A word of warning: I'm not a machine learning practitioner and not even mathematically inclined. I am merely an average person with a (reasonable) degree of culture (I suppose I classify as a sociologist) looking out to understand the world around me a little better.
Yet I loved this book, it opened my eyes on a world I suspected existed somewhere in the depths of my computer or when I did a Google search but that I never understood. If you are afraid to be engulfed in equations, don't be. The author prefers to use allegories and is very good at giving simple explanations, making everything (almost) crystal clear.
What you get is a comprehensive overview of where machine learning is going. This is hugely important, considering the sometimes disturbing news you get in the media - not just from Snowden but also from "neurotechnologists" who guide political campaigns by embedding cameras in ads, cameras that detect the viewers' reactions and then adjust the campaign in function of these reactions.
Perhaps my only quarrel with this book - but it does not detract from its excellence and the five stars I gave it - is the philosophical position taken by the author. I don't quite share his optimism about our robotic future. And this for 2 reasons:
One, the connection between learning algorithms and data. Domingos does note at the outset: "...the more data they [the learners] have, the more intricate the algorithms can be." So without "big data", you don't get "good" learning algorithms - the "bigger" the data, the better the algorithm. Or as Domingos writes, "the more data we have, the more we can learn". True enough. But what about the quality and size of the big data? What if the data is error-filled and we're not aware of it? Can machine learning be aware of something their human masters are not? On what basis? The algorithms are taught to deal with an imperfect world and draw the most likely conclusions, where "most likely" is highly subjective. Or at least, it is "highly subjective" in my opinion and I realize that it is only one opinion and not necessarily one shared by the author.
Two, the connection between you as you are and an expanded "digital you": a "model" of who you are, your work experience, your tastes, a model that the algorithm has learned - and thanks to algorithms, you will be able to do more things and faster than ever before. Domingos describes an extraordinary future where, for example, in your LinkedIn account, "you'll immediately interview for every job in the universe that remotely fits your parameters (profession, location, pay, etc) LinkedIn will respond on the spot with a ranked list of the best prospects, and out of those, you'll pick the first company that you want to have a chat with. Same with dating: your model will go on millions of dates so you don't have to..."
Big time-saver obviously. But it comes at a cost: you have to give your parameters (stuff about your work, your likes and dislikes) to the algorithms. Ye who go digital, leave behind any notion of privacy...So users of this algorithmic landscape will have few shaded areas in which to hide.
But for me, privacy concerns aside (and I'm not that concerned, I have nothing to hide), there is yet another matter that I find more worrisome. Domingos (on p.283) tells us he is confident that the future can only get better: "In fact, it's the systems that have a slight edge in serving us better that will, generation after generation, multiply and take over the gene pool." Then he adds: "Of course, if we're so foolish as to deliberately program a computer to put itself above us, then maybe we'll get what we deserve".
Indeed. That is precisely my worry: can we be sure that there won't be a Doctor Evil who will do so? Can we be sure that there won't be an Apprentice Sorcerer who might end up doing this even if unintentionally? A mistake can happen...
So yes, I'm deeply worried about this algorithmic future and I don't share the author's unflagging optimism. But that doesn't mean it's a book you shouldn't read. On the contrary, it's a must read precisely because it raises all these fundamental questions about the future of humanity. And it is an easy read even for the non-cognoscenti like myself, I highly recommend the introductory chapters, and if you get bogged down in the middle with all the technicalities, no fear, skip to the last two chapters, they are well worth reading!
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Top reviews from other countries
SimpleSimon
Poorly edited but very valuable book
Reviewed in the United Kingdom on December 11, 2020
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Reviewed in Germany on September 6, 2020Quique
Visión global del machine learning, no está mal escrito
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