Sunday 26 January, 2020

What the Clearview AI story means

This morning’s Observer column:

Ultimately, the lesson of Clearview is that when a digital technology is developed, it rapidly becomes commodified. Once upon a time, this stuff was the province of big corporations. Now it can be exploited by small fry. And on a shoestring budget. One of the co-founders paid for server costs and basic expenses. Mr Ton-That lived on credit-card debt. And everyone worked from home. “Democracy dies in darkness” goes the motto of the Washington Post. “Privacy dies in a hacker’s bedroom” might now be more appropriate.

Read on

UPDATE A lawsuit — seeking class-action status — was filed this week in Illinois against Clearview AI, a New York-based startup that has scraped social media networks for people’s photos and created one of the biggest facial recognition databases in the world.


Privacy is a public good

Shoshana Zuboff in full voice:

”The belief that privacy is private has left us careening toward a future that we did not choose, because it failed to reckon with the profound distinction between a society that insists upon sovereign individual rights and one that lives by the social relations of the one-way mirror. The lesson is that privacy is public — it is a collective good that is logically and morally inseparable from the values of human autonomy and self-determination upon which privacy depends and without which a democratic society is unimaginable.”

Great OpEd piece.


The winding path


Why the media shouldn’t underestimate Joe Biden

Simple: Trump’s crowd don’t. They think he’s the real threat. (Which explains the behaviour that’s led to Trump’s Impeachment.) David Brooks has some sharp insights into why the chattering classes are off target About this.

It’s the 947th consecutive sign that we in the coastal chattering classes have not cured our insularity problem. It’s the 947th case in which we see that every second you spend on Twitter detracts from your knowledge of American politics, and that the only cure to this insularity disease is constant travel and interviewing, close attention to state and local data and raw abject humility about the fact that the attitudes and academic degrees that you think make you clever are actually the attitudes and academic degrees that separate you from the real texture of American life.

Also, the long and wide-ranging [NYT interview)(https://www.nytimes.com/interactive/2020/01/17/opinion/joe-biden-nytimes-interview.html) with him is full of interesting stuff — like that he thinks that Section 230 of the Communications Decency Act (that’s the get-out-of-gaol card for the tech companies) should be revoked. I particularly enjoyed this observation by Brooks: “ Jeremy Corbyn in Britain and Bernie Sanders here are a doctoral student’s idea of a working-class candidate, not an actual working person’s idea of one.”


Linkblog

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Foresight, ignored

I’ve been reading “The Anatomy of a Large-Scale Hypertextual Web Search Engine”, the original academic paper in which the co-founders of Google, Sergey Brin and Larry Page, outlined their search engine and its properties. It’s a fascinating read for various reasons, not least the evidence it presents of the pair’s originality. And at the end there are two Appendices, the first of which suggests an eerie prescience about the extent to which advertising would be a malignant business model for any enterprise aiming at objective search. Here it is:

Appendix A: Advertising and Mixed Motives

Currently, the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users. For example, in our prototype search engine one of the top results for cellular phone is “The Effect of Cellular Phone Use Upon Driver Attention”, a study which explains in great detail the distractions and risk associated with conversing on a cell phone while driving. This search result came up first because of its high importance as judged by the PageRank algorithm, an approximation of citation importance on the web [Page, 98]. It is clear that a search engine which was taking money for showing cellular phone ads would have difficulty justifying the page that our system returned to its paying advertisers. For this type of reason and historical experience with other media [Bagdikian 83], we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.

Since it is very difficult even for experts to evaluate search engines, search engine bias is particularly insidious. A good example was OpenText, which was reported to be selling companies the right to be listed at the top of the search results for particular queries [Marchiori 97]. This type of bias is much more insidious than advertising, because it is not clear who “deserves” to be there, and who is willing to pay money to be listed. This business model resulted in an uproar, and OpenText has ceased to be a viable search engine. But less blatant bias are likely to be tolerated by the market. For example, a search engine could add a small factor to search results from “friendly” companies, and subtract a factor from results from competitors. This type of bias is very difficult to detect but could still have a significant effect on the market. Furthermore, advertising income often provides an incentive to provide poor quality search results. For example, we noticed a major search engine would not return a large airline’s homepage when the airline’s name was given as a query. It so happened that the airline had placed an expensive ad, linked to the query that was its name. A better search engine would not have required this ad, and possibly resulted in the loss of the revenue from the airline to the search engine. In general, it could be argued from the consumer point of view that the better the search engine is, the fewer advertisements will be needed for the consumer to find what they want. This of course erodes the advertising supported business model of the existing search engines. However, there will always be money from advertisers who want a customer to switch products, or have something that is genuinely new. But we believe the issue of advertising causes enough mixed incentives that it is crucial to have a competitive search engine that is transparent and in the academic realm.

In today’s edition of his regular newsletter ‘Big’, Matt Stoeller reports something Rana Foroohar, author of Don’t Be Evil: the case against Big Tech (my review of which is here), said when he asked her what was the most surprising or weird thing she learned when working on her book. “I don’t know if it’s weird”, she replied,

but the most surprising thing I leaned while researching the book was that the founders of Google, Sergei and Larry, had basically predicted the key problems with surveillance capitalism and where they would lead us back in their original paper on search, written while they were Stanford grad students. At the very end, in the appendix, there’s a paragraph where they admit that the targeted advertising business model could be misused by companies or other entities in ways that would hurt users. This is kind of a bombshell revelation given that search engines say everything they do is for users. The fact that this paper hasn’t gotten more attention makes me think people aren’t reading….which is itself part of the problem of attention capture I describe in the book.

Matt’s book Goliath: The 100-year war between monopoly power and democracy is well worth a read, btw.

How “Don’t Be Evil” panned out

My Observer review of Rana Foroohar’s new book about the tech giants and their implications for our world.

“Don’t be evil” was the mantra of the co-founders of Google, Sergey Brin and Larry Page, the graduate students who, in the late 1990s, had invented a groundbreaking way of searching the web. At the time, one of the things the duo believed to be evil was advertising. There’s no reason to doubt their initial sincerity on this matter, but when the slogan was included in the prospectus for their company’s flotation in 2004 one began to wonder what they were smoking. Were they really naive enough to believe that one could run a public company on a policy of ethical purity?

The problem was that purity requires a business model to support it and in 2000 the venture capitalists who had invested in Google pointed out to the boys that they didn’t have one. So they invented a model that involved harvesting users’ data to enable targeted advertising. And in the four years between that capitulation to reality and the flotation, Google’s revenues increased by nearly 3,590%. That kind of money talks.
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Rana Foroohar has adopted the Google mantra as the title for her masterful critique of the tech giants that now dominate our world…

Read on

Another reason not to like Facebook Likes

From The Register:

Organisations that deploy Facebook’s ubiquitous “Like” button on their websites risk falling foul of the General Data Protection Regulation following a landmark ruling by the European Court of Justice.

The EU’s highest court has decided that website owners can be held liable for data collection when using the so-called “social sharing” widgets.

The ruling (PDF) states that employing such widgets would make the organisation a joint data controller, along with Facebook – and judging by its recent record, you don’t want to be anywhere near Zuckerberg’s antisocial network when privacy regulators come a-calling.

Well, well.

The soft underbelly of social media

Sarah Roberts has just published Behind the Screen: Content Moderation in the Shadows of Social Media, a major study of the impact of content ‘moderation’ on those who clean up social media so that the rest of us are not traumatised or scandalised by what appears in our feeds. Isaac Chotiner has an interesting interview with her in the New Yorker which includes this brief exchange:

You also go to the Philippines in this book and you talk to people from other countries, in Mexico, for example. What are the consequences of outsourcing these jobs in terms of the quality of the work being done? And I don’t ask that to imply that people abroad can’t do a job as well.

I think there is a precedent for outsourcing this type of service work, and we see that in the call-center industry. The same kinds of problems that are present in that work are present in this particular context. So that would be things like the dissonance and distance culturally and linguistically, contextually, and politically, for a group of people that are being asked to adjudicate and make decisions about material that emanates from one place in the world and is destined for another, that may have absolutely nothing to do with their day-to-day life.

I think a second thing is that the marketplace has chased a globalization solution for the same reasons it has in other industries, which are the issues of: Where can we get the cheapest labor? What countries are lax in terms of labor protections? Where is organizing low? Where is there a huge pool of people for whom this job might be appealing because it’s better than the other jobs on offer? It’s not a simple case of everyone in the Philippines who does this work is exploited, and I was really trying hard not to make that claim in the book. But, at the same time, the United States sends the work to the Philippines for a reason. It sends the work there because Filipino people have a long-standing relationship, so to speak, with the United States, that means that they have a better facility to understand the American context. That’s actually been in the favor of most people in the Philippines.

It’s worrisome to see those kinds of colonial traditions and practices picked up again, especially in this digital marketplace, this marketplace of the mind that was supposed to be deliverance from so many of the difficult working conditions of the twentieth century. So I think that’s the big thing about the way that this plays out on the global stage. The companies have a problem that they don’t have enough people to do the work. And so they are pulling out all the stops in a way to find people to do the work, but it’s still not nearly enough.

What could be done to make the lives of these workers better, given that this is a job that needs to be done? And it needs to be done by smart people doing it well, who need to be very well-trained.

This is a question that I’ve often posed to the workers themselves because I certainly am not possessed of the answers on my own. They want better pay. And I think we can read that in a lot of ways: they want better pay, they want to be respected. The nature of the way the work has been designed has been for the work to be secret. In many cases, their N.D.A. precludes them from even talking about the work. And the industry itself formulated the job as a source of shame in that sense, an industry source of shame. They were not eager to tout the efforts of these people, and so instead they hid them in the shadows. And, if nothing else, that was a business decision and a value judgment that could have gone another way. I think there’s still a chance that we could understand the work of these people in a different way and value it differently, collectively. And we could ask that the companies do that as well.

Good interview. Splendid book.

Quote of the Day

Q: We’re now more than two years out from that experience, and obviously the controversies have not gone away — they’ve actually multiplied. Do you think Zuckerberg and Sandberg have made any progress on the stuff you warned about?

A: I want to avoid absolutes, but I think it’s safe to say that the business model is the source of the problem, and that it’s the same business model as before. And to the extent that they made progress, it’s in going after different moles in the Whack-a-Mole game. From the point of view of the audience, Facebook is as threatening as ever.

From an interview with Roger McNamee, an early investor in Facebook and apparently a recovering former mentor to Mark Zuckerberg. He’s also the author of Zucked: Waking Up to the Facebook Catastrophe.

The dark side of recommendation engines

This morning’s Observer column:

My eye was caught by a headline in Wired magazine: “When algorithms think you want to die”. Below it was an article by two academic researchers, Ysabel Gerrard and Tarleton Gillespie, about the “recommendation engines” that are a central feature of social media and e-commerce sites.

Everyone who uses the web is familiar with these engines. A recommendation algorithm is what prompts Amazon to tell me that since I’ve bought Custodians of the Internet, Gillespie’s excellent book on the moderation of online content, I might also be interested in Safiya Umoja Noble’s Algorithms of Oppression: How Search Engines Reinforce Racism and a host of other books about algorithmic power and bias. In that particular case, the algorithm’s guess is accurate and helpful: it informs me about stuff that I should have known about but hadn’t.

Recommendation engines are central to the “personalisation” of online content and were once seen as largely benign…

Read on

Shoshana Zuboff’s new book

Today’s Observer carries a five-page feature about Shoshana Zuboff’s The Age of Surveillance Capitalism consisting of an intro by me followed by Q&A between me and the author.

LATER Nick Carr has a perceptive review of the book in the LA Review of Books. John Thornhill also had a good long review in last Saturday’s Financial Times, sadly behind a paywall.

Understanding platforms

From an interesting piece by Max Fisher:

We think of any danger as coming from misuse — scammers, hackers, state-sponsored misinformation — but we’re starting to understand the risks that come from these platforms working exactly as designed. Facebook, YouTube and others use algorithms to identify and promote content that will keep us engaged, which turns out to amplify some of our worst impulses.

Even after reporting with Amanda Taub on algorithm-driven violence in Germany and Sri Lanka, I didn’t quite appreciate this until I turned on Facebook push alerts this summer. Right away, virtually every gadget I owned started blowing up with multiple daily alerts urging me to check in on my ex, even if she hadn’t posted anything. I’d stayed away from her page for months specifically to avoid training Facebook to show me her posts. Yet somehow the algorithm had correctly identified this as the thing likeliest to make me click, then followed me across continents to ensure that I did.

It made me think of the old “Terminator” movies, except instead of a killer robot sent to find Sarah Connor, it’s a sophisticated set of programs ruthlessly pursuing our attention. And exploiting our most human frailties to do it.