As the tech industry hype cycle continues to churn my in-box every day, I find myself reflecting on the meme du jour of "artificial intelligence." My initial reaction to over-hyped terms is to resist giving them more credence than they may deserve. The seminal meeting attracted a small group of scientists met to discuss new ideas and the term "artificial intelligence" was first coined by American academic John McCarthy. A few years back my alma mater UCLA was designing a new graduate program to accommodate the accelerating interest in what people were calling data science. For a detailed history of the field of AI, please check out the compelling general audience title "Artificial Intelligence: A Guide for Thinking Humans," by Melanie Mitchell, CS professor at Portland State.

Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI's turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent―really―are the best AI programs? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us?

The Pulitzer Prize-winning book Gödel, Escher, Bach inspired legions of computer scientists in 1979, but few were as inspired as Melanie Mitchell. After reading the 777-page tome, Mitchell, a high school math teacher in New York, decided she "needed to be" in artificial intelligence. She soon tracked down the book's author, AI researcher Douglas Hofstadter, and talked him into giving her an internship. She had only taken a handful of computer science courses at the time, but he seemed impressed with her chutzpah and unconcerned about her academic credentials. Mitchell prepared a "last-minute" graduate school application and joined Hofstadter's new lab at the University of Michigan in Ann Arbor.

Melanie Mitchell, a professor of complexity at the Santa Fe Institute and a professor of computer science at Portland State University, acknowledges the powerful accomplishments of "black box" deep learning neural networks. But she also thinks that artificial intelligence research would benefit most from getting back to its roots and exchanging more ideas with research into cognition in living brains. This week, she speaks with host Steven Strogatz about the challenges of building a general intelligence, why we should think about the road rage of self-driving cars, and why AIs might need good parents. Listen on Apple Podcasts, Spotify, Android, TuneIn, Stitcher, Google Podcasts, or your favorite podcasting app, or you can stream it from Quanta. Melanie Mitchell: You know, you give it a new face, say, and it gives you an answer: "Oh, this is Melanie." And you say, "Why did you think that?" "Well, because of these billions of numbers that I just computed." Steve Strogatz [narration]: From Quanta Magazine, this is The Joy of x. Mitchell: And I'm like, "Well, I can't under-- Can you say more?" And they were like, "No, we can't say more." Steve Strogatz: Isn't that unnerving, that it's this great virtuoso at these narrow tasks, but it has no ability to explain itself? Strogatz: Melanie Mitchell is a computer scientist who is particularly interested in artificial intelligence. Her take on the subject, though, is quite a bit different from a lot of her colleagues' nowadays. She actually thinks that the subject may be adrift and asking the wrong questions. And in particular, she thinks that it would be better if artificial intelligence could get back to its roots in making stronger ties with fields like cognitive science and psychology, because these artificially intelligent computers, while they're smart, they are smart in a way that is so different from human intelligence. Melanie's been intrigued by these questions for really quite a long time, but her journey got started in earnest when she stumbled across a really big and really important book that was published in 1979.

The following is a review of the book Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell (Twitter here). Artificial Intelligence, along with Big Data, Machine Learning, BlockChain and Internet of Things is one of the catch-phrases or buzzwords of our century. While everybody speaks about it, very few people know what it actually is, how it works, its limitations and its possibilities. In Artificial Intelligence: a guide for thinking humans, award winning author Melanie Mitchell, comprehensively explains the history of AI, the recent amazing achievements it has reached, its future, and the fears around it. The book is an incredible overview of Artificial Intelligence and its surrounding world, telling stories about AI with a human touch, and a captivating engaging discurse.

Over the past two years, we've seen the release of many books that provide deep insights about the fundamental concepts, technical process, and applications of artificial intelligence. This list highlights books authored by renowned computer scientists and practitioners who are entrenched in the AI industry. No matter you are a researcher, an engineer, or a business professional in the AI/ML domain, your are bound to find a few interesting books to add to your reading list this year! In this book, professors at New York University Gary Marcus and Ernest Davis explain the technological and theoretical gap between creating successful AI which is constrained to a fixed set of rules (or a fixed environment), and creating successful AI which can effectively interact with the complexities and intricacies of an open world. This book is for researchers and entrepreneurs who want to make practical predictions on the immediate future of AI. Gary Marcus is a Professor of Psychology and Neural Science and CEO of Robust.AI, and Ernest Davis is a Professor of Computer Science.

"Mitchell knows what she's talking about. Artificial Intelligence has significantly improved my knowledge when it comes to automation technology, [but] the greater benefit is that it has also enhanced my appreciation for the complexity and ineffability of human cognition."―John Warner, Chicago Tribune "Without shying away from technical details, this survey provides an accessible course in neural networks, computer vision, and natural-language processing, and asks whether the quest to produce an abstracted, general intelligence is worrisome . . . Mitchell's view is a reassuring one." AI isn't for the faint of heart, and neither is this book for nonscientists . . .

Melanie Mitchell is the Davis Professor of Complexity at the Santa Fe Institute, and Professor of Computer Science at Portland State University. Prof. Mitchell is the author of a number of interesting books such as Complexity: A Guided Tour and Artificial Intelligence: A Guide for Thinking Humans. One interesting detail of her academic bio is that Douglas Hofstadter was her Ph.D. supervisor. During this 90 min interview with Melanie Mitchell, we cover a variety of interesting topics such as: how she started in physics, went into math, and ended up in Computer Science; how Douglas Hofstadter became her Ph.D. supervisor; the biggest issues that humanity is facing today; my predictions of the biggest challenges of the next 100 days of the COVID19 pandemic; how to remain hopeful when it is hard to be optimistic; the problems in defining AI, thinking and human; the Turing Test and Ray Kurzweil's bet with Mitchell Kapor; the Technological Singularity and its possible timeline; the Fallacy of First Steps and the Collapse of AI; Marvin Minsky's denial of progress towards AGI; Hofstadter's fear that intelligence may turn out to be a set of "cheap tricks"; the importance of learning and interacting with the world; the [hard] problem of consciousness; why it is us who need to sort ourselves out and not rely on God or AI; complexity, the future and why living in "Uncertain Times" is an unprecented opportunity. Intelligence is a very complex phenomenon and we should study it as such.

Starfleet's star android, Lt. Commander Data, has been enlisted by his renegade android "brother" Lore to join a rebellion against humankind -- much to the consternation of Jean-Luc Picard, captain of the USS Enterprise. "The reign of biological life-forms is coming to an end," Lore tells Picard. "You, Picard, and those like you, are obsolete." In real life, the era of smart machines has already arrived. They haven't completely taken over the world yet, but they're off to a good start.

Melanie Mitchell is the Davis Professor of Complexity at the Santa Fe Institute, and Professor of Computer Science at Portland State University. Prof. Mitchell is the author of a number of interesting books such as Complexity: A Guided Tour and Artificial Intelligence: A Guide for Thinking Humans. One interesting detail of her academic bio is that Douglas Hofstadter was her Ph.D. supervisor. During this 90 min interview with Melanie Mitchell, we cover a variety of interesting topics such as: how she started in physics, went into math, and ended up in Computer Science; how Douglas Hofstadter became her Ph.D. supervisor; the biggest issues that humanity is facing today; my predictions of the biggest challenges of the next 100 days of the COVID19 pandemic; how to remain hopeful when it is hard to be optimistic; the problems in defining AI, thinking and human; the Turing Test and Ray Kurzweil's bet with Mitchell Kapor; the Technological Singularity and its possible timeline; the Fallacy of First Steps and the Collapse of AI; Marvin Minsky's denial of progress towards AGI; Hofstadter's fear that intelligence may turn out to be a set of "cheap tricks"; the importance of learning and interacting with the world; the [hard] problem of consciousness; why it is us who need to sort ourselves out and not rely on God or AI; complexity, the future and why living in "Uncertain Times" is an unprecented opportunity. Intelligence is a very complex phenomenon and we should study it as such.