Hannah Fry: Hello World (2019, Transworld Publishers Limited)
320 pages
English language
Published Dec. 4, 2019 by Transworld Publishers Limited.
"Hello World takes us on a tour through the good, the bad, and the downright ugly of the algorithms that surround us on a daily basis. Mathematician Hannah Fry reveals their inner workings, showing us how algorithms are written and implemented, and demonstrates the ways in which human bias can literally be written into the code. By weaving in relatable, real world stories with accessible explanations of the underlying mathematics that power algorithms, Hello World helps us to determine their power, expose their limitations, and examine whether they really are improvement on the human systems they replace."--
"Hello World takes us on a tour through the good, the bad, and the downright ugly of the algorithms that surround us on a daily basis. Mathematician Hannah Fry reveals their inner workings, showing us how algorithms are written and implemented, and demonstrates the ways in which human bias can literally be written into the code. By weaving in relatable, real world stories with accessible explanations of the underlying mathematics that power algorithms, Hello World helps us to determine their power, expose their limitations, and examine whether they really are improvement on the human systems they replace."--
I enjoyed reading this book. It helped me get a grasp of some of the ways that algorithms are used in the world and some of the downsides to them. It helped me understand algorithms better.
A very clear exploration of what algorithms can and cannot do. And the answer is "it's complicated" however, despite the issues with algorithms, we shouldn't kid ourselves that human decision-making is flawless. Algorithms are biased but so are human beings. The goal should therefore be to make algorithms more transparent and assistant to human decisions rather than abdicate decision-making to algorithms uncritically.
I especially liked this bit: "Whenever you see a story about an algorithm, see if you can swap out any of the buzzwords, like ‘machine learning’, ‘artificial intelligence’ and ‘neural network’, and swap in the word ‘magic’. Does everything still make grammatical sense? Is any of the meaning lost? If not, I’d be worried that it’s all nonsense.".
This is a book that gives a lot to think about that is also pleasant to read and full of insightful examples.
A very clear exploration of what algorithms can and cannot do. And the answer is "it's complicated" however, despite the issues with algorithms, we shouldn't kid ourselves that human decision-making is flawless. Algorithms are biased but so are human beings. The goal should therefore be to make algorithms more transparent and assistant to human decisions rather than abdicate decision-making to algorithms uncritically.
I especially liked this bit: "Whenever you see a story about an algorithm, see if you can swap out any of the buzzwords, like ‘machine learning’, ‘artificial intelligence’ and ‘neural network’, and swap in the word ‘magic’. Does everything still make grammatical sense? Is any of the meaning lost? If not, I’d be worried that it’s all nonsense.".
This is a book that gives a lot to think about that is also pleasant to read and full of insightful examples.
The book shows effectively the chances and flaws about using machine learning in disciplines such as in crime or art. It is great because it isn’t overly critical nor is it praising them too much. It is shortly - realistic and makes one think about the future.
