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Editing time on AI drafts predicts hiring success as employers shift to alternative signals such as prior work histories.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/letters/","Letters",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/template/signaling-in-the-age-of-ai-evidence-from-cover-letters/256022/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/signaling-in-the-age-of-ai-evidence-from-cover-letters/256022.png","ImageObject",442,249,{"name":42,"@type":43},"Jiven","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-23","2026-09-13",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",13,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"How does the study measure the impact of generative AI on labor market signaling?","Question",{"text":63,"@type":64},"It studies the rollout of an AI-powered cover letter tool on Freelancer.com and tracks access and usage at the application level, then links these to callback and hiring outcomes.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"What do the difference-in-differences results show about cover letters after the tool is introduced?",{"text":68,"@type":64},"Access to the tool increased textual alignment between cover letters and job posts and raised callback rates.",{"name":70,"@type":61,"acceptedAnswer":71},"Why does the paper interpret the 51% fall in the alignment-callback correlation after rollout?",{"text":72,"@type":64},"It matches theory where AI reduces the signal content of cover letters, weakening the relationship between textual alignment and callbacks.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},256022,1790394907,{"code":4,"msg":82,"data":83},"success",[84,89,94,99,104,109,114,118,123],{"id":85,"doc_module":22,"doc_module_name":25,"category_name":86,"show_sort_weight":87,"slug":88},11,"Presentations",90,"presentations",{"id":90,"doc_module":22,"doc_module_name":25,"category_name":91,"show_sort_weight":92,"slug":93},12,"Resumes",80,"resumes",{"id":95,"doc_module":22,"doc_module_name":25,"category_name":96,"show_sort_weight":97,"slug":98},14,"Invoices",70,"invoices",{"id":100,"doc_module":22,"doc_module_name":25,"category_name":101,"show_sort_weight":102,"slug":103},15,"Posters",60,"posters",{"id":105,"doc_module":22,"doc_module_name":25,"category_name":106,"show_sort_weight":107,"slug":108},16,"Social Media",50,"social-media",{"id":110,"doc_module":22,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},17,"Forms",40,"forms",{"id":115,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":116,"slug":117},18,30,"letters",{"id":119,"doc_module":22,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},21,"Paper Templates",5,"papers-templates",{"id":124,"doc_module":22,"doc_module_name":25,"category_name":125,"show_sort_weight":4,"slug":126},158,"General","general-158",{"code":4,"msg":82,"data":128},{"doc_id":79,"user_id":129,"nickname":42,"user_avatar":130,"doc_module":22,"category_id":115,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":136,"language":137,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":138,"faqs":139,"seo_title":140,"seo_description":12,"update_tm":141,"read_time":115},1099513958607,"https://ap-avatar.wpscdn.com/avatar/100002390cf8733938c?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778829742770036399","Signaling in the Age of AI: Evidence from Cover Letters ∗  \nJingyi Cui, Gabriel Dias, and Justin Ye †  \nNovember 12, 2025  \nAbstract  \nWe study the impact of generative AI on labor market signaling using the introduction of an AI-powered cover letter writing tool on a large online labor platform. Our data track both access to the tool and usage at the application level. Difference-in-differences estimates show that access to the tool increased textual alignment between cover letters and job postsand raised callback rates. Time spent editing AI-generated cover letter drafts is positively correlated with hiring success. After the tool’s introduction, the correlation between cover letters’ textual alignment and callbacks fell by 51%, consistent with what theory predicts if the AI technology reduces the signal content of cover letters. In response, employers shifted toward alternative signals, including workers’ prior work histories.  \n∗We are grateful to Elliot Ash for suggesting the research question and Freelancer.com for providing the data. We thank Joe Altonji, Steve Berry, Guillermo Carranza, Winnie van Dijk, Phil Haile, Charles Hodgson, Katja Seim, and participants at seminars for helpful conversations. This work was supported by funding from the Cowles Foundation for Research in Economics at Yale University. Galdin and Silbert (2025) first measured similarity between cover [letters and job posts on Freelancer.com](letters and job posts on Freelancer.com), interpreted it as a signal of worker ability, and showed it predicts hiring. The two research teams later independently conceived and studied the impact of AI, providing complementary evidence.†Yale Department of Economics; Contact information: [jingyi.cui@yale.edu](jingyi.cui@yale.edu), [gabriel.santamarina@yale.edu](gabriel.santamarina@yale.edu), and  \n[justin.ye@yale.edu](justin.ye@yale.edu).  \n1 Introduction  \nJob seekers and college applicants increasingly turn to generative artificial intelligence (AI) tools like ChatGPT to edit r´esum´es, craft cover letters, and prepare for interviews.1 Despite the transformative potential of this technology for processes central to economic opportunities and social mobility, credible empirical evidence on how AI affects labor market signaling remains scarce.2 The main obstacle is observability: outside of controlled lab settings, just as employers struggle to identify AIassisted applications, so too do researchers. Current detection tools are error-prone and unreliable (Weber-Wulff et al. (2023)), making it difficult to assess AI assistance’s real-world impact on hiring.  \nWe overcome this challenge by studying the introduction of a generative AI cover letter writing tool [on Freelancer.com](on Freelancer.com), one of the world’s largest online labor platforms. Freelancer connects international workers and employers to collaborate on short-term, skilled, and mostly remote jobs. On April 19, 2023, Freelancer introduced the “AI Bid Writer,” a tool that automatically generates cover letters tailored to employers’ job descriptions that workers can use or edit. The tool was available to a large subset of workers depending on their membership plans. Employers, as is typical in most real-world settings, could not observe which workers had access to the tool or whether a given cover letter was AI-assisted.  \nWe use eight months of data from two leading skill categories, PHP and Internet Marketing, covering 5 million cover letters submitted to over 100,000 jobs.3 We observe access to the tool and usage of the tool at the application level. We link access and usage information to the submitted cover letters and to callback and hiring outcomes to analyze the effect of generative AI at both the individual level and the market level. We also observe timestamps of workers’ clicks on the AI tool and their application submissions, allowing us to measure the time they spent editing the AI-generated texts and examine the effect of human-AI interac","cbCailxDMV5AaaIN","https://ap.wps.com/l/cbCailxDMV5AaaIN","pdf",2078575,51,"English","# Introduction\n## Research motivation\n## Platform and tool rollout\n## Data and empirical strategy","[{\"question\":\"How does the study measure the impact of generative AI on labor market signaling?\",\"answer\":\"It studies the rollout of an AI-powered cover letter tool on Freelancer.com and tracks access and usage at the application level, then links these to callback and hiring outcomes.\"},{\"question\":\"What do the difference-in-differences results show about cover letters after the tool is introduced?\",\"answer\":\"Access to the tool increased textual alignment between cover letters and job posts and raised callback rates.\"},{\"question\":\"Why does the paper interpret the 51% fall in the alignment-callback correlation after rollout?\",\"answer\":\"It matches theory where AI reduces the signal content of cover letters, weakening the relationship between textual alignment and callbacks.\"}]","Signaling in the Age of AI - Evidence from Cover Letters | PDF",1789297531]