Kirjahaku

How Big Tech is taking advantage of us, how AI is making it worse, and how we can create a thriving, AI-positive world. On balance, will AI help humanity or harm it? AI could revolutionize science, medicine, and technology, and deliver us a world of abundance and better health. Or it could be a disaster, leading to the downfall of democracy, or even our extinction. In Taming Silicon Valley, Gary Marcus, one of the most trusted voices in AI, explains that we still have a choice. And that the decisions we make now about AI will shape our next century. In this short but powerful manifesto, Marcus explains how Big Tech is taking advantage of us, how AI could make things much worse, and, most importantly, what we can do to safeguard our democracy, our society, and our future. Marcus explains the potential and potential risks of AI in the clearest possible terms and how Big Tech has effectively captured policymakers. He begins by laying out what is lacking in current AI, what the greatest risks of AI are, and how Big Tech has been playing both the public and the government, before digging into why the US government has thus far been ineffective at reining in Big Tech. He then offers real tools for readers, including eight suggestions for what a coherent AI policy should like from data rights to layered AI oversight to meaningful tax reform and closes with how ordinary citizens can push for what is so desperately needed. Taming Silicon Valley is both a primer on how AI has gotten to its problematic present state and a book of activism in the tradition of Abbie Hoffman s Steal This Book and Thomas Paine s Common Sense. It is a deeply important book for our perilous historical moment that every concerned citizen must read.

In The Algebraic Mind, Gary Marcus attempts to integrate two theories about how the mind works, one that says that the mind is a computer-like manipulator of symbols, and another that says that the mind is a large network of neurons working together in parallel. Resisting the conventional wisdom that says that if the mind is a large neural network it cannot simultaneously be a manipulator of symbols, Marcus outlines a variety of ways in which neural systems could be organized so as to manipulate symbols, and he shows why such systems are more likely to provide an adequate substrate for language and cognition than neural systems that are inconsistent with the manipulation of symbols. Concluding with a discussion of how a neurally realized system of symbol-manipulation could have evolved and how such a system could unfold developmentally within the womb, Marcus helps to set the future agenda of cognitive neuroscience.