Scan barcode
A review by gj377
Hello World: How to be Human in the Age of the Machine by Hannah Fry
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 Read it now, before it's out of date!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!