{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","title":"被算法操控的生活：重新定义精准广告、大数据和AI","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787571003012","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","id":"094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","uuid":"094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","title":"被算法操控的生活：重新定义精准广告、大数据和AI","normalized_title":"被算法操控的生活重新定义精准广告大数据和ai","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787571003012","isbns":["9787571003012"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":257,"navigation_url":"https://workshop.closeclaw.top/ai/book/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","title_url":"https://workshop.closeclaw.top/ai/title/%E8%A2%AB%E7%AE%97%E6%B3%95%E6%93%8D%E6%8E%A7%E7%9A%84%E7%94%9F%E6%B4%BB%EF%BC%9A%E9%87%8D%E6%96%B0%E5%AE%9A%E4%B9%89%E7%B2%BE%E5%87%86%E5%B9%BF%E5%91%8A%E3%80%81%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%92%8CAI","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a","page_url":"https://workshop.closeclaw.top/api/ai/books/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a/page","search_url":"https://workshop.closeclaw.top/api/ai/books/094ce2a7-d7e6-4de6-a84c-9994a96a3c4a/search"},"page":{"printed_page":53,"pdf_page":73,"physical_index":73,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"5421b7a815420bca67052e246cb12a0183f59c8083f7457eecb71836b3536959"},"chapter":"第3章你以为自己了解朋友？脸书比你更懂他们","content":"朱莉娅和同事的文章发表后，蒂姆和Northpointe很快做出了回应。他们写了一份研究报告，反驳ProPublica的分析是错误的。他们认为，COMPAS遵循的标准和其他久经检验的算法相同。他们声称，他们的算法对白人和黑人罪犯都进行了“精心校准”，而朱莉娅和她的同事们都对算法犯错这一概念产生了误解。\n\nNorthpointe和ProPublica之间的争论让我意识到偏见问题的复杂性。这些人都很聪明，他们在洋洋洒洒近百页的文章中你来我往地抗辩与驳斥，并辅以计算机代码和更多的统计分析。随后，博客、数学家和记者都对双方的辩论进行了热烈讨论，发表了自己对算法偏见的看法。定义偏见是一道数学难题，想弄明白就需要仔细研究它。\n\n为此我下载了ProPublica收集的数据，开始了我的研究。ProPublica收集的这些数据如表6.1所示，它们来自佛罗里达州布劳沃德郡（BrowardCounty)。为了理解 ProPublica 的论点和 Northpointe 的反击，我重新制表以便展示COMPAS算法将白人和黑人罪犯进行分类的方式，以及他们是否会因为再次犯罪而被捕。列，显示的是被COMPAS算法归为高风险和低风险的人数；行，显示的是再次犯罪和没有再犯的人数。\n\n让我们花一分钟看看这张表，问下自己是否认为这个算法存在偏见。首先我们比较一下有多少黑人和白人被归为高风险罪犯。3615名黑人罪犯中有2174人被列为高风险，概率是2174/3615≈60%。对白人罪犯的情况进行同样的计算后，我们发现他们被归类为高风险的概率仅为34.8%。所以黑人比白人更容易被视为潜在的犯罪分子。\n\n第一部分 算在时个我数据做了什么？\n\n53","previous_page":52,"next_page":54}