In an age of breathless predictions and sky-high valuations, cognitive scientist Gary Marcus has emerged as one of the best-known skeptics of generative artificial intelligence (AI). In fact, he recently wrote a book about his concerns, Taming Silicon Valley, in which he made the case that "we are not on the best path right now, either technically or morally." Marcus--who has spent his career examining both natural and artificial intelligence--explained his reasoning in a recent conversation with Leah Hoffmann. You've written about neural networks in everything from your 1992 monograph on language acquisition to, most recently, your book Taming Silicon Valley. Your thoughts about how AI companies and policies fall short have been well covered in your U.S. Senate testimony and other outlets (including your own Substack).

Elon Musk has said he wants to make Twitter "the most accurate source of information in the world." I am not convinced that he means it, but whether he does or not, he's going to have to work on the problem; a lot of advertisers have already made that pretty clear. If he does nothing, they are out. And Musk has continued to tweet in ways that seem to indicate that he is generally on board with some kind of content moderation. The tech journalist Kara Swisher has speculated that Musk wants AI to help; on Twitter she wrote, rather plausibly, that Musk "is hoping to build an AI system that replaces [fired moderators] that will not work well now but will presumably get better."

To talk about Reasoning, it's important to understand how we got here. This article covers what I call the pre-history of Classical AI -- those parts of the story that happened before the invention of modern computers (pre 1950s) but are crucial to understanding why we believe that AI is possible. This is part 2 in a series on Reasoning. Like most things, the very beginnings of classical AI is rooted in philosophy, and starts in the ancient world (the Greeks, Indians, and Chinese all had some early forms of logic). But, as I'm not a masochist we start in more contemporary times with two big ideas that lay the foundation for modern AI: The development of logic was humanity's first great attempt at mechanizing intelligence, and the basis for modern logic lies with George Boole, Charles Pierce, and Gottlob Frege.

Since the 1950s, artificial intelligence has repeatedly overpromised and underdelivered. While recent years have seen incredible leaps thanks to deep learning, AI today is still narrow: it's fragile in the face of attacks, can't generalize to adapt to changing environments, and is riddled with bias. All these challenges make the technology difficult to trust and limit its potential to benefit society. On March 26 at MIT Technology Review's annual EmTech Digital event, two prominent figures in AI took to the virtual stage to debate how the field might overcome these issues. Gary Marcus, professor emeritus at NYU and the founder and CEO of Robust.AI, is a well-known critic of deep learning.

I remember a time, before the Web, when you would look for relevant academic papers by reading large books with tiny fonts that would list all relevant work in a given area published in a given year. Of course, you could have just gone to the shelves and checked the research articles themselves but, by for a slow human being, this would have been just too time consuming. These large volumes contained nothing by "metadata": lists of article titles, authors, keywords… They were tremendously valuable to the researchers. One of the earliest applications of computers was to help manage document collections. In this sense, the Web and Google are very naturally applications for computers.

Reasoning using expressive symbolic representations is a central theme of AI research, yet there are surprisingly few deployed games, even within the AIIDE research community, that use this sort of “classical” AI. This is partly due to practical and methodological issues, but also due to fundamental mismatches between current game genres and classical AI systems. I will argue that if we want to build games that leverage high-end classical AI techniques like commonsense reasoning and natural language processing, we will also have to develop new game genres and mechanics that better exploit those capabilities. I will also present a design sketch of a game that explores potential game mechanics for classical AI.

"How We Know Universals: The Perception Their first paper made many intellectual waves--which are still spreading, 50 years later. They had claimed that the truth or falsity of any (computable) proposition could, in with AI, for it's difficult to say just principle, be computed by a simple type of The future of psychology, they good a date as any, however, is 1943--almost said, consisted of the design of various sorts exactly half a century ago. This In that year, Warren McCulloch (a psychiatrist, novel methodology, and the nascent technology cybernetician, philosopher, and poet) associated with it, promised to show just and Walter Pitts (a research student in mathematics) how mind is grounded in mechanism. Much of this was "logical" in nature result was a heady brew, which explicitly and developed into what's known as classical, promised to revolutionize psychology and or symbolic, AI. But some was what is nowadays philosophy--and which, in the event, revolutionized called connectionist, studying networks technology too. In the late 1980s, however, it McCulloch and Pitts' paper ("A Logical Calculus blossomed--hitting the newsstands with of the Ideas Immanent in Nervous rash promises of "brainlike" computers just Activity") concentrated on how propositions around the corner. But both these forms of AI expressible in logic could be computed by share the same historical roots. Those nets consisted of So much for pedigree. But does a mere halfcentury cells passing inhibitory and excitatory messages of work count as a pedigree? Might it between them and acting as what computer rather be a mere blip, an unfortunate academic scientists (soon afterwards) called "and-mutation with no real intellectual fitness?