Unclear and unpresent dangers

Monthly computer magazines used to fret that their news pages would be out of date by the time the new issue reached readers. This week in AI, a blog posting is out of date before you hit send.

This – Friday – morning, the Italian data protection authority, Il Garante, has ordered ChatGPT to stop processing the data of Italian users until it complies with the General Data Protection Regulation. Il Garante’s objections, per Apple’s translation, posted by Ian Brown: ChatGPT provides no legal basis for collecting and processing its massive store of the personal data used to train the model, and that it fails to filter out users under 13.

This may be the best possible answer to the complaint I’d been writing below.

On Wednesday, the Future of Life Institute published an open letter calling for a six-month pause on developing systems more powerful than Open AI’s current state of the art, GPT4. Barring Elon Musk, Steve Wozniack, and Skype co-founder Jaan Tallinn, most of the signatories are unfamiliar names to most of us, though the companies and institutions they represent aren’t – Pinterest, the MIT Center for Artificial Intelligence, UC Santa Cruz, Ripple, ABN-Amro Bank. Almost immediately, there was a dispute over the validity of the signatures..

My first reaction was on the order of: huh? The signatories are largely people who are inventing this stuff. They don’t have to issue a call. They can just *stop*, work to constrain the negative impacts of the services they provide, and lead by example. Or isn’t that sufficiently performative?

A second reaction: what about all those AI ethics teams that Silicon Valley companies are disbanding? Just in the last few weeks, these teams have been axed or cut at Microsoft and Twitch; Twitter of course ditched such fripperies last November in Musk’s inaugural wave of cost-cutting. The letter does not call to reinstate these.

The problem, as familiar critics such as Emily Bender pointed out almost immediately, is that the threats the letter focuses on are distant not-even-thunder. As she went on to say in a Twitter thread, the artificial general intelligence of the Singularitarian’s rapture is nowhere in sight. By focusing on distant threats – longtermism – we ignore the real and present problems whose roots are being continuously more deeply embedded into the new-building infrastructure: exploited workers, culturally appropriated data, lack of transparency around the models and algorithms used to build these systems….basically, all the ways they impinge upon human rights.

This isn’t the first time such a letter has been written and circulated. In 2015, Stephen Hawking, Musk, and about 150 others similarly warned of the dangers of the rise of “superintelligences”. Just a year later, in 2016, Pro Publica investigated the algorithm behind COMPAS, a risk-scoring criminal justice system in use in US courts in several states. Under Julia Angwin‘s scrutiny, the algorithm failed at both accuracy and fairness; it was heavily racially biased. *That*, not some distant fantasy, was the real threat to society.

“Threat” is the key issue here. This is, at heart, a letter about a security issue, and solutions to security issues are – or should be – responses to threat models. What is *this* threat model, and what level of resources to counter it does it justify?

Today, I’m far more worried by the release onto public roads of Teslas running Full Self Drive helmed by drivers with an inflated sense of the technology’s reliability than I am about all of human work being wiped away any time soon. This matters because, as Jessie Singal, author of There Are No Accidents, keeps reminding us, what we call “accidents” are the results of policy decisions. If we ignore the problems we are presently building in favor of fretting about a projected fantasy future, that, too, is a policy decision, and the collateral damage is not an accident. Can’t we do both? I imagine people saying. Yes. But only if we *do* both.

In a talk this week for a group at the French international research group AI Act. This effort began well before today’s generative tools exploded into public consciousness, and isn’t likely to conclude before 2024. It is, therefore, much more focused on the kinds of risks attached to public sector scandals like COMPAS and those documented in Cathy O’Neil’s 2017 book Weapons of Math Destruction, which laid bare the problems with algorithmic scoring with little to tether it to reality.

With or without a moratorium, what will “AI” look like in 2024? It has changed out of recognition just since the last draft text was published. Prediction from this biological supremacist: it still won’t be sentient.

All this said, as Edwards noted, even if the letter’s proposal is self-serving, a moratorium on development is not necessarily a bad idea. It’s just that if the risk is long-term and existential, what will six months do? If the real risk is the hidden continued centralization of data and power, then those six months could be genuinely destructive. So far, it seems like its major function is as a distraction. Resist.

Illustrations: IBM’s Watson, which beat two of Jeopardy‘s greatest champions in 2011. It has since failed to transform health care.

Wendy M. Grossman is the 2013 winner of the Enigma Award. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. Follow on Mastodon or Twitter.

Re-centralizing

But first, a housekeeping update. Net.wars has moved – to a new address and new blogging software. For details, see here. If you read net.wars via RSS, adjust your feed to https://netwars.pelicancrossing.net. Past posts’ old URLs will continue to work, as will the archive index page, which lists every net.wars column back to November 2001. And because of the move: comments are now open for the first time in probably about ten years. I will also shortly set up a mailing list for those who would rather get net.wars by email.

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This week the Ada Lovelace Institute held a panel discussion of ethics for researchers in AI. Arguably, not a moment too soon.

At Noema magazine, Timnet Gebru writes, as Mary L Gray and Siddharth Suri have previously, that what today passes for “AI” and “machine learning” is, underneath, the work of millions of poorly-paid marginalized workers who add labels, evaluate content, and provide verification. At Wired, Gebru adds that their efforts are ultimately directed by a handful of Silicon Valley billionaires whose interests are far from what’s good for the rest of us. That would be the “rest of us” who are being used, willingly or not, knowingly or not, as experimental research subjects.

Two weeks ago, for example, a company called Koko ran an experiment offering chatbot-written/human-overseen mental health counseling without informing the 4,000 people who sought help via the “Koko Cares” Discord server. In a Twitter thread. company co-founder Rob Morris said those users rated the bot’s responses highly until they found out a bot had written them.

People can build relationships with anything, including chatbots, as was proved in 1996 with the release of the experimental chatbot therapist Eliza. People found Eliza’s responses comforting even though they knew it was a bot. Here, however, informed consent processes seem to have been ignored. Morris’s response, when widely criticized for the unethical nature of this little experiment was to say it was exempt from informed consent requirements because helpers could opt whether to use the chatbot’s reponses and Koko had no plan to publish the results.

One would like it to be obvious that *publication* is not the biggest threat to vulnerable people in search of help. One would also like modern technology CEOs to have learned the right lesson from prior incidents such as Facebook’s 2012 experiment to study users’ moods when it manipulated their newsfeeds. Facebook COO Sheryl Sandberg apologized for *how the experiment was communicated*, but not for doing it. At the time, we thought that logic suggested that such companies would continue to do the research but without publishing the results. Though isn’t tweeting publication?

It seems clear that scale is part of the problem here, like the old saying, one death is a tragedy; a million deaths are a statistic. Even the most sociopathic chatbot owner is unlikely to enlist an experimental chatbot to respond to a friend or family member in distress. But once a screen intervenes, the thousands of humans on the other side are just a pile of user IDs; that’s part of how we get so much online abuse. For those with unlimited control over the system we must all look like ants. And who wouldn’t experiment on ants?

In that sense, the efforts of the Ada Lovelace panel to sketch out the diligence researchers should follow are welcome. But the reality of human nature is that it will always be possible to find someone unscrupulous to do unethical research – and the reality of business nature is not to care much about research ethics if the resulting technology will generate profits. Listening to all those earnest, worried researchers left me writing this comment: MBAs need ethics. MBAs, government officials, and anyone else who is in charge of how new technologies are used and whose decisions affect the lives of the people those technologies are imposed upon.

This seemed even more true a day later, at the annual activists’ gathering Privacy Camp. In a panel on the proliferation of surveillance technology at the borders, speakers noted that every new technology that could be turned to helping migrants is instead being weaponized against them. The Border Violence Monitoring Network has collected thousands of such testimonies.

The especially relevant bit came when Hope Barker, a senior policy analyst with BVMN, noted this problem with the forthcoming AI Act: accountability is aimed at developers and researchers, not users.

Granted, technology that’s aborted in the lab isn’t available for abuse. But no technology stays the same after leaving the lab; it gets adapted, altered, updated, merged with other technologies, and turned to uses the researchers never imagined – as Wendy Hall noted in moderating the Ada Lovelace panel. And if we have learned anything from the last 20 years it is that over time technology services enshittify, to borrow Cory Doctorow’s term in a rant which covers the degradation of the services offered by Amazon, Facebook, and soon, he predicts, TikTok.

The systems we call “AI” today have this in common with those services: they are centralized. They are technologies that re-advantage large organizations and governments because they require amounts of data and computing power that are beyond the capabilities of small organizations and individuals to acquire. We can only rent them or be forced to use them. The ur-evil AI, HAL in Stanley Kubrick’s 2001: A Space Odyssey taught us to fear an autonomous rogue. But the biggest danger with “AIs” of the type we are seeing today, that are being put into decision making and law enforcement, is not the technology, nor the people who invented it, but the expanding desires of its controller.

Illustrations: HAL, in 2001.

Wendy M. Grossman is the 2013 winner of the Enigma Award. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns back to November 2001. Comment here, or follow on Mastodon or Twitter.