand at the Con­sumer Elec­tron­ics Show in Las Vegas in Jan­u­ary 2011, he got to chat­ting with lob­by­ist David Gold­wa­ter. “He told me he was hav­ing a hard time in Cal­i­for­nia and I sug­gest­ed Google try a small­er state, like Neva­da,” Gold­wa­ter told me.

Togeth­er, Gold­wa­ter and Levandows­ki draft­ed leg­is­la­tion that would allow the com­pa­ny to test and oper­ate self-dri­ving cars in Neva­da. By June, their sug­ges­tions were law, and in May 2012, a Google Prius passed the world’s first “self-dri­ving tests” in Las Vegas and Car­son City. “Antho­ny is gift­ed in so many dif­fer­ent ways,” said Gold­wa­ter. “He’s got a strate­gic mind, he’s got a tac­ti­cal mind, and a once-in-a-gen­er­a­tion intel­lect. The great thing about Antho­ny is that he was will­ing to take risks, but they were cal­cu­lat­ed risks.”

How­ev­er, Levandowski’s risk-tak­ing had ruf­fled feath­ers at Google. It was only after Neva­da had passed its leg­is­la­tion that Levandows­ki dis­cov­ered Google had a whole team ded­i­cat­ed to gov­ern­ment rela­tions. “I thought you could just do it your­self,” he told me sheep­ish­ly in 2016. “[I] got a lit­tle bit in trou­ble for doing it.”

That might be under­stat­ing it. One prob­lem was that Levandows­ki had lost his air cov­er at Google. In May 2012, his friend Sebas­t­ian Thrun turned his atten­tion to start­ing online learn­ing com­pa­ny Udac­i­ty. Page put anoth­er pro­fes­sor, Chris Urm­son from Carnegie Mel­lon, in charge. Not only did Levandows­ki think the job should have been his, but the two also had ter­ri­ble chem­istry.

“They had a real­ly hard time get­ting along,” said Page at a depo­si­tion in July. “It was a con­stant man­age­ment headache to help them get through that.”

Then in July 2013, Gae­tan Pen­necot, a 510 alum work­ing on Chauffeur’s lidar team, got a wor­ry­ing call from a ven­dor. Accord­ing to Waymo’s com­plaint, a small com­pa­ny called Odin Wave had placed an order for a cus­tom-made part that was extreme­ly sim­i­lar to one used in Google’s lidars.

Pen­necot shared this with his team leader, Pierre-Yves Droz, the cofounder of 510 Sys­tems. Droz did some dig­ging and replied in an email to Pen­necot (in French, which we’ve trans­lat­ed): “They’re clear­ly mak­ing a lidar. And it’s John (510’s old lawyer) who incor­po­rat­ed them. The date of incor­po­ra­tion cor­re­sponds to sev­er­al months after Antho­ny fell out of favor at Google.”

As the sto­ry emerges in court doc­u­ments, Droz had found Odin Wave’s com­pa­ny records. Not only had Levandowski’s lawyer found­ed the com­pa­ny in August 2012, but it was also based in a Berke­ley office build­ing that Levandows­ki owned, was being run by a friend of Levandowski’s, and its employ­ees includ­ed engi­neers he had worked with at Velo­dyne and 510 Sys­tems. One even spoke with Levandows­ki before being hired. The com­pa­ny was devel­op­ing long range lidars sim­i­lar to those Levandows­ki had worked on at 510 Sys­tems. But Levandowski’s name was nowhere on the firm’s paper­work.

Droz con­front­ed Levandows­ki, who denied any involve­ment, and Droz decid­ed not to fol­low the paper trail any fur­ther. “I was pret­ty hap­py work­ing at Google, and…I didn’t want to jeop­ar­dize that by...exposing more of Anthony’s shenani­gans,” he said at a depo­si­tion last month.

Odin Wave changed its name to Tyto Lidar in 2014, and in the spring of 2015 Levandows­ki was even part of a Google inves­ti­ga­tion into acquir­ing Tyto. This time, how­ev­er, Google passed on the pur­chase. That seemed to demor­al­ize Levandows­ki fur­ther. “He was rarely at work, and he left a lot of the respon­si­bil­i­ty [for] eval­u­at­ing peo­ple on the team to me or oth­ers,” said Droz in his depo­si­tion.

“Over time my patience with his manip­u­la­tions and lack of enthu­si­asm and com­mit­ment to the project [sic], it became clear­er and clear­er that this was a lost cause,” said Chris Urm­son in a depo­si­tion.

As he was torch­ing bridges at Google, Levandows­ki was itch­ing for a new chal­lenge. Luck­i­ly, Sebas­t­ian Thrun was back on the autonomous beat. Lar­ry Page and Thrun had been think­ing about elec­tric fly­ing taxis that could car­ry one or two peo­ple. Project Tiramisu, named after the dessert which means “lift me up” in Ital­ian, involved a winged plane fly­ing in cir­cles, pick­ing up pas­sen­gers below using a long teth­er.

Thrun knew just the per­son to kick­start Tiramisu. Accord­ing to a source work­ing there at the time, Levandows­ki was brought in to over­see Tiramisu as an “advi­sor and stake­hold­er.” Levandows­ki would show up at the project’s work­space in the evenings, and was involved in tests at one of Page’s ranch­es. Tiramisu’s teth­ers soon piv­ot­ed to a ride-aboard elec­tric drone, now called the Kit­ty Hawk fly­er. Thrun is CEO of Kit­ty Hawk, which is fund­ed by Page rather than Alpha­bet, the umbrel­la com­pa­ny that now owns Google and its sib­ling com­pa­nies.

Waymo’s com­plaint says that around this time Levandows­ki start­ed solic­it­ing Google col­leagues to leave and start a com­peti­tor in the autonomous vehi­cle busi­ness. Droz tes­ti­fied that Levandows­ki told him it “would be nice to cre­ate a new self-dri­ving car start­up.” Fur­ther­more, he said that Uber would be inter­est­ed in buy­ing the team respon­si­ble for Google’s lidar.

Uber had explod­ed onto the self-dri­ving car scene ear­ly in 2015, when it lured almost 50 engi­neers away from Carnegie Mel­lon Uni­ver­si­ty to form the core of its Advanced Tech­nolo­gies Cen­ter. Uber cofounder Travis Kalan­ick had described autonomous tech­nol­o­gy as an exis­ten­tial threat to the ride-shar­ing com­pa­ny, and was hir­ing furi­ous­ly. Accord­ing to Droz, Levandows­ki said that he began meet­ing Uber exec­u­tives that sum­mer.

When Urm­son learned of Levandowski’s recruit­ing efforts, his depo­si­tion states, he sent an email to human resources in August begin­ning, “We need to fire Antho­ny Levandows­ki.” Despite an inves­ti­ga­tion, that did not hap­pen.

But Levandowski’s now not-so-secret plan would soon see him leav­ing of his own accord—with a moun­tain of cash. In 2015, Google was due to start­ing pay­ing the Chauf­feur bonus­es, linked to a val­u­a­tion that it would have “sole and absolute dis­cre­tion” to cal­cu­late. Accord­ing to pre­vi­ous­ly unre­port­ed court fil­ings, exter­nal con­sul­tants cal­cu­lat­ed the self-dri­ving car project as being worth $8.5 bil­lion. Google ulti­mate­ly val­ued Chauf­feur at around half that amount: $4.5 bil­lion. Despite this down­grade, Levandowski’s share in Decem­ber 2015 amount­ed to over $50 mil­lion – near­ly twice as much as the sec­ond largest bonus of $28 mil­lion, paid to Chris Urm­son.

**********

Otto seemed to spring forth ful­ly formed in May 2016, demon­strat­ing a self-dri­ving 18-wheel truck bar­rel­ing down a Neva­da high­way with no one behind the wheel. In real­i­ty, Levandows­ki had been plan­ning it for some time.

Levandows­ki and his Otto cofounders at Google had spent the Christ­mas hol­i­days and the first weeks of 2016 tak­ing their recruit­ment cam­paign up a notch, accord­ing to Way­mo court fil­ings. Waymo’s com­plaint alleges Levandows­ki told col­leagues he was plan­ning to “repli­cate” Waymo’s tech­nol­o­gy at a com­peti­tor, and was even solic­it­ing his direct reports at work.

One engi­neer who had worked at 510 Sys­tems attend­ed a bar­be­cue at Levandowski’s home in Palo Alto, where Levandows­ki pitched his for­mer col­leagues and cur­rent Googlers on the start­up. “He want­ed every Way­mo per­son to resign simul­ta­ne­ous­ly, a ful­ly syn­chro­nized walk­out. He was fir­ing peo­ple up for that,” remem­bers the engi­neer.

On Jan­u­ary 27, Levandows­ki resigned from Google with­out notice. With­in weeks, Levandows­ki had a draft con­tract to sell Otto to Uber for an amount wide­ly report­ed as $680 mil­lion. Although the full-scale syn­chro­nized walk­out nev­er hap­pened, half a dozen Google employ­ees went with Levandows­ki, and more would join in the months ahead. But the new com­pa­ny still did not have a prod­uct to sell.

Levandows­ki brought Neva­da lob­by­ist David Gold­wa­ter back to help. “There was some brain­storm­ing with Antho­ny and his team,” said Gold­wa­ter in an inter­view. “We were look­ing to do a demon­stra­tion project where we could show what he was doing.”

After explor­ing the idea of an autonomous pas­sen­ger shut­tle in Las Vegas, Otto set­tled on devel­op­ing a dri­ver­less semi-truck. But with the Uber deal rush­ing for­ward, Levandows­ki need­ed results fast. “By the time Otto was ready to go with the truck, they want­ed to get right on the road,” said Gold­wa­ter. That meant demon­strat­ing their pro­to­type with­out obtain­ing the very autonomous vehi­cle licence Levandows­ki had per­suad­ed Neva­da to adopt. (One state offi­cial called this move “ille­gal.”) Levandows­ki also had Otto acquire the con­tro­ver­sial Tyto Lidar—the com­pa­ny based in the build­ing he owned—in May, for an undis­closed price.

The full-court press worked. Uber com­plet­ed its own acqui­si­tion of Otto in August, and Uber founder Travis Kalan­ick put Levandows­ki in charge of the com­bined com­pa­nies’ self-dri­ving efforts across per­son­al trans­porta­tion, deliv­ery and truck­ing. Uber would even pro­pose a Tiramisu-like autonomous air taxi called Uber Ele­vate. Now report­ing direct­ly to Kalan­ick and in charge of a 1500-strong group, Levandows­ki demand­ed the email address “robot@uber.com.”

In Kalan­ick, Levandows­ki found both a soul­mate and a men­tor to replace Sebas­t­ian Thrun. Text mes­sages between the two, dis­closed dur­ing the lawsuit’s dis­cov­ery process, cap­ture Levandows­ki teach­ing Kalan­ick about lidar at late night tech ses­sions, while Kalan­ick shared advice on man­age­ment. “Down to hang out this eve and mas­ter­mind some shit,” texted Kalan­ick, short­ly after the acqui­si­tion. “We’re going to take over the world. One robot at a time,” wrote Levandows­ki anoth­er time.

But Levandowski’s amaz­ing robot future was about to crum­ble before his eyes.

***********

Last Decem­ber, Uber launched a pilot self-dri­ving taxi pro­gram in San Fran­cis­co. As with Otto in Neva­da, Levandows­ki failed to get a license to oper­ate the high-tech vehi­cles, claim­ing that because the cars need­ed a human over­see­ing them, they were not tru­ly autonomous. The DMV dis­agreed and revoked the vehi­cles’ licens­es. Even so, dur­ing the week the cars were on the city’s streets, they had been spot­ted run­ning red lights on numer­ous occa­sions.

Worse was yet to come. Levandows­ki had always been a con­tro­ver­sial fig­ure at Google. With his abrupt res­ig­na­tion, the launch of Otto, and its rapid acqui­si­tion by Uber, Google launched an inter­nal inves­ti­ga­tion in the sum­mer of 2016. It found that Levandows­ki had down­loaded near­ly 10 giga­bytes of Google’s secret files just before he resigned, many of them relat­ing to lidar tech­nol­o­gy.

Also in Decem­ber 2016, in an echo of the Tyto inci­dent, a Way­mo employ­ee was acci­den­tal­ly sent an email from a ven­dor that includ­ed a draw­ing of an Otto cir­cuit board. The design looked very sim­i­lar to Waymo’s cur­rent lidars.

Way­mo says the “final piece of the puz­zle” came from a sto­ry about Otto I wrote for Backchan­nel based on a pub­lic records request. A doc­u­ment sent by Otto to Neva­da offi­cials boast­ed the com­pa­ny had an “in-house cus­tom-built 64-laser” lidar sys­tem. To Way­mo, that sound­ed very much like tech­nol­o­gy it had devel­oped. In Feb­ru­ary this year, Way­mo filed its head­line law­suit accus­ing Uber (along with Otto Truck­ing, yet anoth­er of Levandowski’s com­pa­nies, but one that Uber had not pur­chased) of vio­lat­ing its patents and mis­ap­pro­pri­at­ing trade secrets on lidar and oth­er tech­nolo­gies.

Uber imme­di­ate­ly denied the accu­sa­tions and has con­sis­tent­ly main­tained its inno­cence. Uber says there is no evi­dence that any of Waymo’s tech­ni­cal files ever came to Uber, let alone that Uber ever made use of them. While Levandows­ki is not named as a defen­dant, he has refused to answer ques­tions in depo­si­tions with Waymo’s lawyers and is expect­ed to do the same at tri­al. (He turned down sev­er­al requests for inter­views for this sto­ry.) He also didn’t ful­ly coop­er­ate with Uber’s own inves­ti­ga­tion into the alle­ga­tions, and that, Uber says, is why it fired him in May.

Levandows­ki prob­a­bly does not need a job. With the pur­chase of 510 Sys­tems and Anthony’s Robots, his salary, and bonus­es, Levandows­ki earned at least $120 mil­lion from his time at Google. Some of that mon­ey has been invest­ed in mul­ti­ple real estate devel­op­ments with his col­lege friend Randy Miller, includ­ing sev­er­al large projects in Oak­land and Berke­ley.

But Levandows­ki has kept busy behind the scenes. In August, court fil­ings say, he per­son­al­ly tracked down a pair of ear­rings giv­en to a Google employ­ee at her going-away par­ty in 2014. The ear­rings were made from con­fi­den­tial lidar cir­cuit boards, and will pre­sum­ably be used by Otto Trucking’s lawyers to sug­gest that Way­mo does not keep a very close eye on its trade secrets.

Some of Levandowski’s friends and col­leagues have expressed shock at the alle­ga­tions he faces, say­ing that they don’t reflect the per­son they knew. “It is...in char­ac­ter for Antho­ny to play fast and loose with things like intel­lec­tu­al prop­er­ty if it’s in pur­suit of build­ing his dream robot,” said Ben Dis­coe. “[But] I was a lit­tle sur­prised at the alleged mag­ni­tude of his dis­re­gard for IP.”

“Def­i­nite­ly one of Anthony’s faults is to be aggres­sive as he is, but it’s also one of his great attrib­ut­es. I don’t see [him doing] all the oth­er stuff he has been accused of,” said David Gold­wa­ter.

But Lar­ry Page is no longer con­vinced that Levandows­ki was key to Chauffeur’s suc­cess. In his depo­si­tion to the court, Page said, “I believe Anthony’s con­tri­bu­tions are quite pos­si­bly neg­a­tive of a high amount.” At Uber, some engi­neers pri­vate­ly say that Levandowski’s poor man­age­ment style set back that company’s self-dri­ving effort by a cou­ple of years.

Even after this tri­al is done, Levandows­ki will not be able to rest easy. In May, a judge referred evi­dence from the case to the US Attorney’s office “for inves­ti­ga­tion of pos­si­ble theft of trade secrets,” rais­ing the pos­si­bil­i­ty of crim­i­nal pro­ceed­ings and prison time. Yet on the time­line that mat­ters to Antho­ny Levandows­ki, even that may not mean much. Build­ing a robot­i­cal­ly enhanced future is his pas­sion­ate life­time project. On the Way of the Future, law­suits or even a jail sen­tence might just feel like lit­tle bumps in the road.

“This case is teach­ing Antho­ny some hard lessons but I don’t see [it] keep­ing him down,” said Randy Miller. “He believes firm­ly in his vision of a bet­ter world through robot­ics and he’s con­vinced me of it. It’s clear to me that he’s on a mis­sion.”

“I think Antho­ny will rise from the ash­es,” agrees one friend and for­mer 510 Sys­tems engi­neer. “Antho­ny has the ambi­tion, the vision, and the abil­i­ty to recruit and dri­ve peo­ple. If he could just play it straight, he could be the next Steve Jobs or Elon Musk. But he just doesn’t know when to stop cut­ting cor­ners.”

———-

“God Is a Bot, and Antho­ny Levandows­ki Is His Mes­sen­ger” by Mark Har­ris; Wired; 09/27/2017

“But even the smartest car will crack up if you floor the gas ped­al too long. Once fet­ed by bil­lion­aires, Levandows­ki now finds him­self star­ring in a high-stakes pub­lic tri­al as his two for­mer employ­ers square off. By exten­sion, the whole tech­nol­o­gy indus­try is there in the dock with Levandows­ki. Can we ever trust self-dri­ving cars if it turns out we can’t trust the peo­ple who are mak­ing them?”

Can we ever trust self-dri­ving cars if it turns out we can’t trust the peo­ple who are mak­ing them? It’s an impor­tant ques­tion that does­n’t just apply to self-dri­ving cars. Like AI God­heads. Can we ever trust man-made AI God­heads if it turns out we can’t trust the peo­ple who are mak­ing it? These are the stu­pid ques­tions we have to now giv­en the dis­turb­ing num­ber of pow­er­ful peo­ple who dou­ble as evan­ge­list for tech­no-cult Lib­er­tar­i­an ide­olo­gies. Espe­cial­ly when they are spe­cial­ist in cre­at­ing auto­mat­ed vehi­cles and have a deep pas­sion for tak­ing over the world. Pos­si­bly tak­ing over the world mil­i­tar­i­ly using robots:

...
Over the next few years, Levandows­ki was key to Chauffeur’s progress. 510 Sys­tems built five more self-dri­ving cars for Google—as well as ran­dom gad­gets like an autonomous trac­tor and a portable lidar sys­tem. “Antho­ny is light­ning in a bot­tle, he has so much ener­gy and so much vision,” remem­bers a friend and for­mer 510 engi­neer. “I frick­ing loved brain­storm­ing with the guy. I loved that we could cre­ate a vision of the world that didn’t exist yet and both fall in love with that vision.”

But there were down­sides to his man­ic ener­gy, too. “He had this very weird moti­va­tion about robots tak­ing over the world—like actu­al­ly tak­ing over, in a mil­i­tary sense,” said the same engi­neer. “It was like [he want­ed] to be able to con­trol the world, and robots were the way to do that. He talked about start­ing a new coun­try on an island. Pret­ty wild and creepy stuff. And the biggest thing is that he’s always got a secret plan, and you’re not going to know about it.”
...

Yeah, that’s dis­turb­ing. And it does­n’t help that Levandows­ki appar­ent­ly found a soul­mate and men­tor in the guy wide­ly viewed as one of the most socio­path­ic CEOs today: Uber CEO Travis Kalan­ick:

...
The full-court press worked. Uber com­plet­ed its own acqui­si­tion of Otto in August, and Uber founder Travis Kalan­ick put Levandows­ki in charge of the com­bined com­pa­nies’ self-dri­ving efforts across per­son­al trans­porta­tion, deliv­ery and truck­ing. Uber would even pro­pose a Tiramisu-like autonomous air taxi called Uber Ele­vate. Now report­ing direct­ly to Kalan­ick and in charge of a 1500-strong group, Levandows­ki demand­ed the email address “robot@uber.com.”

In Kalan­ick, Levandows­ki found both a soul­mate and a men­tor to replace Sebas­t­ian Thrun. Text mes­sages between the two, dis­closed dur­ing the lawsuit’s dis­cov­ery process, cap­ture Levandows­ki teach­ing Kalan­ick about lidar at late night tech ses­sions, while Kalan­ick shared advice on man­age­ment. “Down to hang out this eve and mas­ter­mind some shit,” texted Kalan­ick, short­ly after the acqui­si­tion. “We’re going to take over the world. One robot at a time,” wrote Levandows­ki anoth­er time.
...

“We’re going to take over the world. One robot at a time”

So that gives us an idea of how Levandowski’s AI reli­gion is going to be evan­ge­lized: via his army of robots. Although it’s unclear if his future reli­gion is actu­al­ly intend­ed for us mere humans. After all, for the hard­core Tran­shu­man­ists we’re all sup­posed to fuse with machines or upload our brains so it’s very pos­si­ble humans aren’t actu­al­ly part of Levandowski’s vision for that bet­ter tomor­row. A vision that, as the Cica­da 3301 weird­ness reminds us, prob­a­bly isn’t lim­it­ed to Levandows­ki. *gulp*

Just what the world needs: an AI-pow­ered ‘gay­dar’ algo­rithm that pur­ports to to be able to detect who is gay and who isn’t just by look­ing at faces. Although it’s not actu­al­ly that impres­sive. The ‘gay­dar’ algo­rithm is instead giv­en pairs of faces, one of a het­ero­sex­u­al indi­vid­ual and one of a homo­sex­u­al indi­vid­ual, and the tries to iden­ti­fy the gay per­son. And appar­ent­ly does so cor­rect­ly at a rate of 81 per­cent of cas­es for men and 71 per­cent of cas­es for women, sig­nif­i­cant­ly bet­ter than the 50 per­cent rate we would expect just from ran­dom chance. It’s the kind of gay­dar tech­nol­o­gy that might not be good enough to just ‘pick the gays from a crowd’, but still more than ade­quate for poten­tial­ly being abused. And, more gen­er­al­ly, it’s the kind of research that not sur­pris­ing­ly is rais­ing con­cerns about this cre­at­ing a a 21st cen­tu­ry ver­sion of physig­no­my, the pseu­do­science based on the idea that peo­ples’ char­ac­ter is reflect­ed in their faces.

But as the researchers behind the study put it, we don’t need to wor­ry about this being a high-tech exam­ple of phys­iog­no­my because their gay­dar uses hard sci­ence. And while the researchers agree that phys­iog­no­my is pseu­do­science, they also note that the pseu­do­science nature of phys­iog­no­my does­n’t mean AIs can’t actu­al­ly learn some­thing about you just by look­ing at you. Yep. That’s the reas­sur­ance we’re get­ting from these researchers. Don’t wor­ry about AI dri­ving a 21st cen­tu­ry ver­sion of phys­iog­no­my because they are using much bet­ter sci­ence com­pared to the past. Feel­ing reas­sured?

The Verge

The inven­tion of AI ‘gay­dar’ could be the start of some­thing much worse
Researchers claim they can spot gay peo­ple from a pho­to, but crit­ics say we’re revis­it­ing pseu­do­science

by James Vin­cent
Sep 21, 2017, 1:24pm EDT

Two weeks ago, a pair of researchers from Stan­ford Uni­ver­si­ty made a star­tling claim. Using hun­dreds of thou­sands of images tak­en from a dat­ing web­site, they said they had trained a facial recog­ni­tion sys­tem that could iden­ti­fy whether some­one was straight or gay just by look­ing at them. The work was first cov­ered by The Econ­o­mist, and oth­er pub­li­ca­tions soon fol­lowed suit, with head­lines like “New AI can guess whether you’re gay or straight from a pho­to­graph” and “AI Can Tell If You’re Gay From a Pho­to, and It’s Ter­ri­fy­ing.”

As you might have guessed, it’s not as straight­for­ward as that. (And to be clear, based on this work alone, AI can’t tell whether some­one is gay or straight from a pho­to.) But the research cap­tures com­mon fears about arti­fi­cial intel­li­gence: that it will open up new avenues for sur­veil­lance and con­trol, and could be par­tic­u­lar­ly harm­ful for mar­gin­al­ized peo­ple. One of the paper’s authors, Dr Michal Kosin­s­ki, says his intent is to sound the alarm about the dan­gers of AI, and warns that facial recog­ni­tion will soon be able to iden­ti­fy not only someone’s sex­u­al ori­en­ta­tion, but their polit­i­cal views, crim­i­nal­i­ty, and even their IQ.

With state­ments like these, some wor­ry we’re reviv­ing an old belief with a bad his­to­ry: that you can intu­it char­ac­ter from appear­ance. This pseu­do­science, phys­iog­no­my, was fuel for the sci­en­tif­ic racism of the 19th and 20th cen­turies, and gave moral cov­er to some of humanity’s worst impuls­es: to demo­nize, con­demn, and exter­mi­nate fel­low humans. Crit­ics of Kosinski’s work accuse him of replac­ing the calipers of the 19th cen­tu­ry with the neur­al net­works of the 21st, while the pro­fes­sor him­self says he is hor­ri­fied by his find­ings, and hap­py to be proved wrong. “It’s a con­tro­ver­sial and upset­ting sub­ject, and it’s also upset­ting to us,” he tells The Verge.

But is it pos­si­ble that pseu­do­science is sneak­ing back into the world, dis­guised in new garb thanks to AI? Some peo­ple say machines are sim­ply able to read more about us than we can our­selves, but what if we’re train­ing them to car­ry out our prej­u­dices, and, in doing so, giv­ing new life to old ideas we right­ly dis­missed? How are we going to know the dif­fer­ence?

Can AI real­ly spot sex­u­al ori­en­ta­tion?

First, we need to look at the study at the heart of the recent debate, writ­ten by Kosin­s­ki and his co-author Yilun Wang. Its results have been poor­ly report­ed, with a lot of the hype com­ing from mis­rep­re­sen­ta­tions of the system’s accu­ra­cy. The paper states: “Giv­en a sin­gle facial image, [the soft­ware] could cor­rect­ly dis­tin­guish between gay and het­ero­sex­u­al men in 81 per­cent of cas­es, and in 71 per­cent of cas­es for women.” These rates increase when the sys­tem is giv­en five pic­tures of an indi­vid­ual: up to 91 per­cent for men, and 83 per­cent for women.

On the face of it, this sounds like “AI can tell if a man is gay or straight 81 per­cent of the time by look­ing at his pho­to.” (Thus the head­lines.) But that’s not what the fig­ures mean. The AI wasn’t 81 per­cent cor­rect when being shown ran­dom pho­tos: it was test­ed on a pair of pho­tos, one of a gay per­son and one of a straight per­son, and then asked which indi­vid­ual was more like­ly to be gay. It guessed right 81 per­cent of the time for men and 71 per­cent of the time for women, but the struc­ture of the test means it start­ed with a base­line of 50 per­cent — that’s what it’d get guess­ing at ran­dom. And although it was sig­nif­i­cant­ly bet­ter than that, the results aren’t the same as say­ing it can iden­ti­fy anyone’s sex­u­al ori­en­ta­tion 81 per­cent of the time.

As Philip Cohen, a soci­ol­o­gist at the Uni­ver­si­ty of Mary­land who wrote a blog post cri­tiquing the paper, told The Verge: “Peo­ple are scared of a sit­u­a­tion where you have a pri­vate life and your sex­u­al ori­en­ta­tion isn’t known, and you go to an air­port or a sport­ing event and a com­put­er scans the crowd and iden­ti­fies whether you’re gay or straight. But there’s just not much evi­dence this tech­nol­o­gy can do that.”

Kosin­s­ki and Wang make this clear them­selves toward the end of the paper when they test their sys­tem against 1,000 pho­tographs instead of two. They ask the AI to pick out who is most like­ly to be gay in a dataset in which 7 per­cent of the pho­to sub­jects are gay, rough­ly reflect­ing the pro­por­tion of straight and gay men in the US pop­u­la­tion. When asked to select the 100 indi­vid­u­als most like­ly to be gay, the sys­tem gets only 47 out of 70 pos­si­ble hits. The remain­ing 53 have been incor­rect­ly iden­ti­fied. And when asked to iden­ti­fy a top 10, nine are right.

If you were a bad actor try­ing to use this sys­tem to iden­ti­fy gay peo­ple, you couldn’t know for sure you were get­ting cor­rect answers. Although, if you used it against a large enough dataset, you might get most­ly cor­rect guess­es. Is this dan­ger­ous? If the sys­tem is being used to tar­get gay peo­ple, then yes, of course. But the rest of the study sug­gests the pro­gram has even fur­ther lim­i­ta­tions.

What can com­put­ers real­ly see that humans can’t?

It’s also not clear what fac­tors the facial recog­ni­tion sys­tem is using to make its judge­ments. Kosin­s­ki and Wang’s hypoth­e­sis is that it’s pri­mar­i­ly iden­ti­fy­ing struc­tur­al dif­fer­ences: fem­i­nine fea­tures in the faces of gay men and mas­cu­line fea­tures in the faces of gay women. But it’s pos­si­ble that the AI is being con­fused by oth­er stim­uli — like facial expres­sions in the pho­tos.

This is par­tic­u­lar­ly rel­e­vant because the images used in the study were tak­en from a dat­ing web­site. As Greg­gor Matt­son, a pro­fes­sor of soci­ol­o­gy at Ober­lin Col­lege, point­ed out in a blog post, this means that the images them­selves are biased, as they were select­ed specif­i­cal­ly to attract some­one of a cer­tain sex­u­al ori­en­ta­tion. They almost cer­tain­ly play up to our cul­tur­al expec­ta­tions of how gay and straight peo­ple should look, and, to fur­ther nar­row their applic­a­bil­i­ty, all the sub­jects were white, with no inclu­sion of bisex­u­al or self-iden­ti­fied trans indi­vid­u­als. If a straight male choos­es the most stereo­typ­i­cal­ly “man­ly” pic­ture of him­self for a dat­ing site, it says more about what he thinks soci­ety wants from him than a link between the shape of his jaw and his sex­u­al ori­en­ta­tion.

To try and ensure their sys­tem was look­ing at facial struc­ture only, Kosin­s­ki and Wang used soft­ware called VGG-Face, which encodes faces as strings of num­bers and has been used for tasks like spot­ting celebri­ty looka­likes in paint­ings. This pro­gram, they write, allows them to “min­i­mize the role [of] tran­sient fea­tures” like light­ing, pose, and facial expres­sion.

But researcher Tom White, who works on AI facial sys­tem, says VGG-Face is actu­al­ly very good at pick­ing up on these ele­ments. White point­ed this out on Twit­ter, and explained to The Verge over email how he’d test­ed the soft­ware and used it to suc­cess­ful­ly dis­tin­guish between faces with expres­sions like “neu­tral” and “hap­py,” as well as pos­es and back­ground col­or.

Speak­ing to The Verge, Kosin­s­ki says he and Wang have been explic­it that things like facial hair and make­up could be a fac­tor in the AI’s deci­sion-mak­ing, but he main­tains that facial struc­ture is the most impor­tant. “If you look at the over­all prop­er­ties of VGG-Face, it tends to put very lit­tle weight on tran­sient facial fea­tures,” Kosin­s­ki says. “We also pro­vide evi­dence that non-tran­sient facial fea­tures seem to be pre­dic­tive of sex­u­al ori­en­ta­tion.”

The prob­lem is, we can’t know for sure. Kosin­s­ki and Wang haven’t released the pro­gram they cre­at­ed or the pic­tures they used to train it. They do test their AI on oth­er pic­ture sources, to see if it’s iden­ti­fy­ing some fac­tor com­mon to all gay and straight, but these tests were lim­it­ed and also drew from a biased dataset — Face­book pro­file pic­tures from men who liked pages such as “I love being Gay,” and “Gay and Fab­u­lous.”

Do men in these groups serve as rea­son­able prox­ies for all gay men? Prob­a­bly not, and Kosin­s­ki says it’s pos­si­ble his work is wrong. “Many more stud­ies will need to be con­duct­ed to ver­i­fy [this],” he says. But it’s tricky to say how one could com­plete­ly elim­i­nate selec­tion bias to per­form a con­clu­sive test. Kosin­s­ki tells The Verge, “You don’t need to under­stand how the mod­el works to test whether it’s cor­rect or not.” How­ev­er, it’s the accep­tance of the opac­i­ty of algo­rithms that makes this sort of research so fraught.

If AI can’t show its work­ing, can we trust it?

AI researchers can’t ful­ly explain why their machines do the things they do. It’s a chal­lenge that runs through the entire field, and is some­times referred to as the “black box” prob­lem. Because of the meth­ods used to train AI, these pro­grams can’t show their work in the same way nor­mal soft­ware does, although researchers are work­ing to amend this.

In the mean­time, it leads to all sorts of prob­lems. A com­mon one is that sex­ist and racist bias­es are cap­tured from humans in the train­ing data and repro­duced by the AI. In the case of Kosin­s­ki and Wang’s work, the “black box” allows them to make a par­tic­u­lar sci­en­tif­ic leap of faith. Because they’re con­fi­dent their sys­tem is pri­mar­i­ly ana­lyz­ing facial struc­tures, they say their research shows that facial struc­tures pre­dict sex­u­al ori­en­ta­tion. (“Study 1a showed that facial fea­tures extract­ed by a [neur­al net­work] can be used to accu­rate­ly iden­ti­fy the sex­u­al ori­en­ta­tion of both men and women.”)

Experts say this is a mis­lead­ing claim that isn’t sup­port­ed by the lat­est sci­ence. There may be a com­mon cause for face shape and sex­u­al ori­en­ta­tion — the most prob­a­ble cause is the bal­ance of hor­mones in the womb — but that doesn’t mean face shape reli­ably pre­dicts sex­u­al ori­en­ta­tion, says Qazi Rah­man, an aca­d­e­m­ic at King’s Col­lege Lon­don who stud­ies the biol­o­gy of sex­u­al ori­en­ta­tion. “Biology’s a lit­tle bit more nuanced than we often give it cred­it for,” he tells The Verge. “The issue here is the strength of the asso­ci­a­tion.”

The idea that sex­u­al ori­en­ta­tion comes pri­mar­i­ly from biol­o­gy is itself con­tro­ver­sial. Rah­man, who believes that sex­u­al ori­en­ta­tion is most­ly bio­log­i­cal, prais­es Kosin­s­ki and Wang’s work. “It’s not junk sci­ence,” he says. “More like sci­ence some­one doesn’t like.” But when it comes to pre­dict­ing sex­u­al ori­en­ta­tion, he says there’s a whole pack­age of “atyp­i­cal gen­der behav­ior” that needs to be con­sid­ered. “The issue for me is more that [the study] miss­es the point, and that’s behav­ior.”

Reduc­ing the ques­tion of sex­u­al ori­en­ta­tion to a sin­gle, mea­sur­able fac­tor in the body has a long and often inglo­ri­ous his­to­ry. As Mat­ton writes in his blog post, approach­es have ranged from “19th cen­tu­ry mea­sure­ments of les­bians’ cli­toris­es and homo­sex­u­al men’s hips, to late 20th cen­tu­ry claims to have dis­cov­ered ‘gay genes,’ ‘gay brains,’ ‘gay ring fin­gers,’ ‘les­bian ears,’ and ‘gay scalp hair.’” The impact of this work is mixed, but at its worst it’s a tool of oppres­sion: it gives peo­ple who want to dehu­man­ize and per­se­cute sex­u­al minori­ties a “sci­en­tif­ic” pre­text.

Jen­ny Davis, a lec­tur­er in soci­ol­o­gy at the Aus­tralian Nation­al Uni­ver­si­ty, describes it as a form of bio­log­i­cal essen­tial­ism. This is the belief that things like sex­u­al ori­en­ta­tion are root­ed in the body. This approach, she says, is dou­ble-edged. On the one hand, it “does a use­ful polit­i­cal thing: detach­ing blame from same-sex desire. But on the oth­er hand, it rein­forces the deval­ued posi­tion of that kind of desire,” set­ting up het­ro­sex­u­al­i­ty as the norm and fram­ing homo­sex­u­al­i­ty as “less valu­able … a sort of ill­ness.”

...

Your char­ac­ter, as plain as the nose on your face

For cen­turies, peo­ple have believed that the face held the key to the char­ac­ter. The notion has its roots in ancient Greece, but was par­tic­u­lar­ly influ­en­tial in the 19th cen­tu­ry. Pro­po­nents of phys­iog­no­my sug­gest­ed that by mea­sur­ing things like the angle of someone’s fore­head or the shape of their nose, they could deter­mine if a per­son was hon­est or a crim­i­nal. Last year in Chi­na, AI researchers claimed they could do the same thing using facial recog­ni­tion.

Their research, pub­lished as “Auto­mat­ed Infer­ence on Crim­i­nal­i­ty Using Face Images,” caused a minor uproar in the AI com­mu­ni­ty. Sci­en­tists point­ed out flaws in the study, and con­clud­ed that that work was repli­cat­ing human prej­u­dices about what con­sti­tutes a “mean” or a “nice” face. In a wide­ly shared rebut­tal titled “Physiognomy’s New Clothes,” Google researcher Blaise Agüera y Arcas and two co-authors wrote that we should expect “more research in the com­ing years that has sim­i­lar … false claims to sci­en­tif­ic objec­tiv­i­ty in order to ‘laun­der’ human prej­u­dice and dis­crim­i­na­tion.” (Google declined to make Agüera y Arcas avail­able to com­ment on this report.)

Kosin­s­ki and Wang’s paper clear­ly acknowl­edges the dan­gers of phys­iog­no­my, not­ing that the prac­tice “is now uni­ver­sal­ly, and right­ly, reject­ed as a mix of super­sti­tion and racism dis­guised as sci­ence.” But, they con­tin­ue, just because a sub­ject is “taboo,” doesn’t mean it has no basis in truth. They say that because humans are able to read char­ac­ter­is­tics like per­son­al­i­ty in oth­er people’s faces with “low accu­ra­cy,” machines should be able to do the same but more accu­rate­ly.

Kosin­s­ki says his research isn’t phys­iog­no­my because it’s using rig­or­ous sci­en­tif­ic meth­ods, and his paper cites a num­ber of stud­ies show­ing that we can deduce (with vary­ing accu­ra­cy) traits about peo­ple by look­ing at them. “I was edu­cat­ed and made to believe that it’s absolute­ly impos­si­ble that the face con­tains any infor­ma­tion about your inti­mate traits, because phys­iog­no­my and phrenol­o­gy were just pseu­do­sciences,” he says. “But the fact that they were claim­ing things with­out any basis in fact, that they were mak­ing stuff up, doesn’t mean that this stuff is not real.” He agrees that phys­iog­no­my is not sci­ence, but says there may be truth in its basic con­cepts that com­put­ers can reveal.

For Davis, this sort of atti­tude comes from a wide­spread and mis­tak­en belief in the neu­tral­i­ty and objec­tiv­i­ty of AI. “Arti­fi­cial intel­li­gence is not in fact arti­fi­cial,” she tells The Verge. “Machines learn like humans learn. We’re taught through cul­ture and absorb the norms of social struc­ture, and so does arti­fi­cial intel­li­gence. So it will re-cre­ate, ampli­fy, and con­tin­ue on the tra­jec­to­ries we’ve taught it, which are always going to reflect exist­ing cul­tur­al norms.”

We’ve already cre­at­ed sex­ist and racist algo­rithms, and these sorts of cul­tur­al bias­es and phys­iog­no­my are real­ly just two sides of the same coin: both rely on bad evi­dence to judge oth­ers. The work by the Chi­nese researchers is an extreme exam­ple, but it’s cer­tain­ly not the only one. There’s at least one start­up already active that claims it can spot ter­ror­ists and pedophiles using face recog­ni­tion, and there are many oth­ers offer­ing to ana­lyze “emo­tion­al intel­li­gence” and con­duct AI-pow­ered sur­veil­lance.

Fac­ing up to what’s com­ing

But to return to the ques­tions implied by those alarm­ing head­lines about Kosin­s­ki and Wang’s paper: is AI going to be used to per­se­cute sex­u­al minori­ties?

This sys­tem? No. A dif­fer­ent one? Maybe.

Kosin­s­ki and Wang’s work is not invalid, but its results need seri­ous qual­i­fi­ca­tions and fur­ther test­ing. With­out that, all we know about their sys­tem is that it can spot with some reli­a­bil­i­ty the dif­fer­ence between self-iden­ti­fied gay and straight white peo­ple on one par­tic­u­lar dat­ing site. We don’t know that it’s spot­ted a bio­log­i­cal dif­fer­ence com­mon to all gay and straight peo­ple; we don’t know if it would work with a wider set of pho­tos; and the work doesn’t show that sex­u­al ori­en­ta­tion can be deduced with noth­ing more than, say, a mea­sure­ment of the jaw. It’s not decod­ed human sex­u­al­i­ty any more than AI chat­bots have decod­ed the art of a good con­ver­sa­tion. (Nor do its authors make such a claim.)

The research was pub­lished to warn peo­ple, say Kosin­s­ki, but he admits it’s an “unavoid­able para­dox” that to do so you have to explain how you did what you did. All the tools used in the paper are avail­able for any­one to find and put togeth­er them­selves. Writ­ing at the deep learn­ing edu­ca­tion site Fast.ai, researcher Jere­my Howard con­cludes: “It is prob­a­bly rea­son­ably [sic] to assume that many orga­ni­za­tions have already com­plet­ed sim­i­lar projects, but with­out pub­lish­ing them in the aca­d­e­m­ic lit­er­a­ture.”

We’ve already men­tioned star­tups work­ing on this tech, and it’s not hard to find gov­ern­ment regimes that would use it. In coun­tries like Iran and Sau­di Ara­bia homo­sex­u­al­i­ty is still pun­ish­able by death; in many oth­er coun­tries, being gay means being hound­ed, impris­oned, and tor­tured by the state. Recent reports have spo­ken of the open­ing of con­cen­tra­tion camps for gay men in the Chechen Repub­lic, so what if some­one there decides to make their own AI gay­dar, and scan pro­file pic­tures from Russ­ian social media?

Here, it becomes clear that the accu­ra­cy of sys­tems like Kosin­s­ki and Wang’s isn’t real­ly the point. If peo­ple believe AI can be used to deter­mine sex­u­al pref­er­ence, they will use it. With that in mind, it’s more impor­tant than ever that we under­stand the lim­i­ta­tions of arti­fi­cial intel­li­gence, to try and neu­tral­ize dan­gers before they start impact­ing peo­ple. Before we teach machines our prej­u­dices, we need to first teach our­selves.

———-

“The inven­tion of AI ‘gay­dar’ could be the start of some­thing much worse” by James Vin­cent; The Verge; 09/21/2017

“Kosin­s­ki says his research isn’t phys­iog­no­my because it’s using rig­or­ous sci­en­tif­ic meth­ods, and his paper cites a num­ber of stud­ies show­ing that we can deduce (with vary­ing accu­ra­cy) traits about peo­ple by look­ing at them. “I was edu­cat­ed and made to believe that it’s absolute­ly impos­si­ble that the face con­tains any infor­ma­tion about your inti­mate traits, because phys­iog­no­my and phrenol­o­gy were just pseu­do­sciences,” he says. “But the fact that they were claim­ing things with­out any basis in fact, that they were mak­ing stuff up, doesn’t mean that this stuff is not real.” He agrees that phys­iog­no­my is not sci­ence, but says there may be truth in its basic con­cepts that com­put­ers can reveal.”

It’s not a return of the phys­iog­no­my pseu­do­science but “there may be truth in [phys­iog­no­my’s] basic con­cepts that com­put­ers can reveal.” That’s seri­ous­ly the mes­sage from these researchers, along with a mes­sage of con­fi­dence that their algo­rithm is work­ing sole­ly from facial fea­tures and not oth­er more tran­sient fea­tures. And based on that con­fi­dence in their algo­rithm the researchers point to their results on evi­dence that gay peo­ple have bio­log­i­cal­ly dif­fer­ent faces...even though they can’t actu­al­ly deter­mine what the algo­rithm is look­ing at when com­ing to its con­clu­sion:

...
If AI can’t show its work­ing, can we trust it?

AI researchers can’t ful­ly explain why their machines do the things they do. It’s a chal­lenge that runs through the entire field, and is some­times referred to as the “black box” prob­lem. Because of the meth­ods used to train AI, these pro­grams can’t show their work in the same way nor­mal soft­ware does, although researchers are work­ing to amend this.

In the mean­time, it leads to all sorts of prob­lems. A com­mon one is that sex­ist and racist bias­es are cap­tured from humans in the train­ing data and repro­duced by the AI. In the case of Kosin­s­ki and Wang’s work, the “black box” allows them to make a par­tic­u­lar sci­en­tif­ic leap of faith. Because they’re con­fi­dent their sys­tem is pri­mar­i­ly ana­lyz­ing facial struc­tures, they say their research shows that facial struc­tures pre­dict sex­u­al ori­en­ta­tion. (“Study 1a showed that facial fea­tures extract­ed by a [neur­al net­work] can be used to accu­rate­ly iden­ti­fy the sex­u­al ori­en­ta­tion of both men and women.”)

Experts say this is a mis­lead­ing claim that isn’t sup­port­ed by the lat­est sci­ence. There may be a com­mon cause for face shape and sex­u­al ori­en­ta­tion — the most prob­a­ble cause is the bal­ance of hor­mones in the womb — but that doesn’t mean face shape reli­ably pre­dicts sex­u­al ori­en­ta­tion, says Qazi Rah­man, an aca­d­e­m­ic at King’s Col­lege Lon­don who stud­ies the biol­o­gy of sex­u­al ori­en­ta­tion. “Biology’s a lit­tle bit more nuanced than we often give it cred­it for,” he tells The Verge. “The issue here is the strength of the asso­ci­a­tion.”

The idea that sex­u­al ori­en­ta­tion comes pri­mar­i­ly from biol­o­gy is itself con­tro­ver­sial. Rah­man, who believes that sex­u­al ori­en­ta­tion is most­ly bio­log­i­cal, prais­es Kosin­s­ki and Wang’s work. “It’s not junk sci­ence,” he says. “More like sci­ence some­one doesn’t like.” But when it comes to pre­dict­ing sex­u­al ori­en­ta­tion, he says there’s a whole pack­age of “atyp­i­cal gen­der behav­ior” that needs to be con­sid­ered. “The issue for me is more that [the study] miss­es the point, and that’s behav­ior.”

Reduc­ing the ques­tion of sex­u­al ori­en­ta­tion to a sin­gle, mea­sur­able fac­tor in the body has a long and often inglo­ri­ous his­to­ry. As Mat­ton writes in his blog post, approach­es have ranged from “19th cen­tu­ry mea­sure­ments of les­bians’ cli­toris­es and homo­sex­u­al men’s hips, to late 20th cen­tu­ry claims to have dis­cov­ered ‘gay genes,’ ‘gay brains,’ ‘gay ring fin­gers,’ ‘les­bian ears,’ and ‘gay scalp hair.’” The impact of this work is mixed, but at its worst it’s a tool of oppres­sion: it gives peo­ple who want to dehu­man­ize and per­se­cute sex­u­al minori­ties a “sci­en­tif­ic” pre­text.

Jen­ny Davis, a lec­tur­er in soci­ol­o­gy at the Aus­tralian Nation­al Uni­ver­si­ty, describes it as a form of bio­log­i­cal essen­tial­ism. This is the belief that things like sex­u­al ori­en­ta­tion are root­ed in the body. This approach, she says, is dou­ble-edged. On the one hand, it “does a use­ful polit­i­cal thing: detach­ing blame from same-sex desire. But on the oth­er hand, it rein­forces the deval­ued posi­tion of that kind of desire,” set­ting up het­ro­sex­u­al­i­ty as the norm and fram­ing homo­sex­u­al­i­ty as “less valu­able … a sort of ill­ness.”
...

“In the mean­time, it leads to all sorts of prob­lems. A com­mon one is that sex­ist and racist bias­es are cap­tured from humans in the train­ing data and repro­duced by the AI. In the case of Kosin­s­ki and Wang’s work, the “black box” allows them to make a par­tic­u­lar sci­en­tif­ic leap of faith. Because they’re con­fi­dent their sys­tem is pri­mar­i­ly ana­lyz­ing facial struc­tures, they say their research shows that facial struc­tures pre­dict sex­u­al ori­en­ta­tion. (“Study 1a showed that facial fea­tures extract­ed by a [neur­al net­work] can be used to accu­rate­ly iden­ti­fy the sex­u­al ori­en­ta­tion of both men and women.”)”

So if this research was put forth as a kind of warn­ing to the pub­lic, which is how the researchers are fram­ing it, it’s quite a warn­ing. Both a warn­ing that algo­rithms like this are being devel­oped and a warn­ing of how read­i­ly the con­clu­sions of these algo­rithms might be accept­ed as evi­dence of an under­ly­ing bio­log­i­cal find­ing (as opposed to a ‘black box’ arti­fact that could be pick­ing up all sort of bio­log­i­cal and social cues).

And don’t for­get, even if these algo­rithms do actu­al­ly stum­ble across real asso­ci­a­tions that can be teased out by these AI-dri­ven algo­rithms with just some pic­tures of some­one (or maybe some addi­tion­al bio­met­ric data picked up by the “smart kiosks” of the not-too-dis­tant future), there’s a big dif­fer­ence between demon­strat­ing the abil­i­ty to dis­cern some­thing sta­tis­ti­cal­ly across large data sets and being able to do that with the kind of accu­ra­cy where you don’t have to sig­nif­i­cant­ly wor­ry about jump­ing to the wrong con­clu­sion (assum­ing you aren’t using the tech­nol­o­gy in an abu­sive man­ner in the first place). Even if some­one devel­ops an algo­rithm that can accu­rate guess sex­u­al ori­en­ta­tion 95 per­cent of the time that still leaves a pret­ty sub­stan­tial 5 per­cent chance of get­ting it wrong. And the only way to avoid those incor­rect con­clu­sions is to devel­op an algo­rithm that’s so good at infer­ring sex­u­al ori­en­ta­tion it’s basi­cal­ly nev­er wrong, assum­ing that’s pos­si­ble. And, of course, if such an algo­rithm was devel­oped with that kind of accu­ra­cy that would be real­ly creepy. It points towards one of the scari­er aspects of this kind of tech­nol­o­gy: In order to ensure your pri­va­cy-invad­ing algo­rithms don’t risk jump­ing to erro­neous con­clu­sions you need algo­rithms that are scar­i­ly good at invad­ing your pri­va­cy which is anoth­er rea­son we prob­a­bly should­n’t be pro­mot­ing 21st Cen­tu­ry phys­iog­no­my.

It looks like Google is final­ly get that shiny new object its been pin­ing for: a city. Yep, Side­walk Labs, owned by Google’s par­ent com­pa­ny Alpha­bet, just got per­mis­sion to build its own ‘city of the future’ on a 12-acre water­front dis­trict near Toron­to, filled with self-dri­ving shut­tles, adap­tive traf­fic lights that sense pedes­tri­ans, and under­ground tun­nels for freight-trans­port­ing robots. With sen­sors every­where.

And if that sounds ambi­tious, note that all these plans aren’t lim­it­ed to the ini­tial 12 acres. Alpha­bet report­ed­ly has plans to expand across 800 acres of Toron­to’s post-indus­tri­al water­front zone:

The Finan­cial Times

Alpha­bet to build futur­is­tic city in Toron­to
Plans for tech­nol­o­gy-enabled envi­ron­ment raise pri­va­cy con­cerns

by Leslie Hook in San Fran­cis­co
Octo­ber 17, 2017, 4:54 pm

Alpha­bet is set­ting out to build the city of the future, start­ing with a down­town dis­trict of Toron­to, in what it hopes will serve as a prov­ing ground for tech­nol­o­gy-enabled urban envi­ron­ments around the world.

In a first-of-its-kind project, Alphabet’s sub­sidiary Side­walk Labs will devel­op a 12-acre water­front dis­trict, Quay­side, with a view to expand across 800 acres of Toronto’s post-indus­tri­al water­front zone.

Self-dri­ving shut­tles, adap­tive traf­fic lights that sense pedes­tri­ans, mod­u­lar hous­ing and freight-deliv­er­ing robots that trav­el in under­ground tun­nels might all be part of the new devel­op­ment, accord­ing to the win­ning bid sub­mit­ted by Side­walk Labs.

In its pro­pos­al, Side­walk also said that Toron­to would need to waive or exempt many exist­ing reg­u­la­tions in areas like build­ing codes, trans­porta­tion, and ener­gy in order to build the city it envi­sioned. The project may need “sub­stan­tial for­bear­ances from exist­ing laws and reg­u­la­tions,” the group said.

Alpha­bet chair­man Eric Schmidt and Cana­di­an prime min­is­ter Justin Trudeau announced the deal on Tues­day in Toron­to.

“We start­ed think­ing about all the things we could do if some­one would just give us a city and put us in charge,” said Eric Schmidt, exec­u­tive chair­man of Alpha­bet. “That’s not how it works, for all sorts of good rea­sons,” he added with a laugh.

For Alpha­bet, the project presents a chance to exper­i­ment with new ways to use tech­nol­o­gy — and data — in the real world. “This is not some ran­dom activ­i­ty from our per­spec­tive. This is the cul­mi­na­tion of almost 10 years of think­ing about how tech­nol­o­gy could improve people’s lives,” said Mr Schmidt.

...

Mr Trudeau described the project as a “test bed for new technologies...that will help us build clean­er, smarter, green­er, cities”.

“Eric [Schmidt] and I have been talk­ing about col­lab­o­rat­ing on this for a few years, and see­ing it all come togeth­er now is extra­or­di­nar­i­ly excit­ing,” he added.

One of the chal­lenges for the new dis­trict will be set­ting data poli­cies and address­ing con­cerns over pri­va­cy, which are par­tic­u­lar­ly acute because smart city tech­nolo­gies often rely on col­lect­ing vast amounts of data to make cities run more effi­cient­ly.

In the vision state­ment sub­mit­ted as part of its bid, Side­walk describes a vast sys­tem of sen­sors that will mon­i­tor every­thing from park bench­es and over­flow­ing waste bins, to noise and pol­lu­tion lev­els in hous­ing. The devel­op­ment will also pio­neer new approach­es to ener­gy, includ­ing a ther­mal grid and on-site gen­er­a­tion, and tech-enabled pri­ma­ry health­care that will be inte­grat­ed with social ser­vices.

The trans­porta­tion pro­pos­al for the dis­trict includes restrict­ing pri­vate vehi­cles, and instead offer­ing self-dri­ving shut­tles and bike paths that are heat­ed in the win­ter, accord­ing to the vision doc­u­ment. A series of under­ground util­i­ty tun­nels will house util­i­ties like elec­tri­cal wires and water pipes, and also pro­vide path­ways for freight-deliv­er­ing robots.

Side­walk Labs, a sub­sidiary of Alpha­bet that was found­ed in 2015 by Dan Doc­to­roff, a for­mer deputy may­or of New York, will spend $50m on ini­tial plan­ning and test­ing for the devel­op­ment. As part of the effort, Google will also move its Cana­di­an head­quar­ters to Toron­to.

Mr Doc­to­roff said the group would present a detailed plan in one year, fol­low­ing exten­sive con­sul­ta­tions with the com­mu­ni­ty. “Our goal here is to lis­ten, to under­stand,” he said. “This has to be a com­mu­ni­ty conversation...otherwise it won’t have the polit­i­cal cred­i­bil­i­ty to do things that are quite bold.”

———-

“Alpha­bet to build futur­is­tic city in Toron­to” by Leslie Hook; The Finan­cial Times; 10/17/2017

“In its pro­pos­al, Side­walk also said that Toron­to would need to waive or exempt many exist­ing reg­u­la­tions in areas like build­ing codes, trans­porta­tion, and ener­gy in order to build the city it envi­sioned. The project may need “sub­stan­tial for­bear­ances from exist­ing laws and reg­u­la­tions,” the group said.”

LOL, yeah, it’s a good bet that A LOT of exist­ing laws and reg­u­la­tions are going to have be waived. Espe­cial­ly laws involv­ing per­son­al data pri­va­cy. And it sounds like the data col­lect­ed isn’t just going to involve your where­abouts and oth­er infor­ma­tion the sen­sors every­where will be able to pick up. Alpha­bet is also envi­sion­ing “tech-enabled pri­ma­ry health­care that will be inte­grat­ed with social ser­vices”, which means med­ical data pri­va­cy laws are prob­a­bly also going to have to get waived:

...
One of the chal­lenges for the new dis­trict will be set­ting data poli­cies and address­ing con­cerns over pri­va­cy, which are par­tic­u­lar­ly acute because smart city tech­nolo­gies often rely on col­lect­ing vast amounts of data to make cities run more effi­cient­ly.

In the vision state­ment sub­mit­ted as part of its bid, Side­walk describes a vast sys­tem of sen­sors that will mon­i­tor every­thing from park bench­es and over­flow­ing waste bins, to noise and pol­lu­tion lev­els in hous­ing. The devel­op­ment will also pio­neer new approach­es to ener­gy, includ­ing a ther­mal grid and on-site gen­er­a­tion, and tech-enabled pri­ma­ry health­care that will be inte­grat­ed with social ser­vices.
...

Let’s also not for­get about the devel­op­ment of tech­nolo­gies that can col­lect per­son­al health infor­ma­tion like heart rates and breath­ing infor­ma­tion using WiFi sig­nals alone (which would pair nice­ly with Google’s plans to put free WiFi kiosks bristling with sen­sors on side­walks every­where. And as is pret­ty clear at this point, any­thing that can be sensed remote­ly will be sensed remote­ly in this new city. Because that’s half the point of the whole thing. So yeah, “sub­stan­tial for­bear­ances from exist­ing laws and reg­u­la­tions” will no doubt be required.

Inter­est­ing­ly, Alpha­bet recent­ly announced a new ini­tia­tive that sounds like exact­ly the kind of “tech-enabled pri­ma­ry health­care that will be inte­grat­ed with social ser­vices” the com­pa­ny has planned for its new city: City­block was just launched,. It’s a new Alpha­bet start­up focused on improv­ing health care man­age­ment by, sur­prise!, inte­grat­ing var­i­ous tech­nolo­gies into a health care sys­tem with the goal of bring­ing down costs and improv­ing out­comes. But it’s not sim­ply new tech­nol­o­gy that’s sup­posed to do this. Instead, that tech­nol­o­gy is to be used in a pre­ven­tive man­ner in order to address more expen­sive health con­di­tions before they get worse. As such, City­block is going to focus­es on behav­ioral health being. Yep, it’s a health care mod­el where a tech firm, paired with a health firm, tries to get to you live a more healthy lifestyle by col­lect­ing lots of data about you. And while this approach would undoubt­ed­ly cause wide­spread pri­va­cy con­cerns, those con­cerns will prob­a­bly be some­what stunt­ed in this case since the tar­get mar­ket City­block has in mind is poor peo­ple, espe­cial­ly Med­ic­aid patients in the US:

Fierce Health­care

Google’s par­ent com­pa­ny spins off an inno­v­a­tive start­up health­care provider

by Matt Kuhrt | Oct 5, 2017 8:49am

The lat­est Sil­i­con Val­ley bid to dis­rupt a tra­di­tion­al indus­try appears to be aimed at health­care. City­block, a start­up qui­et­ly launched by Google’s par­ent com­pa­ny Alpha­bet, will focus on pro­vid­ing team-based care for low-income com­mu­ni­ties.

The ven­ture comes from one of Alphabet’s inno­va­tion-ori­ent­ed groups, Side­walk Labs, and will rely upon a team-based care deliv­ery struc­ture that is sup­port­ed by doc­tors, behav­ioral health coach­es and tech­no­log­i­cal tools, accord­ing to an arti­cle from CNBC.

Efforts by health­care orga­ni­za­tions to improve care man­age­ment and increase patient engage­ment through social inter­ac­tion have attract­ed atten­tion, par­tic­u­lar­ly in the con­text of chron­ic con­di­tions, as Fierce­Health­care has pre­vi­ous­ly report­ed. While cell phones and social media apps have pro­vid­ed new avenues to boost patient engage­ment, inte­grat­ing those tech­nolo­gies into an effec­tive care deliv­ery mod­el has proven more com­plex. At the same time, major play­ers such as the Cen­ters for Medicare & Med­ic­aid Ser­vices, active­ly seek feed­back on mod­els that pri­or­i­tize behav­ioral health in response to the indus­try’s inter­est in the poten­tial for effi­cien­cy from an increased empha­sis on pre­ven­tive and ongo­ing care.

City­block aims to pro­vide Med­ic­aid and low­er-income Medicare ben­e­fi­cia­ries access to high-val­ue, read­i­ly avail­able per­son­al­ized health ser­vices. To do this, Iyah Romm, cofounder and CEO, writes in a blog post on Medi­um that the orga­ni­za­tion will apply lead­ing-edge care mod­els that ful­ly inte­grate pri­ma­ry care, behav­ioral health and social ser­vices. It expects to open its first clin­ic, which it calls a Neigh­bor­hood Health Hub, in New York City in 2018.

Cityblock’s inter­dis­ci­pli­nary man­age­ment team, which includes both vet­er­ans of the tra­di­tion­al health­care indus­try and Google tech­nol­o­gists, will focus on pre­ven­tive care. Behav­ioral health coach­es will dri­ve care teams that will build social rela­tion­ships and deliv­er care at cen­tral­ly locat­ed “hubs,” via tele­health ser­vices or house calls, accord­ing to the web­site. City­block is also in the process of nego­ti­at­ing part­ner­ships to ensure insur­ance com­pa­nies cov­er its ser­vices.

...

He also points out that City­block has made a con­scious deci­sion to tar­get low-income Amer­i­cans, who he says have tra­di­tion­al­ly been short-changed by indus­try inno­va­tion efforts.

———-

“Google’s par­ent com­pa­ny spins off an inno­v­a­tive start­up health­care provider” by Matt Kuhrt; Fierce Health­care; 10/05/2017

“City­block aims to pro­vide Med­ic­aid and low­er-income Medicare ben­e­fi­cia­ries access to high-val­ue, read­i­ly avail­able per­son­al­ized health ser­vices. To do this, Iyah Romm, cofounder and CEO, writes in a blog post on Medi­um that the orga­ni­za­tion will apply lead­ing-edge care mod­els that ful­ly inte­grate pri­ma­ry care, behav­ioral health and social ser­vices. It expects to open its first clin­ic, which it calls a Neigh­bor­hood Health Hub, in New York City in 2018.”

It’s prob­a­bly worth recall­ing that per­son­al­ized ser­vices for the poor intend­ed to ‘help them help them­selves’ was the cen­ter­piece for House Speak­er Paul Ryan’s pro­pos­al to give every poor per­son a life coach who will issue “life plans” and “con­tracts” that poor peo­ple would be expect­ed to meet and face penal­ties if they fail to meet them. So when we’re talk­ing about set­ting up spe­cial per­son­al­ized “behav­ior health” mon­i­tor­ing sys­tems as part of health care ser­vices for the poor, don’t for­get that this per­son­al­ized mon­i­tor­ing sys­tem is going to be real­ly handy when politi­cians want to say, “if you want to stay on Med­ic­aid you have bet­ter make XYZ changes in your lifestyle. We are watch­ing you.” And since right-wingers gen­er­al expect the poor to be super-human (capa­ble of work­ing mul­ti­ple jobs, get­ting an edu­ca­tion, raise a fam­i­ly, and deal­ing with any unfore­seen per­son­al dis­as­ters in stride, all simul­ta­ne­ous­ly), it’s not like it’s we should be sur­prised to see the kinds of behav­ior health stan­dards that almost no one can meet, espe­cial­ly since work­ing mul­ti­ple jobs, get­ting an edu­ca­tion, raise a fam­i­ly, and deal­ing with any unfore­seen per­son­al dis­as­ters in stride simul­ta­ne­ous­ly is an incred­i­bly unhealthy lifestyle.

Also recall that Paul Ryan sug­gest­ed that his ‘life coach’ plan could apply to oth­er fed­er­al pro­grams for the poor, includ­ing food stamps. It’s not a stretch at all to imag­ine ‘life coach­es’ for Med­ic­aid recip­i­ents would appeal the right-wing. As long as it involves a ‘kick­ing the poor’ dynam­ic. And that’s part of the tragedy of the mod­ern age: sur­veil­lance tech­nol­o­gy and a focus on behav­ior health could be great as a help­ful vol­un­tary tool for peo­ple that want help get­ting health­i­er, but it’s hard to imag­ine it not becom­ing a coer­cive night­mare sce­nario in the US giv­en the incred­i­ble antipa­thy towards the poor that per­vades Amer­i­can soci­ety.

So as creepy as Google’s city is on its face regard­ing what it tells us about how the future is unfold­ing for peo­ple of all incomes and class­es, don’t for­get that we could be look­ing at the first test bed for cre­at­ing the kind of sur­veil­lance wel­fare state that’s per­fect for kick­ing peo­ple off of wel­fare. Just make unre­al­is­tic stan­dards that involve a lot of pater­nal­is­tic moral pos­tur­ing (which should play well with vot­ers), watch all the poor peo­ple with the sur­veil­lance tech­nol­o­gy, and wait for the wave of inevitable fail­ures who can be kicked off for not ‘try­ing’ or some­thing.

There’s some big news about Face­book’s mind-read­ing tech­nol­o­gy ambi­tions, although it’s not entire­ly clear if it’s good news, bad news, scary news or what: Regi­na Dugan, the for­mer head of DARPA who jumped to Google and then Face­book where we was work­ing on the mind-read­ing tech­nol­o­gy, just left Face­book. Why? Well, that’s where it’s unclear. Accord­ing to a Tweet Dugan made about her depar­ture:

There is a tidal shift going on in Sil­i­con Val­ley, and those of us in this indus­try have greater respon­si­bil­i­ties than ever before. The tim­ing feels right to step away and be pur­pose­ful about what’s next, thought­ful about new ways to con­tribute in times of dis­rup­tion.

So Dugan is leav­ing Face­book, to be more pur­pose­ful and respon­si­ble. And she was the one head­ing up the mind-read­ing tech­nol­o­gy project. Is that scary news? It’s unclear but it seems like that might be scary news:

Giz­mo­do

What Hap­pens to Facebook’s Mind Read­ing Project Now That Its Leader Is Gone?

Alex Cranz
10/17/2017 5:05pm

Regi­na Dugan, a tech exec with roots in the gov­ern­ment sec­tor as the for­mer direc­tor of DARPA, is leav­ing Face­book and her depar­ture calls into ques­tion the sta­tus of one of the cra­zi­est things Face­book has been work­ing on.

Fit­ting­ly, Dugan announced the depar­ture in a post on Face­book today.

[see Face­book post]

If you’re unfa­mil­iar with Dugan her­self you may be famil­iar with some of the skunkworks projects she over­saw while man­ag­ing Google’s secre­tive Advanced Tech­nol­o­gy and Projects (ATAP) group from 2012 to 2016. Those projects includ­ed Tan­go, a high­ly accu­rate aug­ment­ed real­i­ty device packed into a phone, and Ara, the now scut­tled mod­u­lar phone that could have made your mobile hard­ware upgrades a whole lot cheap­er.

In 2016 Dugan left Google for anoth­er huge com­pa­ny with lit­tle con­sumer gad­get expe­ri­ence: Face­book. At Face­book she ran Build­ing 8, anoth­er pri­vate­ly fund­ed research and devel­op­ment group like ATAP.

The projects Dugan and her col­leagues devel­oped at Build­ing 8 didn’t just include neat gad­gets for the near future; they could have also led to enor­mous leaps for­ward in tech­nol­o­gy as a whole. The most not­ed project was one announced at F8, Facebook’s annu­al devel­op­er con­fer­ence, in April. Called Silent Voice First, the project sought to allow com­put­ers to read your mind. Obvi­ous­ly that would make it eas­i­er to post to Face­book when your hands are busy, and it could be life alter­ing for peo­ple with severe phys­i­cal lim­i­ta­tions, but it would also, you know, be a com­put­er, run by Face­book, that READS YOUR MIND.

Nei­ther Dugan nor Face­book has made it clear why she’s depart­ing at this time; a rep­re­sen­ta­tive for Face­book told Giz­mo­do the com­pa­ny had noth­ing fur­ther to add (we’ve also reached out to Dugan). And Face­book has not detailed what will hap­pen to the projects she over­saw at Build­ing 8.

...

Beyond that, all we have is a pre­pared quote from Dugan that was pro­vid­ed to reporters, via Bloomberg’s Sarah Frier.

There is a tidal shift going on in Sil­i­con Val­ley, and those of us in this indus­try have greater respon­si­bil­i­ties than ever before. The tim­ing feels right to step away and be pur­pose­ful about what’s next, thought­ful about new ways to con­tribute in times of dis­rup­tion.

These aren’t exact­ly the words you want to hear from the woman over­see­ing the devel­op­ment of mind-read­ing tech­nol­o­gy for one of the largest pri­vate sur­veil­lance appa­ra­tus­es in the world.

But it is a good reminder for us all that the biggest leaps for­ward in tech­nol­o­gy, the next steps on our jour­ney towards a Matrix or Star Trek-like future, are not nec­es­sar­i­ly in the hands of altru­is­tic sci­en­tists with pub­lic fund­ing, but poten­tial­ly in the hands of enor­mous pri­vate cor­po­ra­tions who seem to pri­mar­i­ly per­ceive humans as com­modi­ties, and tech­nol­o­gy as inroads into our wal­lets and minds. In cas­es like that one would hope they’d be respon­si­ble.

———-

“What Hap­pens to Facebook’s Mind Read­ing Project Now That Its Leader Is Gone?” by Alex Cranz; Giz­mo­do; 10/17/2017

“Nei­ther Dugan nor Face­book has made it clear why she’s depart­ing at this time; a rep­re­sen­ta­tive for Face­book told Giz­mo­do the com­pa­ny had noth­ing fur­ther to add (we’ve also reached out to Dugan). And Face­book has not detailed what will hap­pen to the projects she over­saw at Build­ing 8.”

It’s a mys­tery. A mind-read­ing tech­nol­o­gy mys­tery. Oh good­ie. As the author of the above piece notes in response to Dugan’s tweet about being respon­si­ble and pur­pose­ful, these are exact­ly reas­sur­ing words in this con­text:

...
These aren’t exact­ly the words you want to hear from the woman over­see­ing the devel­op­ment of mind-read­ing tech­nol­o­gy for one of the largest pri­vate sur­veil­lance appa­ra­tus­es in the world.
...

That’s the con­text. The head of the mind-read­ing tech­nol­o­gy divi­sion for one of the largest pri­vate sur­veil­lance appa­ra­tus­es in the world just left the com­pa­ny for cryp­tic rea­sons involv­ing the need for the tech indus­try to be more respon­si­ble than ever and her choice to step away to be pur­pose­ful. It’s not par­tic­u­lar­ly reas­sur­ing news.

Here’s some new research worth keep­ing in mind regard­ing the mind-read­ing tech­nolo­gies being devel­oped by Face­book and Elon Musk: While read­ing your exact thoughts, the stat­ed goals of Face­book and Musk, is prob­a­bly going to require quite a bit more research, read­ing your emo­tions is some­thing researchers can already do. And this abil­i­ty to read emo­tion can, in turn, be poten­tial­ly used to read what you’re think­ing by look­ing at your emo­tion­al response to par­tic­u­lar con­cepts.

That’s what some researchers just demon­strat­ed, using fMRI brain imag­ing tech­nol­o­gy to gath­er data on brain activ­i­ty which was fed into soft­ware trained to iden­ti­fy dis­tinct pat­terns of brain activ­i­ty. The results are pret­ty astound­ing. In the study, researchers recruit­ed 34 indi­vid­u­als: 17 peo­ple who self-pro­fessed to hav­ing had sui­ci­dal thoughts before, and 17 oth­ers who had­n’t. Then they mea­sured the brain activ­i­ties of these 34 indi­vid­u­als in response to var­i­ous words, includ­ing the word “death.” It turns out “death” cre­at­ed a dis­tinct sig­na­ture of brain activ­i­ty dif­fer­en­ti­at­ing the sui­ci­dal indi­vid­u­als from the con­trol group, allow­ing the researchers to iden­ti­fy those with sui­ci­dal thoughts 91 per­cent of the time in this study:

The Dai­ly Beast

A Machine Might Just Read Your Mind and Pre­dict If You’re Sui­ci­dal
A psy­chol­o­gy pro­fes­sor says his soft­ware can fig­ure out if a per­son is sui­ci­dal. But does it real­ly work?

Tanya Basu
11.01.17 9:00 AM ET

A few years ago, Mar­cel Just was try­ing to fig­ure out how to have real-life appli­ca­tions for his research. Just, a pro­fes­sor of psy­chol­o­gy at Carnegie Mel­lon and direc­tor of the Cen­ter for Cog­ni­tive Brain Imag­ing, had spent the major­i­ty of the past decade teach­ing com­put­er pro­grams how to iden­ti­fy thoughts. He had found—with the help of an func­tion­al mag­net­ic res­o­nance imag­ing (fMRI) machine—that each emo­tion we feel had a spe­cif­ic sig­na­ture in the brain and lit up in unique­ly iden­ti­fi­able ways. Just had trained a piece of soft­ware to fol­low these pat­terns and rec­og­nize about 30 con­cepts and emo­tions.

“We asked whether we could iden­ti­fy what a per­son was think­ing from the machine learn­ing pat­terns,” Just explained. “The machine learn­ing data was fig­ured out with var­i­ous kinds of con­cepts; even­tu­al­ly it learned how to map between pat­terns and con­cepts.”

“From that research,” he added, “we real­ized it was pos­si­ble to tell what a per­son was think­ing.”

In oth­er words, Just had cre­at­ed arti­fi­cial intel­li­gence that could read your thoughts.

Around this time, Just spoke at the Uni­ver­si­ty of Pitts­burgh’s med­ical school. David Brent, a pro­fes­sor of psy­chol­o­gy spe­cial­iz­ing in chil­dren, approached him.

“Do you think this could be used to iden­ti­fy sui­ci­dal thoughts?” Brent asked.

It hit Just then: What if arti­fi­cial intel­li­gence could pre­dict what a sui­ci­dal per­son was think­ing? And maybe even pre­vent a sui­ci­dal per­son from com­mit­ting sui­cide?

Ear­li­er this week, Just, Brent, and a few oth­er col­leagues pub­lished a land­mark paper in the jour­nal Nature that finds that with an aston­ish­ing 91% accu­ra­cy, arti­fi­cial intel­li­gence is able to fig­ure out if a per­son is con­sid­er­ing sui­cide.

The exper­i­ment is remark­able for more than one rea­son. There’s of course the idea of using a machine trained to fig­ure out neur­al pat­terns to iden­ti­fy those who might con­sid­er sui­cide. It’s a sub­set of the pop­u­la­tion that is typ­i­cal­ly dif­fi­cult to pin­point and help before it’s too late, rely­ing not only on their telling oth­ers of their desire to kill them­selves, but also that per­son actu­al­ly act­ing on it and help­ing the sui­ci­dal per­son in trou­ble.

Just and Brent recruit­ed 34 indi­vid­u­als from local clin­ics: 17 who’d self-pro­fessed to hav­ing had sui­ci­dal thoughts before, and 17 oth­ers who had­n’t. The research team put the 34 indi­vid­u­als through an fMRI machine and had them think about words (with the help of the Adult Sui­ci­dal Ideation Ques­tion­naire, which mea­sures “sui­cide ideation”) that rep­re­sent­ed dif­fer­ent “stim­u­lus” con­cepts, rang­ing from pos­i­tive ones (praise, bliss, care­free, and kind­ness), neg­a­tive ones (ter­ri­ble, cru­el­ty, evil), and sui­cide (fatal, funer­al, death).

The last one—death—was the most damn­ing of the brain sig­na­tures in Just’s study. Those who were sui­ci­dal showed a spot of angry crim­son at the front of the brain. Con­trol patients, mean­while, just had specks of red amidst a sea of blue in the pic­tures. “These peo­ple who are sui­ci­dal had more sad­ness in their rep­re­sen­ta­tion of death, and more shame as well,” he said.
[see neur­al imag­ine rep­re­sen­ta­tions]

So Just and Brent set to work teach­ing a machine the con­cepts that were most asso­ci­at­ed with sui­cide, and those that weren’t. “If you trained the machine on 10 peo­ple in their anger sig­na­ture, and put the 11th per­son on the scan­ner, it should be able to tell if the 11th per­son is angry or not,” Just said of how the machine was put to the test. The machine then fig­ured out if the per­son was sui­ci­dal or not.

The results are strong, even if the sam­ple size is rel­a­tive­ly small: After going through all 34 peo­ple, Just and his research team were able to say with a 91% suc­cess rate which of the indi­vid­u­als had dis­played sui­ci­dal thoughts.

That’s, in short, amaz­ing. But it’s not per­fect. What about the oth­er 9%? “It’s a good ques­tion,” he said of the gap. “There seems to be an emo­tion­al dif­fer­ence [we don’t under­stand]” that the group hopes to test in future iter­a­tions of the study.

Anoth­er prob­lem with the study as it stands? The fact that it uses the fMRI machine in the first place. “Nobody used machine learn­ing in the ear­ly days,” Just said. “This [arti­fi­cial intel­li­gence] uses mul­ti­ple vol­ume elements—‘voxels’—to fig­ure out neur­al rep­re­sen­ta­tion.” If that sounds expen­sive, it is. And expense makes any poten­tial ther­a­py there­fore more dif­fi­cult to access, a crit­i­cism of brain scan­ning stud­ies cov­ered by Ed Yong at The Atlantic: “When sci­en­tists use med­ical scan­ners to repeat­ed­ly peer at the shapes and activ­i­ties of the human brain, those brains tend to belong to wealthy and well-edu­cat­ed peo­ple. And unless researchers take steps to cor­rect for that bias, what we get is an under­stand­ing of the brain that’s incom­plete, skewed, and ... well ... a lit­tle weird.”

...

The more sub­tle nuance of the study that deserves note is the very real pos­si­bil­i­ty that arti­fi­cial intel­li­gence can do some­thing that strong­ly resem­bles read­ing your mind. We like to con­ceive of thoughts as amor­phous con­cepts, as unique to our own head­space and expe­ri­ence. What might tick­le one per­son­’s fan­cy might not nec­es­sar­i­ly do the same for anoth­er; what brings one indi­vid­ual shame won’t both­er some­one else. But those core feel­ings of hap­pi­ness, shame, sad­ness, and oth­ers seem to look almost iden­ti­cal from per­son to per­son.

Does this mean that we can poten­tial­ly erad­i­cate sui­cide, though? Just is hes­i­tant to make that assump­tion, though he thinks this is a huge step towards under­stand­ing what he terms “thought dis­or­ders.” “We can look at the neur­al sig­na­ture and see how it’s changed,” he said, “see what this per­son is think­ing, whether it’s unusu­al.” Just thinks that most real­is­ti­cal­ly, this is going to be a huge first step towards devel­op­ing a unique ther­a­py for sui­ci­dal indi­vid­u­als: If we know the spe­cif­ic thought process­es that are symp­to­matic of sui­cide, we can know how to poten­tial­ly spot sui­ci­dal indi­vid­u­als and help them.

“This isn’t a wild pie in the sky idea,” Just said. “We can use machine learn­ing to fig­ure out the phys­i­cal­i­ty of thought. We can help peo­ple.”

———-

“A Machine Might Just Read Your Mind and Pre­dict If You’re Sui­ci­dal” by Tanya Basu; The Dai­ly Beast; 11/01/2017

““This isn’t a wild pie in the sky idea,” Just said. “We can use machine learn­ing to fig­ure out the phys­i­cal­i­ty of thought. We can help peo­ple.””

Yes indeed, this kind of tech­nol­o­gy could be wild­ly help­ful in the field of brain sci­ence and study­ing men­tal ill­ness. The abil­i­ty to break down the men­tal activ­i­ty in response to con­cepts and see which parts of the brains are light­ing up and what types of emo­tions they’re asso­ci­at­ed with would be an invalu­able research tool. So let’s hope researchers are able to come up with all sorts of use­ful dis­cov­er­ies about all sorts of men­tal con­di­tions using this kind of tech­nol­o­gy. In respon­si­ble hands this could lead to incred­i­ble break­throughs in med­i­cine and men­tal health and real­ly could improve lives.

But, of course, with tech­nol­o­gy being the dou­ble-edged sword that it is, we can’t ignore the real­i­ty that the same tech­nol­o­gy that would be won­der­ful for respon­si­ble researchers work­ing with vol­un­teers in a lab set­ting would be absolute­ly ter­ri­fy­ing if it was incor­po­rat­ed into, say, Face­book’s planned mind-read­ing con­sumer tech­nol­o­gy. After all, if Face­book’s planned mind-read­ing tech can read peo­ple’s thoughts it seems like it should be also be capa­ble of read­ing some­thing much sim­pler to detect like emo­tion­al response too.

Or at least typ­i­cal emo­tion­al respons­es. As the study also indi­cat­ed, there’s going to a sub­set of peo­ple whose brains don’t emo­tion­al­ly respond in the “nor­mal” man­ner, where the def­i­n­i­tion “nor­mal­cy” is prob­a­bly filled with all sorts of unknown bias­es:

...
The results are strong, even if the sam­ple size is rel­a­tive­ly small: After going through all 34 peo­ple, Just and his research team were able to say with a 91% suc­cess rate which of the indi­vid­u­als had dis­played sui­ci­dal thoughts.

That’s, in short, amaz­ing. But it’s not per­fect. What about the oth­er 9%? “It’s a good ques­tion,” he said of the gap. “There seems to be an emo­tion­al dif­fer­ence [we don’t under­stand]” that the group hopes to test in future iter­a­tions of the study.

Anoth­er prob­lem with the study as it stands? The fact that it uses the fMRI machine in the first place. “Nobody used machine learn­ing in the ear­ly days,” Just said. “This [arti­fi­cial intel­li­gence] uses mul­ti­ple vol­ume elements—‘voxels’—to fig­ure out neur­al rep­re­sen­ta­tion.” If that sounds expen­sive, it is. And expense makes any poten­tial ther­a­py there­fore more dif­fi­cult to access, a crit­i­cism of brain scan­ning stud­ies cov­ered by Ed Yong at The Atlantic: “When sci­en­tists use med­ical scan­ners to repeat­ed­ly peer at the shapes and activ­i­ties of the human brain, those brains tend to belong to wealthy and well-edu­cat­ed peo­ple. And unless researchers take steps to cor­rect for that bias, what we get is an under­stand­ing of the brain that’s incom­plete, skewed, and ... well ... a lit­tle weird.”
...

“What about the oth­er 9%? “It’s a good ques­tion,” he said of the gap. “There seems to be an emo­tion­al dif­fer­ence [we don’t under­stand]” that the group hopes to test in future iter­a­tions of the study.”

So once this tech­nol­o­gy because cheap enough for wide­spread use (which is one of the goals of Face­book and Musk) we could eas­i­ly find that “brain types” become a new cat­e­go­ry for assess­ing peo­ple. And pre­dict­ing behav­ior. And any­thing else peo­ple (and not just expert researchers) can think up to use this kind of data for.

And don’t for­get, if Face­book real­ly can devel­op cheap thought-read­ing tech­nol­o­gy designed to inter­face your brain with a com­put­er, that could eas­i­ly become the kind of thing employ­ees are just expect­ed to use due to the poten­tial pro­duc­tiv­i­ty enhance­ments. So imag­ine tech­nol­o­gy that’s not only read­ing the words you’re think­ing but also read­ing the emo­tion response you have to those words. And imag­ine basi­cal­ly being basi­cal­ly forced to use this tech­nol­o­gy in the work­place of the future because it’s deemed to be pro­duc­tiv­i­ty enhanc­ing or some­thing. That could actu­al­ly hap­pen.

It also rais­es the ques­tion of what Face­book would do if it detect­ed some­one was show­ing the sui­ci­dal brain sig­na­ture. Do they alert some­one? Will think­ing sad thoughts while using the mind-read­ing tech­nol­o­gy result in a vis­it from a men­tal health pro­fes­sion­al? What about real­ly angry or vio­lent thoughts? It’s the kind of area that’s going to raise fas­ci­nat­ing ques­tions about the respon­si­ble use of this data. Fas­ci­nat­ing and often ter­ri­fy­ing ques­tions.

It’s all pret­ty depress­ing, right? Well, if the emerg­ing mind-read­ing econ­o­my gets over­whelm­ing­ly depress­ing, at least it sounds like the mind-read­ing tech­nol­o­gy caus­ing your depres­sion will be able to detect that it’s caus­ing this. Yay?

Remem­ber those reports about Big Data being used in the work­place to allow employ­ers to pre­dict which employ­ees are like­ly to get sick (so they get get rid of them before the ill­ness­es get expen­sive)? Well, as the fol­low­ing arti­cle makes clear, employ­ers are going to be pre­dict­ing a lot more than just who is get­ting sick. They’re going to be try­ing to pre­dict every­thing they can pre­dict along with things they can’t accu­rate­ly pre­dict but decide to try to pre­dict any­way:

The Guardian

Big Broth­er isn’t just watch­ing: work­place sur­veil­lance can track your every move

Employ­ers are using a range of tech­nolo­gies to mon­i­tor their staff’s web-brows­ing pat­terns, key­strokes, social media posts and even pri­vate mes­sag­ing apps

Olivia Solon in San Fran­cis­co
Mon­day 6 Novem­ber 2017 03.00 EST

How can an employ­er make sure its remote work­ers aren’t slack­ing off? In the case of tal­ent man­age­ment com­pa­ny Crossover, the answer is to take pho­tos of them every 10 min­utes through their web­cam.

The pic­tures are tak­en by Crossover’s pro­duc­tiv­i­ty tool, WorkS­mart, and com­bine with screen­shots of their work­sta­tions along with oth­er data – includ­ing app use and key­strokes – to come up with a “focus score” and an “inten­si­ty score” that can be used to assess the val­ue of free­lancers.

Today’s work­place sur­veil­lance soft­ware is a dig­i­tal panop­ti­con that began with email and phone mon­i­tor­ing but now includes keep­ing track of web-brows­ing pat­terns, text mes­sages, screen­shots, key­strokes, social media posts, pri­vate mes­sag­ing apps like What­sApp and even face-to-face inter­ac­tions with co-work­ers.

“If you are a par­ent and you have a teenage son or daugh­ter com­ing home late and not doing their home­work you might won­der what they are doing. It’s the same as employ­ees,” said Brad Miller, CEO of Aware­ness Tech­nolo­gies, which sells a pack­age of employ­ee mon­i­tor­ing tools under the brand Inter­guard.

Crossover’s San­jeev Pat­ni insists that work­ers get over the ini­tial self-con­scious­ness after a few days and accept the need for such mon­i­tor­ing as they do CCTV in shop­ping malls.

“The response is ‘OK, I’m being mon­i­tored, but if the com­pa­ny is pay­ing for my time how does it mat­ter if it’s record­ing what I’m doing? It’s only for my bet­ter­ment,’” he said.

Such “bet­ter­ment” appar­ent­ly isn’t nec­es­sary for man­agers: they can pick and choose when to turn their cam­eras on.

The major­i­ty of sur­veil­lance tech providers focus their atten­tion on the finan­cial sec­tor, where com­pa­nies are legal­ly required to track staff com­mu­ni­ca­tions to pre­vent insid­er trad­ing. But they are increas­ing­ly sell­ing their tech to a broad­er range of com­pa­nies to mon­i­tor staff pro­duc­tiv­i­ty, data leaks and Human Resources vio­la­tions, like sex­u­al harass­ment and inap­pro­pri­ate behav­ior.

Wire­tap spe­cial­izes in mon­i­tor­ing work­place chat forums such as Face­book Work­place, Slack and Yam­mer to iden­ti­fy, among oth­er issues, “inten­tion­al and unin­ten­tion­al harass­ment, threats, intim­i­da­tion”.

Last year an employ­ee at an IT ser­vices com­pa­ny sent a pri­vate chat mes­sage to a friend at work wor­ried that he had just shared his sex­u­al iden­ti­ty with his man­ag­er in a meet­ing and fear­ing he’d face career reprisal. Wire­tap detect­ed the employee’s con­cern and alert­ed a senior com­pa­ny exec who was then able to inter­vene, talk to the man­ag­er and defuse the sit­u­a­tion.

“Hav­ing the vis­i­bil­i­ty allows you to step in pro­duc­tive­ly,” said Greg Moran, COO of Wire­tap. “Even if it’s not a seri­ous offense you can see the ear­ly indi­ca­tions of some­one head­ing down a path.”

To mon­i­tor pro­duc­tiv­i­ty, soft­ware can mea­sure prox­ies such as the num­ber of emails being sent, web­sites vis­it­ed, doc­u­ments and apps opened and key­strokes. Over time it can build a pic­ture of typ­i­cal user behav­iour and then alert when some­one devi­ates.

“If it’s nor­mal for you to send out 10 emails, type 5,000 key­strokes and be active on a com­put­er for three hours a day, if all of a sud­den you are only active for one hour or typ­ing 1,000 key­strokes, there seems to be a dip in pro­duc­tiv­i­ty,” said Miller.

“Or if you usu­al­ly touch 10 doc­u­ments a day and print two and sud­den­ly you are touch­ing 500 and print­ing 200 that may mean you’re steal­ing doc­u­ments in prepa­ra­tion of leav­ing the com­pa­ny.”

Oth­er com­pa­nies, such as Tera­mind, seek to mea­sure dis­trac­tion by look­ing at how much a per­son is switch­ing between appli­ca­tions.

“If a para­le­gal is writ­ing a doc­u­ment and every few sec­onds is switch­ing to Hipchat, Out­look and Word then there’s an issue that can be resolved by address­ing it with the employ­ee,” said Teramind’s CEO, Isaac Kohen.

A com­mon but flawed tech­nique is key­word detec­tion, draw­ing from a list of pre­de­fined terms includ­ing swear words and slang asso­ci­at­ed with shady behav­ior. This approach tends to kick up a lot of false pos­i­tives and is easy to cir­cum­vent by any­one intent on beat­ing the sys­tem.

That wasn’t the case when an All State Insur­ance fran­chise did a live demon­stra­tion of Interguard’s soft­ware to oth­er deal­ers. The tech­nol­o­gy start­ed scan­ning the net­work and almost imme­di­ate­ly found an email with the words “client list” and “résumé”. The demon­stra­tor opened the email in front of a room full of peers to dis­cov­er his best employ­ee was plot­ting to move to anoth­er com­pa­ny.

Com­pa­nies like Dig­i­tal Rea­son­ing search for more sub­tle indi­ca­tors of pos­si­ble wrong­do­ing, such as con­text switch­ing. This is where one per­son sug­gests mov­ing the dis­cus­sion to encrypt­ed apps like What­sApp or Sig­nal or even tak­ing the con­ver­sa­tion offline, indi­cat­ing that the sub­ject mat­ter is too risky for the cor­po­rate net­work.

“Now peo­ple know a lot of these sys­tems mon­i­tor­ing com­mu­ni­ca­tions are becom­ing more sophis­ti­cat­ed, they are say­ing, ‘Hey let’s move over to the oth­er app’ or ‘Let’s meet down­stairs for cof­fee’. These are small clues that have sur­faced in pros­e­cu­tions,” said Dig­i­tal Reasoning’s chief prod­uct offi­cer, Marten den Har­ing.

Even What­sApp isn’t safe from Qumram’s mon­i­tor­ing soft­ware, which is placed on employ­ees’ devices – with their con­sent – to cap­ture every­thing they do, includ­ing the mes­sages they send to cus­tomers using What­sApp.

“It tru­ly is Big Broth­er watch­ing you,” said Qumram’s Patrick Bar­nett.

The spy­ing tech­nique that most com­pa­nies avoid, despite Crossover’s enthu­si­asm, is access­ing employ­ees’ web­cams. (Although you should prob­a­bly tape over yours like Mark Zucker­berg does if you are wor­ried about it.)

...

Amer­i­can com­pa­nies gen­er­al­ly aren’t required by law to dis­close how they mon­i­tor employ­ees using com­pa­ny-issued devices, although they tend to include a catch-all clause in employ­ment con­tracts declar­ing such mon­i­tor­ing.

“You can look at every­thing [in the US],” said Al Gidari, direc­tor of pri­va­cy at the Stan­ford Cen­tre for Inter­net and Soci­ety, adding that new sur­veil­lance soft­ware is so intru­sive because it’s “more per­va­sive, con­tin­u­ous and search­able”.

Even if you’re not an employ­ee you may still be sub­ject to sur­veil­lance, thanks to tech­nol­o­gy used to screen poten­tial job can­di­dates. San­ta Mon­i­ca-based Fama pro­vides social media screen­ing to employ­ers to check for any prob­lem­at­ic con­tent.

CEO Ben Mon­es said Fama was only inter­est­ed in con­tent that’s rel­e­vant to busi­ness­es, which includes “ref­er­ences to big­otry, misog­y­ny and vio­lence” as well as drug and alco­hol ref­er­ences. The soft­ware, he said, can “tell the dif­fer­ence between smok­ing weed in the back­yard and weed­ing the back­yard”.

When pushed on how the com­pa­ny dif­fer­en­ti­ates big­otry ver­sus, for exam­ple, a black per­son using the N‑word, the response is a lit­tle fuzzy.

“It’s a super-nuanced top­ic,” Mon­es said, adding that some of the thin­ly veiled signs of racism, like ref­er­ences to Con­fed­er­ate flags or stat­ues, wouldn’t come up.

“Employ­ers aren’t look­ing at ref­er­ences like that to make a hir­ing deci­sion,” he said.

And con­nect­ing the dots between a person’s work life and per­son­al life can lead to uncom­fort­able ter­ri­to­ry. One insid­er at a large con­sult­ing firm told the Guardian the com­pa­ny was look­ing into whether it could pre­vent fraud among bankers by look­ing at their Face­book pages. One sce­nario would be a trad­er who had just changed their rela­tion­ship sta­tus from mar­ried to divorce, the expense of which “could put that per­son under pres­sure to com­mit fraud or steal”.

The insid­er had reser­va­tions about the effec­tive­ness of such a sys­tem.

“If I were divorced, would I be more like­ly to steal? I don’t think so. It makes assump­tions,” he said, adding, “The more data and tech­nol­o­gy you have with­out an under­ly­ing the­o­ry of how people’s minds work then the eas­i­er it is to jump to con­clu­sions and put peo­ple in the crosshairs who don’t deserve to be.”

———-

“Big Broth­er isn’t just watch­ing: work­place sur­veil­lance can track your every move” by Olivia Solon; The Guardian; 11/06/2017

“Today’s work­place sur­veil­lance soft­ware is a dig­i­tal panop­ti­con that began with email and phone mon­i­tor­ing but now includes keep­ing track of web-brows­ing pat­terns, text mes­sages, screen­shots, key­strokes, social media posts, pri­vate mes­sag­ing apps like What­sApp and even face-to-face inter­ac­tions with co-work­ers.”

And what are employ­ers doing with that dig­i­tal panop­ti­con? For starters, sur­veilling employ­ees’ com­put­er usage, as would unfor­tu­nate­ly be expect­ed. But what might not be expect­ed is that this panop­ti­can soft­ware can be set up to deter­mine the expect­ed behav­ior of a par­tic­u­lar employ­ee and then com­pare that behav­ior pro­file to the observed behav­ior. And if there’s a big change, the man­agers get a warn­ing. The panop­ti­con isn’t just sur­veilling you. It’s get­ting to know you:

...
To mon­i­tor pro­duc­tiv­i­ty, soft­ware can mea­sure prox­ies such as the num­ber of emails being sent, web­sites vis­it­ed, doc­u­ments and apps opened and key­strokes. Over time it can build a pic­ture of typ­i­cal user behav­iour and then alert when some­one devi­ates.

“If it’s nor­mal for you to send out 10 emails, type 5,000 key­strokes and be active on a com­put­er for three hours a day, if all of a sud­den you are only active for one hour or typ­ing 1,000 key­strokes, there seems to be a dip in pro­duc­tiv­i­ty,” said Miller.

“Or if you usu­al­ly touch 10 doc­u­ments a day and print two and sud­den­ly you are touch­ing 500 and print­ing 200 that may mean you’re steal­ing doc­u­ments in prepa­ra­tion of leav­ing the com­pa­ny.”

Oth­er com­pa­nies, such as Tera­mind, seek to mea­sure dis­trac­tion by look­ing at how much a per­son is switch­ing between appli­ca­tions.

“If a para­le­gal is writ­ing a doc­u­ment and every few sec­onds is switch­ing to Hipchat, Out­look and Word then there’s an issue that can be resolved by address­ing it with the employ­ee,” said Teramind’s CEO, Isaac Kohen.
...

“If a para­le­gal is writ­ing a doc­u­ment and every few sec­onds is switch­ing to Hipchat, Out­look and Word then there’s an issue that can be resolved by address­ing it with the employ­ee”

If you’re the type of per­son whose brain works bet­ter jump­ing back and forth between tasks you’re going to get flagged as not being focused. Peo­ple with ADHD are going to love the future.

Peo­ple who like to talk in per­son over cof­fee are also going to love the future:

...
Com­pa­nies like Dig­i­tal Rea­son­ing search for more sub­tle indi­ca­tors of pos­si­ble wrong­do­ing, such as con­text switch­ing. This is where one per­son sug­gests mov­ing the dis­cus­sion to encrypt­ed apps like What­sApp or Sig­nal or even tak­ing the con­ver­sa­tion offline, indi­cat­ing that the sub­ject mat­ter is too risky for the cor­po­rate net­work.

“Now peo­ple know a lot of these sys­tems mon­i­tor­ing com­mu­ni­ca­tions are becom­ing more sophis­ti­cat­ed, they are say­ing, ‘Hey let’s move over to the oth­er app’ or ‘Let’s meet down­stairs for cof­fee’. These are small clues that have sur­faced in pros­e­cu­tions,” said Dig­i­tal Reasoning’s chief prod­uct offi­cer, Marten den Har­ing.
...

So the fact that employ­ees know they’re being mon­i­tored is get­ting incor­po­rat­ed into more sophis­ti­cat­ed algo­rithms that oper­ate under the assump­tion that employ­ees know they’re being mon­i­tored and will try to hide their mis­be­hav­ior from the panop­ti­con. Of course, employ­ees are inevitably going to learn about all these sub­tle clues that the panop­ti­con is watch­ing for so this will no doubt lead to a need for algo­rithms that incor­po­rate even more sub­tle clues. An ever more sophis­ti­cat­ed cat to catch an ever more sophis­ti­cat­ed mouse. And so on, for­ev­er.

What could pos­si­bly go wrong? Oh yeah, a lot, espe­cial­ly if the assump­tions that go into all these algo­rithms are wrong:

...
And con­nect­ing the dots between a person’s work life and per­son­al life can lead to uncom­fort­able ter­ri­to­ry. One insid­er at a large con­sult­ing firm told the Guardian the com­pa­ny was look­ing into whether it could pre­vent fraud among bankers by look­ing at their Face­book pages. One sce­nario would be a trad­er who had just changed their rela­tion­ship sta­tus from mar­ried to divorce, the expense of which “could put that per­son under pres­sure to com­mit fraud or steal”.

The insid­er had reser­va­tions about the effec­tive­ness of such a sys­tem.

“If I were divorced, would I be more like­ly to steal? I don’t think so. It makes assump­tions,” he said, adding, “The more data and tech­nol­o­gy you have with­out an under­ly­ing the­o­ry of how people’s minds work then the eas­i­er it is to jump to con­clu­sions and put peo­ple in the crosshairs who don’t deserve to be.”

“The more data and tech­nol­o­gy you have with­out an under­ly­ing the­o­ry of how people’s minds work then the eas­i­er it is to jump to con­clu­sions and put peo­ple in the crosshairs who don’t deserve to be.”

And keep in mind that when your employ­er panop­ti­con pre­dicts you’re going to do some­thing bad in the future they prob­a­bly aren’t going to tell you that when they let you go. They’re just make up some ran­dom excuse. Much like how employ­ers who pre­dict you’re going to get sick with an expen­sive ill­ness prob­a­bly aren’t going to tell you this. They’re just going to find a rea­sons to let you go. So we can add “mis­ap­plied algo­rith­mic assump­tions” to the list of poten­tial mys­tery rea­sons for when you sud­den­ly get let go from your job with min­i­mal expla­na­tion in the panop­ti­con office of the future: maybe your employ­er pre­dicts you’re about to get real­ly ill. Or maybe some oth­er com­plete­ly ran­dom thing set off the bad behav­ior pre­dic­tive algo­rithm. There’s a range of mys­tery rea­sons so at least you should­n’t nec­es­sar­i­ly assume you’re about to get hor­ri­bly ill when you’re fired. Yay.

It told you so:

Lis­ten to this pro­gram, and then read this:

https://www.yahoo.com/news/kill-foster-parents-amazons-alexa-talks-murder-sex-120601149–finance.html

Have Fun!

Dave Emory

I think it is impor­tant that you are report­ing this kind of infor­ma­tion. I can tell you that in my career the most depress­ing and uneth­i­cal work that I ever moved in the prox­im­i­ty of was at Intel. I can tell you in 2013 that they had play­ing in the lob­by just before you enter their cafe­te­ria an adver­tis­ing video that was pro­mot­ing a great new devel­op­ment of theirs called ‘Smart Response’. This new inno­va­tion would allow your com­put­er to act as a good but­ler and pre­dict your deci­sions and serve as what I could only call your ‘con­fi­dant.’

>Imag­ine, your com­put­er as your ‘best bro’, nobody knows you bet­ter. Of course, you can Trust him Right? He’d nev­er Fink on You?

From work­ing in User Expe­ri­ence it was clear that there was effort in get­ting the machines to col­lect data about your face from your laptop/device cam­era as well as your tone of voice and then use that to inter­pret your reac­tions to what­ev­er you may be look­ing at and then alter the ad con­tent accord­ing­ly that the pages you vis­it dis­play. Sup­pos­ed­ly they could inter­pret your gen­er­al state of mind with a high degree of accu­ra­cy just by focus­ing on the tri­an­gu­lar area between your eyes and your mouth.

>In order for ‘Smart Response’ to work your com­put­er might need to col­lect this data, build a pro­file on you. But that’s OK, it’s your Bud­dy Riight?

From what I could gath­er, this seemed to be an out­growth of a project involv­ing physi­cist Stephen Hawkins. They want­ed to be able to build soft­ware to inter­pret him clear­ly. Once they did they may have begun apply­ing it gen­er­al­ly.. What real­ly con­cerned me about it is the prospect of reverse pro­gram­ming. Once they build these pro­files how would they use them? Would they try to pro­vide con­tent that they could guess an indi­vid­ual would respond to in a cer­tain way?
Would they have our com­put­ers try pro­gram­ming us?

https://amp.cnn.com/cnn/2019/08/01/tech/robot-racism-scn-trnd/index.html

Robot racism? Yes, says a study show­ing humans’ bias­es extend to robots
By Car­o­line Klein and David Allan, CNN
Updat­ed 8:37 AM EDT, Thu August 01, 2019

How­ev­er, as machines are get­ting clos­er to acquir­ing human-like lan­guage abil­i­ties, they are also absorb­ing the deeply ingrained bias­es con­cealed with­in the pat­terns of lan­guage use, the lat­est research reveals. Joan­na Bryson, a com­put­er sci­en­tist at the Uni­ver­si­ty of Bath and a co-author, said: ‘A lot of peo­ple are say­ing this is show­ing that AI is prej­u­diced. No. This is show­ing we’re prej­u­diced and that AI is learn­ing it.’ . . .”

There was a fas­ci­nat­ing study recent­ly pub­lished by the US Army about the future impact of cyborg tech­nol­o­gy on mil­i­tary affairs by the year 2050. But the report was­n’t just about the impact cyborg tech­nol­o­gy might have on the mil­i­tary. It includ­ed spec­u­la­tion about the impact the incor­po­ra­tion of cyborg tech­nol­o­gy in the mil­i­tary would have on the rest of soci­ety. Per­haps the most impor­tant con­clu­sion of the study was that some sort of incor­po­ra­tion of cyborg tech­nol­o­gy into mil­i­tary affairs was going to be tech­ni­cal­ly fea­si­ble by 2050 or ear­li­er and that when this becomes part of the mil­i­tary it’s inevitably going to be felt by the rest of soci­ety because the cyborg sol­diers of the future will inevitably leave ser­vice and join civ­il soci­ety. And at that point when retired cyborg sol­diers enter civ­il soci­ety all of the var­i­ous ques­tions that soci­ety needs to ask about how to bal­ance things out when human cyborg aug­men­ta­tion becomes a tech­ni­cal­ly viable are going to have to be asked and answered. So the ques­tion of whether or not soci­ety should allow cyborg aug­men­ta­tion is inter­twined with the ques­tion of whether or not nations are going to end up cre­at­ing cyborg sol­diers for the mil­i­tary. And giv­en the seem­ing­ly end­less glob­al mil­i­tary tech­nol­o­gy race for suprema­cy, it seems like a giv­en that cyborg sol­diers are com­ing as soon as tech­no­log­i­cal­ly fea­si­ble and then enter­ing the job mar­ket a few years lat­er after they retire from being a cyborg sol­dier. In oth­er words, unless human­i­ty fig­ures out how to demil­i­ta­rize and end war over the next 30 years, get ready for cyborgs. And pos­si­bly soon­er.

Anoth­er omi­nous aspect of the report is the empha­sis it placed on direct human-to-com­put­er com­mu­ni­ca­tions as being the cyborg tech­nol­o­gy that could most rev­o­lu­tion­ize com­bat. This is, of course, par­tic­u­lar­ly omi­nous because that brain-to-com­put­er inter­face tech­nol­o­gy is anoth­er area where there appears to be a tech­nol­o­gy race already under­way. For instance, recall how the head of Face­book’s project work­ing on mind-read­ing tech­nol­o­gy — the for­mer head of DARPA, Regi­na Dugan — resigned from the project and issued a vague state­ment about the need for the indus­try to be more respon­si­ble than ever before. And Elon Musk’s Tel­sa has been work­ing on sim­i­lar tech­nol­o­gy that involves actu­al­ly sur­gi­cal­ly implant­i­ng chips in your brain. Also recall how part of Elon Musk’s vision for how the appli­ca­tion of this com­put­er-to-brain com­mu­ni­ca­tion tech­nol­o­gy is to have humans direct­ly watch­ing over arti­fi­cial intel­li­gences to make sure the AIs to get out of con­trol, i.e. the ‘sum­mon­ing the demon’ metaphor. So the tech­nol­o­gy that the US Army expect to most rev­o­lu­tion com­bat is a tech­nol­o­gy that Face­book and Tes­la are already years into devel­op­ing. It’s a reminder that, while the sce­nario where cyborg tech­nol­o­gy first gets applied in the mil­i­tary and then spreads from there to civ­il soci­ety is a plau­si­ble sce­nario, it’s also very pos­si­ble we’ll see the cyborg tech­nol­o­gy like human-to-com­put­er inter­faces direct­ly sold to civ­il soci­ety as soon as pos­si­ble with­out first going through the mil­i­tary because that’s what the tech­nol­o­gy giants are active­ly plan­ning on doing right now. That lat­ter sce­nario is actu­al­ly in the US Army report, which pre­dict­ed that these cyborg capa­bil­i­ties will prob­a­bly “be dri­ven by civil­ian demand” and “a robust bio-econ­o­my that is at its ear­li­est stages of devel­op­ment in today’s glob­al mar­ket”:

Army Times

Cyborg war­riors could be here by 2050, DoD study group says

By: Kyle Rempfer
Novem­ber 27, 2019

Ear, eye, brain and mus­cu­lar enhance­ment is “tech­ni­cal­ly fea­si­ble by 2050 or ear­li­er,” accord­ing to a study released this month by the U.S. Army’s Com­bat Capa­bil­i­ties Devel­op­ment Com­mand.

The demand for cyborg-style capa­bil­i­ties will be dri­ven in part by the civil­ian health­care mar­ket, which will accli­mate peo­ple to an indus­try fraught with eth­i­cal, legal and social chal­lenges, accord­ing to Defense Depart­ment researchers.

Imple­ment­ing the tech­nol­o­gy across the mil­i­tary, how­ev­er, will like­ly run up against the dystopi­an nar­ra­tives found in sci­ence fic­tion, among oth­er issues, the researchers added.

The report — enti­tled “Cyborg Sol­dier 2050: Human/Machine Fusion and the Impli­ca­tions for the Future of the DOD” — is the result of a year-long assess­ment.

It was writ­ten by a study group from the DoD Biotech­nolo­gies for Health and Human Per­for­mance Coun­cil, which is tasked to look at the rip­ple effects of mil­i­tary biotech­nol­o­gy.

The team iden­ti­fied four capa­bil­i­ties as tech­ni­cal­ly fea­si­ble by 2050:

* ocu­lar enhance­ments to imag­ing, sight and sit­u­a­tion­al aware­ness;

* restora­tion and pro­grammed mus­cu­lar con­trol through an opto­ge­net­ic body­suit sen­sor web;

* audi­to­ry enhance­ment for com­mu­ni­ca­tion and pro­tec­tion; and

* direct neur­al enhance­ment of the human brain for two-way data trans­fer.

The study group sug­gest­ed that direct neur­al enhance­ments in par­tic­u­lar could rev­o­lu­tion­ize com­bat.

“This tech­nol­o­gy is pre­dict­ed to facil­i­tate read/write capa­bil­i­ty between humans and machines and between humans through brain-to-brain inter­ac­tions,” an exec­u­tive sum­ma­ry reads. “These inter­ac­tions would allow warfight­ers direct com­mu­ni­ca­tion with unmanned and autonomous sys­tems, as well as with oth­er humans, to opti­mize com­mand and con­trol sys­tems and oper­a­tions.”

Cyborg tech­nolo­gies are like­ly to be used among civ­il soci­ety as well over the next 30 years, the researchers not­ed.

Devel­op­ment of these capa­bil­i­ties will prob­a­bly “be dri­ven by civil­ian demand” and “a robust bio-econ­o­my that is at its ear­li­est stages of devel­op­ment in today’s glob­al mar­ket,” the group wrote.

But it’s after the year 2050 that the impli­ca­tions of cyborg capa­bil­i­ties become con­cern­ing.

“Intro­duc­tion of aug­ment­ed human beings into the gen­er­al pop­u­la­tion, DoD active-duty per­son­nel, and near-peer com­peti­tors will accel­er­ate in the years fol­low­ing 2050 and will lead to imbal­ances, inequal­i­ties, and inequities in estab­lished legal, secu­ri­ty, and eth­i­cal frame­works,” the sum­ma­ry reads.

The study group pro­posed sev­en rec­om­men­da­tions, list­ed in no par­tic­u­lar order, for Pen­ta­gon lead­ers to con­sid­er:

* The mil­i­tary should take a sec­ond look at the glob­al and soci­etal per­cep­tion of human-machine aug­men­ta­tion. Amer­i­cans typ­i­cal­ly imag­ine Chi­na or Rus­sia devel­op­ing run­away tech­nolo­gies because of a lack of eth­i­cal con­cerns, but “the atti­tudes of our adver­saries toward these tech­nolo­gies have nev­er been ver­i­fied,” researchers wrote.

* U.S. polit­i­cal lead­ers should use forums like NATO to dis­cuss how cyborg advance­ments could impact inter­op­er­abil­i­ty between allied forces dur­ing oper­a­tions.

* The Pen­ta­gon should start invest­ing in legal, secu­ri­ty and eth­i­cal frame­works to antic­i­pate emerg­ing tech­nolo­gies and bet­ter pre­pare for their impact. Lead­ers should sup­port poli­cies that “pro­tect indi­vid­ual pri­va­cy, sus­tain secu­ri­ty, and man­age per­son­al and orga­ni­za­tion­al risk, while max­i­miz­ing defined ben­e­fits to the Unit­ed States and its allies and assets,” the study group wrote.

* Mil­i­tary lead­ers should also work to reverse the “neg­a­tive cul­tur­al nar­ra­tives of enhance­ment tech­nolo­gies.” It’s no secret that sci­ence fiction’s depic­tion of cyborg tech­nolo­gies revolves around dystopi­an futures. Trans­paren­cy in how the mil­i­tary adopts this tech­nol­o­gy will help to alle­vi­ate con­cerns, while cap­i­tal­iz­ing on ben­e­fits, accord­ing to the study group.

* The Pen­ta­gon should use wargames to gauge the impact of asym­met­ric biotech­nolo­gies on tac­tics, tech­niques and pro­ce­dures. DoD per­son­nel can sup­port this through tar­get­ed intel­li­gence assess­ments of the emerg­ing field.

* A whole-of-nation, not whole-of-gov­ern­ment, approach to cyborg tech­nolo­gies is pre­ferred. As it stands, “fed­er­al and com­mer­cial invest­ments in these areas are unco­or­di­nat­ed and are being out­paced by Chi­nese research and devel­op­ment,” the study group wrote. If Chi­nese firms dom­i­nate the com­mer­cial sec­tor, the U.S. defense sec­tor will also be at a dis­ad­van­tage.

* Final­ly, the long-term safe­ty con­cerns and the impact of these tech­nolo­gies on peo­ple should be mon­i­tored close­ly.

“The ben­e­fits afford­ed by human/machine fusions will be sig­nif­i­cant and will have pos­i­tive qual­i­ty-of-life impacts on humankind through the restora­tion of any func­tion­al­i­ty lost due to ill­ness or injury,” the study group wrote.

...

———-

“Cyborg war­riors could be here by 2050, DoD study group says” by Kyle Rempfer; Army Times; 11/27/2019

“The demand for cyborg-style capa­bil­i­ties will be dri­ven in part by the civil­ian health­care mar­ket, which will accli­mate peo­ple to an indus­try fraught with eth­i­cal, legal and social chal­lenges, accord­ing to Defense Depart­ment researchers.”

Civil­ian demand for cyborg-style capa­bil­i­ties is expect­ed to be a dri­ver for the devel­op­ment of this tech­nol­o­gy. So it sounds like the peo­ple who did this study expect soci­eties to read­i­ly embrace cyborg tech­nolo­gies like direct neur­al enhance­ment of the human brain for two-way data trans­fers, a tech­nol­o­gy that’s expect­ed to be par­tic­u­lar­ly impor­tant for com­bat. And if that tech­nol­o­gy is going to be par­tic­u­lar­ly impor­tant for com­bat, it’s pre­sum­ably going to be used in a lot of sol­diers. So it’s expect­ed that both the mil­i­tary and civ­il soci­ety are going to be cre­at­ing the demand for these tech­nolo­gies:

...
The team iden­ti­fied four capa­bil­i­ties as tech­ni­cal­ly fea­si­ble by 2050:

* ocu­lar enhance­ments to imag­ing, sight and sit­u­a­tion­al aware­ness;

* restora­tion and pro­grammed mus­cu­lar con­trol through an opto­ge­net­ic body­suit sen­sor web;

* audi­to­ry enhance­ment for com­mu­ni­ca­tion and pro­tec­tion; and

* direct neur­al enhance­ment of the human brain for two-way data trans­fer.

The study group sug­gest­ed that direct neur­al enhance­ments in par­tic­u­lar could rev­o­lu­tion­ize com­bat.

“This tech­nol­o­gy is pre­dict­ed to facil­i­tate read/write capa­bil­i­ty between humans and machines and between humans through brain-to-brain inter­ac­tions,” an exec­u­tive sum­ma­ry reads. “These inter­ac­tions would allow warfight­ers direct com­mu­ni­ca­tion with unmanned and autonomous sys­tems, as well as with oth­er humans, to opti­mize com­mand and con­trol sys­tems and oper­a­tions.”
...

But note how the study does­n’t just call for soci­ety to address all of the var­i­ous ques­tions that arise when we’re talk­ing about intro­duc­ing cyborg-enhance­ments to human pop­u­la­tions. It also calls for “a whole-of-nation, not whole-of-gov­ern­ment, approach to cyborg tech­nolo­gies,” in order to ensure the US main­tains a tech­no­log­i­cal lead over coun­tries like Rus­sia and Chi­na, and sug­gests mil­i­tary lead­ers should work to reverse the “neg­a­tive cul­tur­al nar­ra­tives of enhance­ment tech­nolo­gies.”:

...
The study group pro­posed sev­en rec­om­men­da­tions, list­ed in no par­tic­u­lar order, for Pen­ta­gon lead­ers to con­sid­er:

* The mil­i­tary should take a sec­ond look at the glob­al and soci­etal per­cep­tion of human-machine aug­men­ta­tion. Amer­i­cans typ­i­cal­ly imag­ine Chi­na or Rus­sia devel­op­ing run­away tech­nolo­gies because of a lack of eth­i­cal con­cerns, but “the atti­tudes of our adver­saries toward these tech­nolo­gies have nev­er been ver­i­fied,” researchers wrote.

* U.S. polit­i­cal lead­ers should use forums like NATO to dis­cuss how cyborg advance­ments could impact inter­op­er­abil­i­ty between allied forces dur­ing oper­a­tions.

* The Pen­ta­gon should start invest­ing in legal, secu­ri­ty and eth­i­cal frame­works to antic­i­pate emerg­ing tech­nolo­gies and bet­ter pre­pare for their impact. Lead­ers should sup­port poli­cies that “pro­tect indi­vid­ual pri­va­cy, sus­tain secu­ri­ty, and man­age per­son­al and orga­ni­za­tion­al risk, while max­i­miz­ing defined ben­e­fits to the Unit­ed States and its allies and assets,” the study group wrote.

* Mil­i­tary lead­ers should also work to reverse the “neg­a­tive cul­tur­al nar­ra­tives of enhance­ment tech­nolo­gies.” It’s no secret that sci­ence fiction’s depic­tion of cyborg tech­nolo­gies revolves around dystopi­an futures. Trans­paren­cy in how the mil­i­tary adopts this tech­nol­o­gy will help to alle­vi­ate con­cerns, while cap­i­tal­iz­ing on ben­e­fits, accord­ing to the study group.

* The Pen­ta­gon should use wargames to gauge the impact of asym­met­ric biotech­nolo­gies on tac­tics, tech­niques and pro­ce­dures. DoD per­son­nel can sup­port this through tar­get­ed intel­li­gence assess­ments of the emerg­ing field.

* A whole-of-nation, not whole-of-gov­ern­ment, approach to cyborg tech­nolo­gies is pre­ferred. As it stands, “fed­er­al and com­mer­cial invest­ments in these areas are unco­or­di­nat­ed and are being out­paced by Chi­nese research and devel­op­ment,” the study group wrote. If Chi­nese firms dom­i­nate the com­mer­cial sec­tor, the U.S. defense sec­tor will also be at a dis­ad­van­tage.

* Final­ly, the long-term safe­ty con­cerns and the impact of these tech­nolo­gies on peo­ple should be mon­i­tored close­ly.

“The ben­e­fits afford­ed by human/machine fusions will be sig­nif­i­cant and will have pos­i­tive qual­i­ty-of-life impacts on humankind through the restora­tion of any func­tion­al­i­ty lost due to ill­ness or injury,” the study group wrote.
...

So as we can see, the report isn’t just a warn­ing about poten­tial com­pli­ca­tions asso­ci­at­ed with the devel­op­ment of cyborg tech­nolo­gies and the need to think this through to avoid dystopi­an out­comes. It’s also a ral­ly­ing cry for a “whole-of-nation” full public/private/military/civilian embrace of these tech­nolo­gies and a warn­ing that the use of these tech­nolo­gies is com­ing whether we like it or not. Which seems kind of dystopi­an.