a book
Humans Need Not Apply
Jerry Kaplan · 2015 · 241 pages
Selected as one of the 10 best science and technology books of 2015 by The Economist
After billions of dollars and fifty years of effort, researchers are finally cracking the code on artificial intelligence. As society stands on the cusp of unprecedented change, Jerry Kaplan unpacks the latest advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure -- but as Kaplan warns, the transition may be protracted and brutal unless we address the two great scourges of the modern developed world: volatile labor markets and income inequality. He proposes innovative, free-market adjustments to our economic system and social policies to avoid an extended period of social turmoil. His timely and accessible analysis of the promise and perils of artificial intelligence is a must-read for business leaders and policy makers on both sides of the aisle.
recommended by 3 people
sourced from public statements
Andrej Karpathy
“This book provides a decent exploration of the future of automation. The first part of the book talks about AI/Machine Learning. This may have been a decent intro for someone completely new to the field, but for someone very much inside the field it was a little frustrating to read because of explanations that I think confused concepts in artificial intelligence, sometimes for example using the terms "machine learning" and "neural networks" interchangeably. I was also put off by some silly examples of what the future looks like, such as "Trying on an outfit? Instead of asking a sales assistant if you look nice, why not take a snapshot of yourself and seek crowdsourced opinions?". To me, these silly and quite speculative examples of small use cases give off too much of a singularity hype hype vibe. The later part of the book is where things finally take off and the book goes into some social-economical repercussions of automation and the likely more dramatic income inequality. This is mostly why I got the book and I was looking forward to these parts, but unfortunately the book dives in quite quickly and became a bit of a stream-of-consciousness that assumed quite a lot of knowledge of economics, law, etc. I did not have enough background to appreciate entire chapters (e.g. surrounding the proposed job mortgage concept and its merits) and went from being bored in the first half to mostly confused in the second half. I think these chapters should have been expanded, introduced more slowly, put in wider context, and made more concrete with more frequent examples.”
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