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Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (English Edition) eBook Kindle
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Descrição do produto
'A manual for the 21st-century citizen ... accessible, refreshingly critical, relevant and urgent' Federica Cocco, Financial Times
'O'Neil's book offers a frightening look at how algorithms are increasingly regulating people ... masterly' Clay Shirky, The New York Times Book Review
'Opens the curtain on algorithms that exploit people and distort the truth while posing as neutral mathematical tools. This book is wise, fierce, and desperately necessary' Jordan Ellenberg, author of How Not to Be Wrong
'A vital crash course in why we must interrogate the systems around us and demand better' Cory Doctorow
'Cathy O'Neil has a story to tell, and it is a story about you ... what she reveals is fascinating' Danny Dorling, Times Higher Education--Este texto se refere à uma edição alternativa kindle_edition
Sobre o Autor
Detalhes do produto
- Tamanho do arquivo : 3086 KB
- Dicas de vocabulário : Habilitado
- Editora : Crown; Reprint edição (6 setembro 2016)
- Número de páginas : 254 páginas
- Configuração de fonte : Habilitado
- Leitura de texto : Habilitado
- X-Ray : Habilitado
- Idioma: : Inglês
- ASIN : B019B6VCLO
- Ranking dos mais vendidos: Nº 4,488 em Loja Kindle (Conheça o Top 100 na categoria Loja Kindle)
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The author passion for the subject can be felt through the book and although enjoyed it did leave me feeling a little saddened to see so many examples of poorly implemented analytics.
The book would have benefitted from a broader perspective and also included success stories to show how data can also be a force for good to simplify and improve our lives. At the end of the day these are tools and it’s how people use them that can produce these WMD’s.
Also reminds us of the need to educate the wider community on how data is used and that data asset needs to benefit everyone.
If you are looking for a really in depth text, this is not it. This is meant for everyone and in that respect it is a good book. When I started reading it I thought perhaps it could do with the Michael Lewis touch (Flashboys, Moneyball etc) but when I finished I thought not. It looks like this is the way the future looks, and it is not pretty the way it is right now. Let's hope that the technology and scale leads to greater beneifts to all, and not mass categorisation with a dumb central machine.
The book covers several different fields, all of them tied by the common theme of how the lack of understanding of algorithms, sometimes unintentionally, sometimes for personal gain, leads to entirely false evaluations of phenomena, based on spurious correlations or too simplistic approaches, that quite too often provide false bases on top of which important, but entirely unsubstantiated decisions, are already being made.
I strongly advise anyone, but in particular people working in IT, to read this book since it is important that more people are made aware of how little their choices, and who they really are, may matter in their lives, once their data is fed to the algorithms most companies use nowadays.
IT people can, and should, use this knowledge to push for a review of how people data is used to make decisions that affect people's lives.