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
发表于2024-11-05
Weapons of Math Destruction pdf epub mobi txt 電子書 下載 2024
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.
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.
太嘮叨
評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!
評分迷信大數據的時代,需要好好讀一下這本書
評分名字起得不錯,作者對“數學殺傷性武器“的定義也很明確:opaque, large scale ,disruptive. 現實生活中的例子也有清晰闡述,包括 value added model 並不能真正反映教師的水平(很多差生+很多好生的班級能夠進步的空間不大,相反比較中等的班級更容易通過提高成績而增加教師的評分);大數據分析信貸對弱勢群體的不公;自動調班係統讓零售業打工者疲於奔命等。
評分可能之前期待值太高 所以落差比較大.. 對fairness and accountability in ml比較陌生的人還是很推薦的。 讀起來覺得大媽強項的數學模型方麵可能考慮非technical讀者粗略帶過不過癮, 不是專項的policy方麵argument又比較sloppy...
感谢 recall 这本书的不知名同学,谢谢你逼得我用4个小时读完。 作者创造了“数学杀伤性武器”(Weapons of Math Destruction, WMD)这个词指代统计模型,探讨现实生活中统计模型的大规模应用对社会的影响。 正面例子是棒球、篮球比赛的分析,可以即时调整战术(参考《点球成金...
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...
評分文 / 董小琳 我们可以将时代划分为:有大数据之前 和 有大数据之后。 为什么要这么分? 因为,谁也不能忽视,大数据对我们每个人生活方方面面的影响。 比如说: 之前,你的日子过得好不好,恐怕除了家里人,只有几个关系特别好的朋友知道。 甚至,在亲戚比较多的大家庭里,你还...
Weapons of Math Destruction pdf epub mobi txt 電子書 下載 2024