图书标签: 大数据 社会学 美国 数字社会学 inequality 数学 社会 政治科学
发表于2024-12-22
Weapons of Math Destruction pdf epub mobi txt 电子书 下载 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.
https://book.douban.com/review/9331833/
评分通篇读完觉得稍空了一些 中途回想起实习时的贷款延期批准模型 误判率数字背后都联系着顾客生计 唉想来不止是一个技术问题这么简单 作者自己从业经历背景也蛮厉害的 总体论调不反智!
评分可能之前期待值太高 所以落差比较大.. 对fairness and accountability in ml比较陌生的人还是很推荐的。 读起来觉得大妈强项的数学模型方面可能考虑非technical读者粗略带过不过瘾, 不是专项的policy方面argument又比较sloppy...
评分迷信大数据的时代,需要好好读一下这本书
评分各种案例堆积,看不下去。对每个模型bad feedback loop都分析了,但是alternative呢?transparency怎么做不够深入
【春上春树随喜文化】 算法是层级和并行思维的融合 可视化,标准化,规模化,全球化 去中心化,分布式计算,智能虚拟助手 乃至宗教般毋庸置疑的 民主和科学的感召 最后所有人被既得利益者 网罗为囊中之物 辛普森悖论 是《国富论》所谓的 看不见的手 阶层难以穿透 跃迁机会渺茫 ...
评分 评分作者在华尔街对冲基金德绍集团担任过金融工程师,后来去银行做过风险分析,再后来去做旅游网站的用户分析。后来辞职专门揭露美国社会生活背后的各种算法的阴暗面。 书中提到的算法的技术缺陷,我归纳为两点:第一个比较致命:不准确。不准确有两种体现,首先是算法先天的问题,...
评分Weapons of Math Destruction pdf epub mobi txt 电子书 下载 2024