AI Will Understand Humans Better Than Humans Do

A Stanford study psychologist with a passion for cutting-edge topics, Michael Kosinski is one of them. He believes that his work serves as an example of how computer science advances understanding and raises awareness of potential hazards brought on by its effects. His most well-known projects included analysing the ways in which Facebook ( now Meta ) gained an astonishingly detailed understanding of its users from all the times they clicked “like” on the platform. He has then switched to researching new ways that AI can be useful. He’s conducted research, for example, that indicate that laptops may identify a woman’s sexuality by analyzing a digital photograph of their experience.

Through my reading about Meta, I’ve gotten to know Kosinski, and we recently spoke over his most recent report, which was published this week in the peer-reviewed Proceedings of the National Academy of Sciences. His finish is striking. Large language versions like OpenAI’s, he claims, have crossed a boundary and are using methods analogous to actual idea, once considered purely the world of flesh-and-blood individuals ( or at least animals ). Specifically, he tested OpenAI’s GPT-3.5 and GPT-4 to see if they had mastered what is known as” theory of mind”. This potential, which was developed during the humanities ‘ early ages, allows for the comprehension of other people’s thought processes. It’s an essential ability. If a computer system ca n’t interpret what people think correctly, its understanding of the world will become impoverished and cause many problems. If types have theory of mind, they are one step closer to exceeding and matching human potential. Kosinski tested LLMs, and now claims that his findings indicate that a concept of mind-like ability “may have emerged as an unexpected by-product of LLMs’ improving language skills… They signify the development of more powerful and politically experienced AI.”

Kosinski sees his job in AI as a direct result of his earlier exploration of Twitter Wants. ” I was not really studying cultural sites, I was studying people”, he says. He claims that when Google and OpenAI began creating their most recent conceptual AI models, they believed they were mainly teaching them to handle language. You ca n’t predict what word I’m going to say next without modeling your mind, so they trained a human mind model.

Kosinski is careful to avoid making the mistaken say that LLMs have completely mastered theory of mind. He gave the bots a few traditional problems in his experiments, some of which they handled really well. But even the most powerful concept, GPT-4, failed a third of the time. The achievement, he writes, put GPT-4 on a stage with 6-year-old kids. No bad, given the early position of the area. ” Observing AI’s swift progress, some question whether and when AI could reach ToM or consciousness”, he writes. Putting off that nuclear c-word, that’s a lot to digest on.

If theory of mind naturally manifested in those models, it also suggests that different abilities might develop as well, he says. ” They can be better at educating, controlling, and manipulating us owing to those skills”. He worries that we are n’t really prepared for LLMs that comprehend how people think. particularly if they eventually get to the point where they comprehend people more fully than humans do.

” We individuals do not model personality—we have personality”, he says. ” So I’m kind of stuck with my character. These things design character. They have an edge in that they can have any temperament they want at any time. Kosinski groans when I tell him that it sounds like he’s describing a narcissist. ” I use that in my deals”! he says. ” A narcissist can put on a mask—they’re never truly unhappy, but they can enjoy a terrible person”. This chameleon-like strength could render AI a better scammer. With zero grief.

Some studies psychologists have challenged Kosinski’s says. A group of AI experts suggested Kosinski was truly observing a” Clever Hans,” a prominent early 20th century animal that people were duped into believing could do math and keep track of a calendar in a draft Kosinski had published on Arxiv in early 2023. Their argument was that an LLM fully fails if it fails even one check of theory of mind. “LLMs might have some logic powers, but it’s certainly not perfect or strong in the way of people”, says Vered Shwartz, an assistant teacher of computer science at the University of British Columbia, who is one of the coauthors. ” We did a lot of different tests, and we definitely ca n’t claim that language models have the same]theory-of-mind ] ability that people do. And it could be that it’s just cheating”.

Shwartz is referring to the fact that some LLMs inevitably contain published academic papers that discuss experiments that are comparable to those conducted by Kosinski because they are trained on enormous corpora of information. GPT-4 might have searched through its extensive training manuals to find the solutions. AI’s skeptic-in-chief, Gary Marcus, found that the tests Kosinski used were also deployed in classic experiments that had been cited in scientific papers more than 11, 000 times. It appears as though the LLMs were using theory of mind to fake their own crib sheets. ( To me, this cold-blooded shortcut to cognition, if true, is even scarier than LLMs emergently acquiring theory of mind. )

Kosinski claims that the criticisms were addressed in the most recent paper. Also, some other papers have been published recently that seem to bolster his claims, including one in Nature Human Behavior that found that both GPT-3.5 and GPT-4, while not succeeding at every theory-of-mind task, “exhibited impressive performance” on some of them, and “exceeded human level” on others. In an email to me, the lead author, James Strachan, a postdoctoral researcher at the University Medical Center Hamburg-Eppendorf, does n’t claim that LLMs have fully mastered theory of mind, but says his team did refute the cheating charge. It appears that these abilities transcend simply repurposing the information used to train LLMs, he claims, and that “it is possible to reconstruct a great deal of information about human mental states from the statistics of natural language.”

I’m unsure whether LLMs will actually develop theory of mind. What matters is whether they act as though they possess that skill, which they are undoubtedly on the verge of. Even Shwartz, who swatted down some of Kosinski’s methods, concedes that it’s possible. ” If companies continue to make language models more sophisticated, maybe they would have ]ToM] at some point”, she says.

That’s why Kosinski, despite the tough critiques of his work, is worth listening to. According to his paper, Theory of Mind is “unlikely to be the pinnacle of what neural networks can achieve in this universe,” he writes. We might soon be surrounded by AI systems that have cognitive prowesses that we, humans, cannot even imagine. Happy holidays!

Kosinski was a pioneer in the analysis of Facebook data, and he contributed to Cambridge Analytica’s infamous misuse of data on the service as an early researcher in the field at Cambridge University. But as I wrote in my book Facebook: The Inside Story, Kosinski’s work ( with collaborator David Stillwell ) alerted the world to how much data Facebook gathered whenever people pressed the ever-present Like button. Just as now, critics challenged his findings.

Kosinski encountered some skepticism about ]his ] methodology. ” Senior academics at that time did n’t use Facebook, so they believed these stories that a 40-year-old man would suddenly become a unicorn or a 6-year-old girl or whatever”, he says. Kosinski was aware of the fact that what users did on Facebook had a real selves. And as he began to use Facebook Likes more and more, he realized how revealing they were. He came to the conclusion that you did n’t need a quiz to be so knowledgeable about people. What you were looking for on Facebook was all you needed to know.

Kosinski]and collaborators ] used statistics to make predictions about personal traits from the Likes of about 60, 000 volunteers, then compared the predictions to the subjects ‘ actual traits as revealed by the myPersonality test. The authors had to recheck and recheck the outcomes because they were so astounding. He claims that it took him a year to actually gain confidence in the results and publish them because he “felt uneasy” about it. They only discovered that 88 percent of the time by analyzing Likes whether someone was straight or gay. In 19 out of 20 cases, they could figure out if someone was White or African American. And they were 85 percent accurate in predicting a person’s political party.

In the coming months, Kosinski and Stillwell would develop their prediction techniques and publish a paper that claimed a researcher would know someone better than those who worked with, grew up with, or even married that person using Likes alone. ” Computer models need 10, 70, 150, and 300 Likes, respectively, to outperform an average work colleague, cohabitant or friend, family member and spouse”, they wrote.

Alan asks,” Why ca n’t we choose how to pay for online content”?

Thanks for the question, Alan. It’s one that baffles me, too. I have no tolerance for those who complain when they come across articles that appear behind paywalls. At one point, young people, everything was in print, and you could n’t read it for free unless you grabbed it from the newstand and waited for the owner to take it away. Folks, it costs money to produce those gems. Admittedly, the news industry did n’t do itself any favors initially by giving its content away online, but now most, if not all, places have abandoned the idea that digital ads alone can fund excellent writing and reporting.

However, you are voicing your disapproval of how we are paid for it. I’m assuming that you find our current system to be nothing more than a subscription. There’s generally no way to pay a small fee for a single article or even newsletter. How many times have you clicked on a link that might be useful in a newspaper in a town you’ve never been to and had to pay a credit card to access the archives and news without having to give it up completely? Literally for decades, I’ve been assuming that a simple micropayment system will be created and put into use. The technical challenges are minimal. Yet despite multiple attempts, none has caught on. One company, Blendle, once promised to” save journalism” with its micropayment system. It announced last year that it was moving to an Apple News-style subscription service that would give access to multiple publications and that it was no longer in the pay-per-article industry.

Micropayment appears to be dead. Still, when I hit a paywall and ca n’t access something I want to read, I would certainly hit a button that would move a few cents, or in some cases even a dollar or two, into the account of a publication. It seems so logical. Making sense is not enough of a condition for something to actually occur, as we all too well know.

You can submit questions to [email protected]. Include the phrase” ASK LEVY” in the subject line.

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