I found this an excellent read, which sums up the current state of development of AI computing and looks at some pathways and some possible outcomes. Each chapter has the references at the end so it's easy to follow, and there's a glossary but no index. The writing is nicely done and there are some clear tables that are very helpful.
I think readers will benefit from having read some other books before coming to this one. For instance I had read the mentioned books by Neal Stephenson, Nick Bostrom, Robin Hanson, and more not mentioned, which had covered the issue of Target sending vouchers for pregnancy products to a young teen girl, etc., how AI batches are trained to physical work, or the Go moves in the computer match against the master, rather better and at more length. But you can hunt these up if interested. The topic is AI and this author wants to stick to it. Familiarity with the topic also means you know terms like LLM, IOT and AGI, which are explained briefly, but you don't want to keep flicking pages when they come up again. Maslow's hierarchy of needs is another item which it's assumed you'll know.
We cover issues like hacking, pen testing, accidental data leak, and ethics of security. Also, legal frameworks and loopholes. We go from responsible users to third party chip suppliers to inbred datasets - training an AI on a dataset which is the output of a previous AI, with inherent issues. Bias in race, gender and other areas are looked at and suggestions are provided. Again, not in depth. The author is briefly summarising other papers and books.
Not much space is given to the races between the big name players in the market. Nor how trustworthy the general public finds their firms. From personal experience, I have been sent ads by Google onto my list of emails in my phone, for dating sites where I could meet fat women. I'm a woman, and have been an athlete most of my life, but obviously Google misinterpreted the keenness of my internet reading of science and computing papers and books, and my reading on health and good diet. Now suppose the same ads are sent to the phone of a married man, and his wife sees them. I reported the ads as offensive every time, and got automatically told they didn't contravene policies, until eventually Google got tired of serving me ads for services I was never going to buy. On the good side, other Google products such as Maps, Lens and Gmail are becoming more helpful.
A friend showed me his Facebook phone feed over a lunchtime meal, and it contained large ads for pints of beer of various brands. I said, "They know you're in a pub, they're geolocating you." He turned off the location on his phone. The ads were without regard for the fact that he might be a driver, or returning to work, and he does not drink beer, because he doesn't like it. Given the above story about me, I speculate that he might also have been a pregnant woman or under legal age.
A mere paragraph is given to the environmental cost of AI computing, and it's glossed over and we're told that the benefits outweigh the drawbacks. Do they really? Having spent pages counting the number of ways that an AGI might destroy the world, or destroy all humans, or demand ever more resources, or enslave all humans, etc. we're assured it'll be fine. That's after the list of numerous ways that AI is taking our jobs, leaving only gig work, removing training of young staff so they can't progress to senior posts, taking on creative outputs and peddling lies and deepfakes to targeted electorates. The author does not explain that an AI search as opposed to a standard internet search, uses 6 to 10 times as much energy. And we see that the results are prone to hallucinations, lies, sarcastic or bad answers from a single Reddit post presented as truth. The usage of REEs and precious metals, which could go into other items like MRI scanners and e-bikes, and trashpiles of chips, motherboards and GPUs from which metals are not recovered... this will make it necessary to mine the asteroids, not for us, but for AI demands.
Glossary p. 294 - 299 in my e-ARC. This book will be useful to those in the computer industry, tech journalists, students, and business people generally. A good point is that after each chapter we get a box on the bottom line, the big picture, and another on leadership actions. This might include providing opt in or opt out material to employees or users, regular checks that data is secure, collaborating with others and with universities. No photos - I thought a few photos of datacentres, AIs being trained on physical tasks, and some of the major names in the field, would be helpful to students. Largely names are absent and general ethics discussions are prominent. But it'll all work out fine. Maybe that's what an AI would say if it wrote this book. I can but speculate.
I read an e-ARC from Net Galley. This is an unbiased review by a live human.