21 Lessons for the 21st Century

I have now read all three of Harari's books. And I found this to be the most interesting and infuriating. My biggest critique remains the same across all three books - he can see nuance in the places that are convenient (i.e., economy, technology) and simplicity in the places that are inconvenient to his arguments (i.e., religion). I think the kind of work Harari has done in illuminating big history and getting people to think deeply about global trends is commendable. I only hope that people read this as part of a larger conversation and not an entire worldview perfectly prepackaged. One should use his writings as a springboard for their own inquiries and analysis.

Note - I read this book a number of months ago and currently do not have the book in front of me for this review. I will update the review when I have a chance to look over the book.

Harari's first two powerhouses: Sapiens and Homo Deus were two books I thoroughly enjoyed. This one, at least to me, missed the mark a little - although I'm struggling to find out why. Sapiens was almost an archetypal story, which is where it gained its power and prominence. Homo Deus, as I stated in my review of it, fell a little flat in the early portions but made up in the discussions of a post-liberal democracy technological future.

Where did 21 lessons go wrong? Why was it wrong? Well. Much of it was perhaps talking about things that are obvious, but could not be considered archetypal. Thus I was not hit in the face with the realisations and acceptance of every page turn like Sapiens. It was more of an "I know this, we struggle with this, because this is fundamentally a Value, and it's not a thing we can 'solve'" situation. Is it therefore that Harari's perceptions of these value questions were not as enlightening as the eye opening reflections he has on the subconscious portions of humanity a la Sapiens? Or, is this book a bunch of off cuts that didn't make it into the previous two master works? Since I couldn't differentiate these possibilities through inference, it made me feel that this was more and more a coattails product, however masterfully written & edited.

In addition, I strongly recommend you read Bill Gate's review here on Goodreads. His expertise with global problems and how to approach them, not just theoretically, but practically is certainly up there with the best we have. Some of his critiques resonate with my struggles with this book, and I'm not as qualified as he to tell you about them.

After the first couple of chapters, I was ready to give this book 1 or 2 stars. There was a lot of talk about artificial intelligence, machine learning and big data - all topics that are familiar to me because of my profession as a software engineer. I got the impression that the author did not fully understand what he was writing about. The narrative in those chapters is pervaded by pessimism, and paints a world where people have no jobs, and all their movements and thoughts are controlled and predicted by "the algorithm", an ominous presence that nobody really understands. In this future reality, according to the author, people would become irrelevant and would be completely dominated by machines and by a biologically-enhanced human elite. But here's a big inconsistency in this narrative: if people become so irrelevant, why is it so important for algorithms to be able to know and predict people? In other words, why should an "elite" develop algorithms that study people, if people are so irrelevant? So much for irrelevance - the "elite" still wants a lot from the rest of humanity! It sounds to me like people are just as relevant as they are today, or else "the algorithm" and the marketing machines would not give people so much attention.

Besides, nobody really knows what is going to happen with AI. How do we know that the current trend of deep learning techniques will keep evolving and will reach such levels of sophistication that will push people into irrelevance? Deep learning is just a statistical method that is enhanced by today's powerful CPUs and GPUs, but how do we know its capabilities will not plateau in the future? Today's neural networks are great at specific tasks, but they are absolutely nowhere near a position where they can match biological intelligence when it comes to things such as having a morality or conscience (mostly because we don't even know how it works with us in the first place). On the other hand, these algorithms do have the potential to enhance our lives by aiding us in mundane tasks, or in tasks where our feelings might be counter-productive (e.g. driving).

Harari only writes about pessimistic scenarios that are borderline dystopian - he should consider more optimistic ones instead. There's plenty that AI and big data can help us with.

The next few chapters were a bit better, but overall felt a bit disconnected. There was a lot of jumping here and there, and at this stage I felt the book lacked a coherent structure.

Luckily, Harari writes very well. His writing style is engaging and clear and it kept me reading despite my disagreements on the book's content and apparent lack of a cohesive narrative.

Well, I am glad I kept reading, because the end of the book is much better - especially parts 4 and 5. I guess this is Harari's familiar territory: here, he is able to combine his deep knowledge in history and sociology with clear insights about contemporary society and about human beings. The 20th chapter, "Meaning", was probably the best of the entire book.