Weapons of Math Destruction

Weapons of Math Destruction pdf epub mobi txt 電子書 下載2025

Catherine ("Cathy") Helen O'Neil is an American mathematician and the author of the blog mathbabe.org and several books on data science, including Weapons of Math Destruction. She was the former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism, Tow Center and was employed as Data Science Consultant at Johnson Research Labs.

She lives in New York City and is active in the Occupy movement.

出版者:Crown
作者:Cathy O'Neil
出品人:
頁數:272
译者:
出版時間:2016-9-6
價格:USD 26.00
裝幀:Hardcover
isbn號碼:9780553418811
叢書系列:
圖書標籤:
  • 大數據 
  • 社會學 
  • 美國 
  • 數字社會學 
  • inequality 
  • 數學 
  • 社會 
  • 政治科學 
  •  
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

A former Wall Street quant sounds an alarm on mathematical modeling—a pervasive new force in society that threatens to undermine democracy and widen inequality.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O’Neil reveals in this shocking book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his race or neighborhood), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.

Tracing the arc of a person’s life, from college to retirement, O’Neil exposes the black box models that shape our future, both as individuals and as a society. Models that score teachers and students, sort resumes, grant (or deny) loans, evaluate workers, target voters, set parole, and monitor our health—all have pernicious feedback loops. They don’t simply describe reality, as proponents claim, they change reality, by expanding or limiting the opportunities people have. O’Neil calls on modelers to take more responsibility for how their algorithms are being used. But in the end, it’s up to us to become more savvy about the models that govern our lives. This important book empowers us to ask the tough questions, uncover the truth, and demand change.

具體描述

讀後感

評分

The answer is yes. A model, after all, is nothing more than an abstract representation of some process, be it a baseball game, an oil company’s supply chain, a foreign government’s actions, or a movie theater’s attendance. Whether it’s running in a comp...  

評分

虽然是很多事实的罗列,但如果不去看,可能永远也不会知道。前半部分比较无趣,后半部分有种战斗的感觉。 人类发明出来的许多工具都是中性的,关键是如何利用。这可能不仅仅是一个科技上的问题,更是一个道德问题。风险共担的意识在大数据时代更为重要和宝贵。因为一旦违背道德...  

評分

評分

評分

用戶評價

评分

https://book.douban.com/review/9331833/

评分

一篇討伐大數據的檄文。與那些贊歌不同,作者解釋各行各業中所用的數學模型(以及人們應對這些模型的方法)背後所蘊藏的種種歧視、黑箱與不公。這些陰暗麵加劇瞭當今社會的貧富差距和底層人民的憤怒,監管時不我待。

评分

太嘮叨

评分

迷信大數據的時代,需要好好讀一下這本書

评分

通篇讀完覺得稍空瞭一些 中途迴想起實習時的貸款延期批準模型 誤判率數字背後都聯係著顧客生計 唉想來不止是一個技術問題這麼簡單 作者自己從業經曆背景也蠻厲害的 總體論調不反智!

本站所有內容均為互聯網搜索引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度google,bing,sogou

© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有