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does the report define the role of predictive tools in the hiring funnel?","Question",{"text":56,"@type":57},"It describes hiring as a cumulative series of small decisions, where predictive technology can influence visibility of job ads, estimation of performance, and forecasting of candidate compensation expectations across multiple stages.","Answer",{"name":59,"@type":54,"acceptedAnswer":60},"Why doesn’t removing sensitive attributes fully solve bias in predictive hiring tools?",{"text":61,"@type":57},"The report states that predictions built from past hiring decisions and evaluations can still reveal and reproduce inequitable patterns even when tools explicitly ignore protected attributes like race, gender, and age.",{"name":63,"@type":54,"acceptedAnswer":64},"What is the report’s main recommendation to address bias in predictive hiring?",{"text":65,"@type":57},"It concludes that bias will arise by default without active mitigation, and it calls for further scrutiny and reflection supported by more deliberation, transparency, and oversight.","https://schema.org",{"og:url":32,"og:type":68,"og:title":10,"og:site_name":40,"og:description":12},"article",{"robots":70,"canonical":32},"index,follow",{"doc_id":72,"site_id":7},571509,1791921573,{"code":4,"msg":75,"data":76},"success",[77,82,87,92,97,102,107,112,117],{"id":78,"doc_module":22,"doc_module_name":25,"category_name":79,"show_sort_weight":80,"slug":81},11,"Presentations",90,"presentations",{"id":83,"doc_module":22,"doc_module_name":25,"category_name":84,"show_sort_weight":85,"slug":86},12,"Resumes",80,"resumes",{"id":88,"doc_module":22,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},14,"Invoices",70,"invoices",{"id":93,"doc_module":22,"doc_module_name":25,"category_name":94,"show_sort_weight":95,"slug":96},15,"Posters",60,"posters",{"id":98,"doc_module":22,"doc_module_name":25,"category_name":99,"show_sort_weight":100,"slug":101},16,"Social 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Summary.............................................................................................................................1  \n1 Introduction ............................................................................................................................................3  \n2 Key Concepts..........................................................................................................................................5  \nTechnology: From [Monster.com](Monster.com) to Machine Learning ............................................................ 5  \nA History of Hiring Technology ........................................................................................................................... 5  \nWhy Employers Adopt Predictive Tools ........................................................................................................ 6  \nEquity: Beyond Interpersonal Bias ....................................................................................................... 7  \nDifferent Dimensions of Bias................................................................................................................................ 7  \nHow Predictive Tools Can Perpetuate Biases ............................................................................................ 8  \nLaw and Policy: Antidiscrimination and Ambiguities ............................................................... 9  \nKey U.S. Statutes and Regulations .................................................................................................................. 10  \nGaps and Ambiguities ..............................................................................................................................................11  \n3 Predictive Tools Across the Hiring Funnel ..........................................................................13  \nA Landscape of Predictive Hiring Tools........................................................................................... 14  \nSourcing ......................................................................................................................................................................... 14  \nScreening.......................................................................................................................................................................26  \nInterviewing .................................................................................................................................................................36  \nSelection.........................................................................................................................................................................39  \n4 Reflections and Recommendations...................................................................................... 44  \nGuiding Questions ...................................................................................................................................... 44  \nReflections....................................................................................................................................................... 45  \nRecommendations..................................................................................................................................... 46  \n5 Conclusion.............................................................................................................................................47  \nExecutive Summary  \nThe hiring process is a critical gateway to economic opportunity, determining who can access consistent work to support themselves and their families. Employers have long used digital technology to manage their hiring decisions, and now many are turning to new predictive hiring tools to inform each step of their hiri","cbCaidoXU1LLel0U","https://ap.wps.com/l/cbCaidoXU1LLel0U","pdf",5450214,75,"English","# Executive Summary\n# Introduction\n# Key Concepts\n## Technology: From Monster.com to Machine Learning\n## Equity: Beyond Interpersonal Bias\n## Law and Policy: Antidiscrimination and Ambiguities\n# Predictive Tools Across the Hiring Funnel\n## Sourcing\n## Screening\n## Interviewing\n## Selection\n# Reflections and Recommendations\n## Guiding Questions\n## Reflections\n## Recommendations\n# Conclusion","[{\"question\":\"How does the report define the role of predictive tools in the hiring funnel?\",\"answer\":\"It describes hiring as a cumulative series of small decisions, where predictive technology can influence visibility of job ads, estimation of performance, and forecasting of candidate compensation expectations across multiple stages.\"},{\"question\":\"Why doesn’t removing sensitive attributes fully solve bias in predictive hiring tools?\",\"answer\":\"The report states that predictions built from past hiring decisions and evaluations can still reveal and reproduce inequitable patterns even when tools explicitly ignore protected attributes like race, gender, and age.\"},{\"question\":\"What is the report’s main recommendation to address bias in predictive hiring?\",\"answer\":\"It concludes that bias will arise by default without active mitigation, and it calls for further scrutiny and reflection supported by more deliberation, transparency, and oversight.\"}]","Upturn - Help Wanted - An Examination of Hiring Algorithms, Equity, and Bias | PDF",26]