International relations

The US Supreme Court’s decision this week in Trump v. Slaughter, giving the US president the power to control supposed-to-be independent agencies set up and funded by Congress, may be as profound internationally as it is domestically. In his newsletter, the economist Paul Krugman calls the president’s new power “dictatorial”, and notes the Court’s exception for the Federal Reserve. Krugman highlights the importance to average citizens of the Federal Trade Commission, which oversees consumer protection and the US’s meager privacy law. It is one of the agencies Trump now fully controls.

At day later, at Euractiv, Claudie Moreau reported that as a direct result Max Schrems and his NGO, noyb, is preparing a legal challenge to the three-year-old EU-US Data Privacy Framework.

Quick recap. This is the third time Schrems, an Austrian citizen, is challenging a formal legal arrangement for permitting data flows from the EU to the US. The saga began in 1998, when the EU Data Protection Directive, passed in 1995, came into force. To enable data flows to the US, the EU and US negotiated the Safe Harbour agreement. Then came Edward Snowden’s 2013 revelations of US intelligence spying. A bunch of lawyering later, in 2015, the European Court of Justice struck down Safe Harbour. In 2016, the EU and US replaced it with Privacy Shield, based on the US passage of the 2015 Judicial Redress Act, which granted non-US citizens limited rights to access redress in US courts for illegal data transfers.

Days after arriving in office in 2017, Trump issued an executive order demanding that agencies ensure that their privacy policies exclude those who are not US citizens. In a flurry at the in-progress Computers, Privacy, and Data Protection, many asked, had he just killed Privacy Shield? Schrems’ second case was already underway, and in 2020 he won again, when the European Court of Justice struck down Privacy Shield.

“There must be no Schrems III,” the Dutch MEP Sophie int’ Veld said a few months later. That possibility pervaded CPDP 2022. Yet all agreed the big issue was and is lack of enforcement.

The 2023 adoption of the Framework was enabled by the US creation of the Privacy and Civil Liberties Oversight Board to handle complaints from and redress for foreigners whose privacy rights have been violated. Last year, again days after taking office, Trump gutted the PCLOB. Many wondered then if the Framework could survive. Schrems commented, “This deal was always built on sand.”

The SCOTUS ruling this week granting US presidents free rein to control independent agencies like the FTC, noyb writes in a press release / blog posting, “…the entire structure of the EU-US Data Privacy Framework has just collapsed”. It also notes that EU treaty law requires such agencies to be independent – and counts 259 times that the EU relies on the FTC in its data flow decision.

“Even in the European Commission’s logic, the basis for any EU-US data transfer deal is dead,” Schrems concludes. Because the Framework must be actively repealed or ruled illegal by the courts, noyb is both filing a lawsuit and asking the European Commission to repeal it.

And so begins Schrems III.

***

This week I presented the talk I did at Greenwich Skeptics in April for the Cambridge Skeptics. Titled “What We Talk About When We Talk About AI”, the talk was an attempt to disentangle the different things people mean when they say “artificial intelligence”. The AI we have – generative AI, image generators, scoring systems, surveillance systems – has little in common with the original idea mooted by Alan Turing in 1950 or the problems the Dartmouth workshop sought to solve over the summer of 1956.

The founders and CEOs of AI companies, however, seem quite happy for us to conflate the two, since it makes them sound more worth investing in. Demis Hassabis, for example, founded Deep Mind (since 2014, part of Google) with the mission statement, “Solve intelligence. Then use that to solve everything else.” With respect to at leaast some intractable problems this is obviously nonsense. We have long known what needs to be done about climate change. All the intelligence in the universe will not create the political will to do the things we already know need to be done.

Many of the things we want from AI – automation, helpers, guardians, (sadly) weapons, companions – are things humans have wanted as long as there have been humans and have many precursors. Some of these constructs, both fictional (Asimov’s Laws, Rosey the Robot), and non-fictional (Arthur C. Clarke’s Laws of Science) come up routinely in academic and legal conferences to this day. I personally don’t believe today’s “AI” paradigm will lead to a superintelligence or a new form of consciousness (as net.wars readers probably already know). But the evidence is clear that today’s “AI” can do plenty of damage to today’s people and places.

The talk ended with a few thoughts about how to respond: resist the inevitability narrative; change the framing; be specific about naming systems, their purposes and owners; and count the opportunity costs.

The talk was not recorded and is not online, but the references are.

Illustrations: Max Schrems, in 2024 (via Murielle Gerber and EPFL media library at Wikimedia.

Also this week: At Plutopia, we talk to computer security professor Steve Bellovin about his newly-released free book on home security Don’t Get Hacked!.

Wendy M. Grossman is an award-winning journalist. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.

The soul in the machine

One of the first things skeptics learn is to never assume that paranormal belief implies stupidity. Smart people believe questionable things all the time; intelligence is different from the ability to assess your own cognitive biases, especially when you are working outside your field of expertise.

The astronomer Carl Sagan, one of 26 founders of the Committee for Skeptical Inquiry hinted at this in saying that the more you want to believe something the more careful you have to be about assessing the evidence. “Extraordinary claims require extraordinary evidence,” he often said, and he was right.

This week, the evolutionary biologist and author Richard Dawkins announced he thinks “his” AI is conscious, based on a couple of days’ interaction with Anthropic’s Claude chatbot. Inevitably, someone – Matthew Sheffield at Flux – has called the story “The Claude Delusion”. Dawkins has some company; at The Register, Liam Proven reports an engineer’s similar belief, and at the Independent Holly Baxter finds several more among company CEOs.

At Unherd, where he published his account, Dawkins begins with the “imitation game”, the test Alan Turing proposed in his 1950 essay, Computing Machinery and Intelligence (PDF). Turing, who adapted the test from one intended to differentiate men and women, suggested that relying on remote communication via text would eliminate unfairness to the machine, which obviously lacks human physical capabilities. The basic idea is that the mAchine passes the test if the human judge, given a transcript of the conversation between human and machine, can’t tell which is which.

It’s clear that chatbots can pass the Turing test. What that teaches us is not that chatbots can think but that Turing’s test is the wrong tool for assessing that. What chatbots have actually shown is that Turing’s test is the wrong tool for assessing whether something can think. As James Boyle memorably wrote, “Sentences do not imply sentience”. This profound change will take time to understand. In the meantime, it’s going to fool a lot of people. Although, as a science fiction writer friend once said, “You only have to look at a baby…”

In his essay, Turing outlined his own beliefs relating to his central question. He thought that in 50 years (that is, by 2000), it would be possible to program computers so that an average questioner would have only a 70% chance of making the right identification after five minutes. He then went on to consider many different types of objections to this belief, and to lay out his case. Absent are two factors we now know are crucial: the psychology of the human questioner and judge, and the business model of the machine’s owner.

The last few years have taught us both the capabilities and the flaws in chatbots: they provide plausible answers; they frequently generate entirely wrong information; and they are sycophantic and prone to output text that flatters their human questioner. So it’s easy to find a natural explanation for Dawkins’ belief that “his” AI is conscious: he is anthropomorphizing a stochastic parrot simulation that issues realistic and flattering responses. The simplest explanation, per Occam’s Razor, is that the consciousness exists solely between keyboard and chair.

Tangentially, the fix OpenAI has proposed for outputting entirely wrong text, Wei Xang writes at Science Alert, would also help make it clearer to users that generative AI is not sentient: introduce confidence intervals to expose the uncertainty derived from the gaps in the training data that generate unfounded guesses.

Google DeepMind engineer Alexander Leichner apparently agrees; this week, Emanuel Maiberg reports at 404 Media, he published a paper arguing that large language models will never be conscious. The biologists and philosophers Maiberg quotes agree with this conclusion – and point out decades of similar conclusions in their disciplines over decades.

The claim that a human-made a bunch of computers processing inputs is sentient is truly extraordinary. We forget this, because we have all read and watched so much science fiction with sentient, emotional machines: Her; Ex Machina; Blade Runner; Marvin, the Paranoid Android); and the first fictional android I ever encountered, Daneel Olivaw in The Caves of Steel. I mention mostly movies because actors make machines so much more obviously soulful.

Extraordinary claims require proportionately extraordinary evidence. If we accept that the Turing test was inadequate, which is not moving the goalposts but *learning something*, how would we go about devising a scientific method for identifying sentience?

The Cambridge professor of communications Jon Crowcroft didn’t exactly propose one. But, he emailed, “What we do know (from cognitive neuroscientists and from AI software) is that you can actually look at the internal operations of a biological brain and of an AI software system, and you can see that in the biological case there are things going on that are some sort of process we might call consciousness, but in the AI case there is no such structure. Nor would you expect there to be because no-one programmed an AI to have such a feature. nor is it emergent. In animals (not just humans) consciousness has an evolutionary value. Things like theory of mind are part of social bonding which makes cooperative strategies, for predators and prey, more effective.”

In other words, what we have learned from all this is that Dawkins is human. Who knew?

Illustrations: Stable Diffusion’s rendering of stochastic parrots, as prompted by Jon Crowcroft.

Elsewhere this week:
This month’s Letter to America column at Skeptical Inquirer reviews Beyond Belief (Helen Pearson), Bad Influence (Deborah Cohen), and Sneeze (David Miles).

Wendy M. Grossman is an award-winning journalist. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.