<div dir="ltr">Maria is back!<div><br></div><div>Artur<br><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">---------- Forwarded message ---------<br>From: <strong class="gmail_sendername" dir="auto">Martin Gaynor</strong> <span dir="auto"><<a href="mailto:mgaynor@andrew.cmu.edu">mgaynor@andrew.cmu.edu</a>></span><br>Date: Mon, Feb 13, 2023 at 3:35 PM<br>Subject: Seminar Detail - Seminar Tracker<br>To: heinz-phd@lists. edu <<a href="mailto:heinz-phd@lists.andrew.cmu.edu">heinz-phd@lists.andrew.cmu.edu</a>>, <<a href="mailto:heinz-all-faculty@lists.andrew.cmu.edu">heinz-all-faculty@lists.andrew.cmu.edu</a>><br></div><br><br><div style="line-break:after-white-space"><div>FYI our terrific PhD alum Maria DeArtega, who some of you may recall, is giving a talk over at Tepper this Friday. Best, Marty</div><div><blockquote type="cite" style="border-left-style:none;color:inherit;padding:inherit;margin:inherit"><div><div><br><a href="https://seminartracker.tepper.cmu.edu/" target="_blank">https://seminartracker.tepper.cmu.edu/</a><br><br></div><div id="m_-5156046459534190342article" role="article" style="font-family:-apple-system-font;font-size:1.2em;line-height:1.5em;margin:0px;padding:0px">
<div style="text-align:start;max-width:100%"><h1 style="font-weight:bold;font-size:1.95552em;line-height:1.2141em;margin-top:0px;margin-bottom:0.5em;text-align:start;display:block;max-width:100%">Maria De-Arteaga</h1>
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</p><h1 style="font-weight:bold;font-size:1.5em;line-height:1.4em;max-width:100%">BT/IS Seminar - A Case for Humans-in-the-Loop: Decisions in the Presence of Misestimated Algorithmic Scores </h1>
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<label name="seminartm" style="max-width:100%">February 17, 2023 at 12:00 PM EST (local)</label>
|| Duration: 60 minutes
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Location: Virtual, Meeting Link: (Virtual)
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The increased use of machine learning to assist with decision-making in high-stakes domains has been met with both enthusiasm and concern. One source of ongoing debate is the effect and value of decision makers' discretionary power to override algorithmic recommendations. In this paper, we study the adoption of an algorithmic tool used to help with decisions in child maltreatment hotline screenings. By taking advantage of an implementation glitch, we investigate corrective overrides: whether decision makers are more likely to override algorithmic recommendations when the tool misestimates the risk score shown to call workers. We find that, after the deployment of the tool, decisions became better aligned with algorithmic assessments, but human adherence to the tool's recommendation was less likely when the displayed score was misestimated as a result of the glitch. Then, analyzing the effect of adoption and overrides on racial and socioeconomic disproportionalities, we find that the deployment of the tool did not affect disproportionalities with respect to the pre-deployment period. We also observe that the disproportionalities resulting from algorithmic-informed decisions were substantially smaller than those associated with the algorithm in isolation. Together, these results make a case for the value of humans in-the-loop, showing that in high-stakes contexts, human discretionary power can mitigate the risks of algorithmic errors and reduce disparities.
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<span style="max-width:100%">Paper:</span> <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4050125" style="color:rgb(65,110,210);max-width:100%;text-decoration:underline" target="_blank">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4050125</a>
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<span style="max-width:100%">Additional Notes:</span> Meeting ID: 951 4541 3358
Passcode: 294771
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If you have any questions, please contact
Phil Conley
at <a href="mailto:pconley@andrew.cmu.edu" style="color:rgb(65,110,210);max-width:100%;text-decoration:underline" target="_blank">pconley@andrew.cmu.edu</a>
(412) 268-6212
(Carnegie Mellon University).
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