Scan barcode
edriessen's review against another edition
5.0
This is a good book. It offers a good introduction into algorithms in various fields. It shines a light on both the positives and the negatives, and how we could improve on our use of algorithms.
(If you already have a lot experience in working with ML/AI/algorithms/magic in various fields, then it might be a bit shallow.)
(If you already have a lot experience in working with ML/AI/algorithms/magic in various fields, then it might be a bit shallow.)
chaptersnchatter's review against another edition
4.0
An excellent read for people without a technology background. Hannah elegantly explains technology without bombarding you with jargon.
I have a degree in computer science so was already aware of how all the algorithms work. I was also convinced that we need regulation for tech. But I still don’t regret reading this because
1. The way Hannah words things for a non-tech audience is simply outstanding! I was particularly blown away by her explanation of the Bayes Theorem
2. I always knew algorithms aren’t perfect but her human case studies made me realise the gravity of these seemingly “occasional” errors. We, as a community of (future) creators of some of these technologies, need to be extremely considerate of the cost of them going wrong.
I have a degree in computer science so was already aware of how all the algorithms work. I was also convinced that we need regulation for tech. But I still don’t regret reading this because
1. The way Hannah words things for a non-tech audience is simply outstanding! I was particularly blown away by her explanation of the Bayes Theorem
2. I always knew algorithms aren’t perfect but her human case studies made me realise the gravity of these seemingly “occasional” errors. We, as a community of (future) creators of some of these technologies, need to be extremely considerate of the cost of them going wrong.
gj377's review against another edition
4.0
I really enjoyed this! Fry writes an incredibly accessible account of how algorithms are already affecting our lives and the world we live in.
Split into different section - crime, justice, art, medicine etc - Fry details the ways in which algorithms are used, and the differing consequences of a naive reliance on technology that's often not wholly understood. Along the way, Fry explains the machine learning concepts that lie behind algorithmic construction and design, detailing them in an extremely easy to read, but not too simplistic, manner - Fry's expertise is readily apparent in how accessible she makes it all.
This book really is exactly what I love in non-fiction books. Well-written, without being too technically dense, but still well-referenced and fairly balanced. This book is split into digestible sections that nevertheless flow into each other organically. As someone who works in machine learning without having studied it, I liked learning a bit about the science as well. I could have done with it being a bit more in-depth, but that's a personal preference.
In an age where algorithms are becoming inescapable, you could do a lot worse than reading Fry's account of where they can go right, and where they can do wrong. Read it now, before it's out of date!
Split into different section - crime, justice, art, medicine etc - Fry details the ways in which algorithms are used, and the differing consequences of a naive reliance on technology that's often not wholly understood. Along the way, Fry explains the machine learning concepts that lie behind algorithmic construction and design, detailing them in an extremely easy to read, but not too simplistic, manner - Fry's expertise is readily apparent in how accessible she makes it all.
This book really is exactly what I love in non-fiction books. Well-written, without being too technically dense, but still well-referenced and fairly balanced. This book is split into digestible sections that nevertheless flow into each other organically. As someone who works in machine learning without having studied it, I liked learning a bit about the science as well. I could have done with it being a bit more in-depth, but that's a personal preference.
In an age where algorithms are becoming inescapable, you could do a lot worse than reading Fry's account of where they can go right, and where they can do wrong. Read it now, before it's out of date!