Book review: “Architects of Intelligence”

Architects of Intelligence is a series of interviews with a grab bag of prominent researchers and entrepreneurs in AI. The roster is the star attraction – most of the interviewees are pretty famous, ranging from neural network pioneers like Geoffrey Hinton to “classic” AI experts like Stuart Russell. Most of them are excellent communicators, and this shines through in their responses. Unfortunately, the quality of the questions leaves a lot to be desired. Martin Ford is a business writer, and he’s more concerned about the impact of AI on the labor market than on how it works and whether it’s safe. I’m not saying that economics isn’t important, but asking Judea Pearl about whether robots will take our jobs is a bit like asking Anthony Fauci about the economic impact of people taking time off work to get their covid vaccines. It’s especially frustrating when the interviewee makes some interesting point about their research, and Ford completely drops the thread to ask about an unrelated topic outside their field of expertise. 

So, you can probably find better interviews with the people featured in this book elsewhere. But in spite of this, I still found the book surprisingly valuable. Why? Because while each interview is unremarkable in isolation, the collection of them shows a fascinating diversity of viewpoints. Ford asks everyone a core set of questions, so we get to see the contrast between researchers in stark relief. Some of the experts are worried about the safety of increasingly sophisticated AI agents; others find the idea of safety concerns so ridiculous that they refuse to discuss it. Deep neural networks are sufficient for human-level AI, or need to be supplemented with some other techniques, or are on the wrong track entirely. AI will worsen inequality, or even the playing field, or neither (because humanity will merge with the AI and transcend these kinds of petty concerns). There’s no shortage of very hot takes. It’s impossible to come away from reading these interviews thinking that there’s consensus about much of anything in AI research.

I also found going through this book to be helpful in building up my mental model of what kinds of research are done by which labs and companies. This knowledge does accrue naturally as you go to talks and read papers, but among all the details it’s easy to lose sight of the big picture. I’ve found myself returning to my notes from Architects of Intelligence many times when I come across a new quote or idea from one of the interviewees, and each time I’ve been grateful for the extra context. Wikipedia is a fantastic resource, but it isn’t a substitute for having a curated set of the most interesting/relevant/useful things you’ve learned about someone. These interviews are a great source of interesting facts about prominent AI researchers and their views.

I hold out hope that someday, someone will put together a similar project with better interviews and more interesting questions. In the meantime, I recommend this book (I guess!).

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