Ratings21
Average rating3.6
It was not what I expected, the book is very opinionated and biased against AI and machines. I didn’t expect her to be completely neutral, that would be really hard for any of us being humans but I did expect her to be a bit more fair given the fact she decided to write about this topic. It is not very technical but more of a moral reflection about modern world’s algorithmic tools, and as a consequence it is more appealing to people that share some common background with the author.
The book is divided in seven field chapters: Power, Data, Justice, Medicine, Cars, Crime, Art, and a conclusion chapter to close. I think there is a lot of overlapping among some of the chapters and others may not be as relevant. Through the book the author presents a lot of factual information about news and studies related to the algorithms in that field, but most of those are not new but the same ones that you can find in other popular books about algorithmic biases(I am thinking in Weapons of Math Destruction here).
I was really disappointed by the last chapters, and particularly the conclusion which I would summarize as a conservative call to regulate algorithms for the sake of humanity, understanding humanity not as a scientific feature but a spiritual one. Still I am trying to be fair, since the opinion part should be assumed from the How to be human in the age of the machine part in the title.
Nevertheless, and precisely because it is this lack of empathy she criticizes from algorithm makers and adopters, she should have tried to think that not all human share the same background and experiences regarding this topic are vastly influenced by geography, which is not just development indexes and access to the technologies but also the culture and social norms used to assess the outcome (just to be crystal clear, I don’t think algorithms are fair, I think humans are at least as unfair as algorithms because they are designed by them, a topic that is briefly discussed in the book but apparently vanished from the conclusions).
I won’t say the book is bad, most of it is interesting and well written, but I disagree with the reviews, and wouldn’t call it a science book or say it explains AI, machine learning or complicated algorithms. Although I enjoy it I would have not picked it, or said another way, I would have spent my time reading another book. I’ll let here two quotes that I hope will help you decide if it is the book for you.
But for me, true art can’t be created by accident. There are boundaries to the reach of algorithms. Limits to what can be quantified. Among all of the staggeringly impressive, mind-boggling things that data and statistics can tell me, how it feels to be human isn’t one of them.
The supermarket algorithm that robs a teenage girl of the chance to tell her father that she’s fallen pregnant.