![]() If you were to ask a human to consider true and false statements in turn, for instance, and monitor their brain activity, different regions might light up. Over time, he developed a strong intuition: that it might be possible to read the mind of a large language model.Īs Burns saw it, the minds of humans and those of large language models were, in one salient respect, not so different: related information clusters together, allowing you to search for patterns and structures. In 2015, he broke the world record, solving the puzzle in just 5.25 seconds.Īt UC Berkeley, where he started a PhD in Computer Science during the pandemic, Burns applied a similar approach to research. Burns developed an intuition for what might happen after the next twist. Paradoxically, this approach made him very, very fast. Rather than memorize complex algorithms for unique cases, he twisted the puzzle very, very slowly. He also spent hours solving Rubik’s Cubes. Growing up in suburban Philadelphia, he took college-level math classes at the University of Pennsylvania as a teenager. “The only problem is how do you make sense of it.” Seeing Through the PatternsĮven as a teenager, Collin Burns was thoughtful. ![]() “We have complete access to the code of these systems,” says Aaronson. “We have a very limited and crude ability to look inside of a human brain,” says Aaronson, “and get some idea of at least which regions are active - you know, which ones are burning more glucose.”īut the mind of a large language model - if you can call a multidimensional vector space a mind - is different. In humans, interpretability is an inexact science. “We have complete access to the code … The only problem is how do you make sense of it.” Scott Aaronson ![]() “One thing every single person in AI safety research I’ve talked to agrees is important,” he says, is interpretability - making the “ black box” of AI cognition intelligible to human observers. “The very idea sounds ridiculous.”įor the past year, Aaronson has been on leave from UT to work at OpenAI, the maker of ChatGPT and DALL-E, on AI safety. “Imagine an orangutan trying to build a human-level intelligence that only pursues orangutan values,” says Scott Aaronson, a computer scientist at the University of Texas at Austin. The imperfections of large language models are obvious (and specifically flagged in a pop-up whenever you open ChatGPT, the new Bing, or Google’s Bard AI): these models make up information constantly, leading them to generate content that some have likened to hallucinations, and are liable to reflect the biases in their training data.īut what if there comes a day when the fabrications and errors of tools like ChatGPT and Bing AI are no longer unwitting? What if these tools - which can convincingly produce images, text, and audio in virtually any style - ever actively deceive us? Inside the Black Box Perhaps most importantly, what will happen in the future, as large language models - the technical foundation of today’s cutting-edge AIs - grow more powerful? Presently, we can still train large language models to behave, but only with significant human intervention, as when OpenAI hired scores of contractors in Kenya to manually train ChatGPT to avoid its most inappropriate outputs. Should such tools be regulated, or even banned, as in New York City’s public schools? And is effective regulation even possible, given that much of the research behind these models is so readily available that you can build GPT, one of ChatGPT’s predecessors, in less than two hours on YouTube? But none has ever had storytellers as prolific, or as devoid of moral intuition, as ChatGPT, DALL-E, and the various other generative artificial intelligence tools that have grabbed headlines in recent months.Īs Plato might have been forced to acknowledge - after all, his own works take the form of fictional dialogues - artistic imitation is often necessary to grab an audience’s attention, but with the cost of such imitations reduced to almost nothing by generative AIs, the philosophical questions that once preoccupied Plato have entered the realm of policy. Of course, all societies have storytellers, from West African griots to contemporary TikTokers. Powerful fictions that play with our emotions, he argued, can lead us astray from virtuous behavior - or, even worse, make us believe in a false reality, and act on impulses generated by nothing more than make-believe. For Plato, the ability of Homer’s Iliad to make us envision scenes from the Trojan War and convinced us of their reality was less an artistic achievement than a threat. ![]()
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