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X-WR-CALNAME;VALUE=TEXT:Group fairness in dynamic refugee assignment
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SUMMARY:Group fairness in dynamic refugee assignment
DESCRIPTION:<p>	 </p><p>	This <strong>Friday, 1-2pm in SEC 1.413</strong>, we will have <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__mitmgmtfaculty.mit.edu_tlykouris_&amp;d=DwMFaQ&amp;c=WO-RGvefibhHBZq3fL85hQ&amp;r=ZOP6tLIqLOHbdgCvrXjUlPta0tw7K_-ivqiItQhh6LQ&amp;m=xyFg9zZLKvPEm2nJ1d69XakQtVKJVwswzReOu-Eu_VVWVzwMs0xI9aQTWQ28_H7n&amp;s=cRx-QNqwWqEAuSnVrlxkC5Vnh2cM1M86GQDgwPo_0SA&amp;e=">professor Thodoris Lykouris</a> from MIT to speak <strong>in-person</strong> on<br><br>Title: <strong>Group fairness in dynamic refugee assignment</strong></p><p>	<span><span style="color:black">Abstract: </span></span></p><p>	<span><span style="color:black">Ensuring that refugees and asylum seekers thrive (e.g., find employment) in their host countries is a profound humanitarian goal, and a primary driver of employment is the geographic location within a host country to which the refugee or asylum seeker is assigned. Recent research has proposed and implemented algorithms that assign refugees and asylum seekers to geographic locations in a manner that maximizes the average employment across all arriving refugees. While these algorithms can have substantial overall positive impact, using data from two industry collaborators we show that the impact of these algorithms can vary widely across key subgroups based on country of origin, age, or educational background. Thus motivated, we develop a simple and interpretable framework for incorporating group fairness into the dynamic refugee assignment problem. In particular, the framework can flexibly incorporate many existing and future definitions of group fairness from the literature (e.g., minmax, randomized, and proportionally-optimized within-group). Equipped with our framework, we propose two bid-price algorithms that maximize overall employment while simultaneously yielding provable group fairness guarantees. Through extensive numerical experiments using various definitions of group fairness and real-world data from the U.S. and the Netherlands, we show that our algorithms can yield substantial improvements in group fairness compared to state-of-the-art algorithms with only small relative decreases (≈ 1%-2%) in global performance.</span></span></p><p style="margin-bottom:12.0pt">	<br><span><span style="color:black">Paper information:<br>This talk is based on joint work with Daniel Freund, Elisabeth Paulson, Bradley Sturt, and Wentao Weng. A preprint of the corresponding paper can be found here: </span></span><a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__arxiv.org_abs_2301.10642&amp;d=DwMFaQ&amp;c=WO-RGvefibhHBZq3fL85hQ&amp;r=ZOP6tLIqLOHbdgCvrXjUlPta0tw7K_-ivqiItQhh6LQ&amp;m=xyFg9zZLKvPEm2nJ1d69XakQtVKJVwswzReOu-Eu_VVWVzwMs0xI9aQTWQ28_H7n&amp;s=-BOukPHichcxSJrUY5neEaIEHIu72qZEB6gGeJMsDDc&amp;e=" target="_blank">https://arxiv.org/abs/2301.10642</a>.</p><p>	For those who cannot attend in-person, the Zoom link is as usual: <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__harvard.zoom.us_j_95184948637-3Fpwd-3DbXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09&amp;d=DwMFaQ&amp;c=WO-RGvefibhHBZq3fL85hQ&amp;r=ZOP6tLIqLOHbdgCvrXjUlPta0tw7K_-ivqiItQhh6LQ&amp;m=xyFg9zZLKvPEm2nJ1d69XakQtVKJVwswzReOu-Eu_VVWVzwMs0xI9aQTWQ28_H7n&amp;s=GXpqa6Ppz9AVm7w3E5mSAJ-4aWOmUIWaCLX4Qjsz5lI&amp;e=" target="_blank">https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09</a> (password: econcs)</p><p>	<span><span style="color:black">This work is closely related to last Friday's wonderful talk from Professor Elisabeth Paulson. Email me or Jamie (</span></span><span><a href="mailto:jtuckerfoltz@gmail.com">jtuckerfoltz@gmail.com</a><span style="color:black">) for the recording. And heads-up for next week: we will have professor Shared Goel on </span></span><em>Included-variable bias and everything but the kitchen sink</em></p><p>	 </p>
LOCATION:SEC 1.413, & streamed via Zoom at: https://harvard.zoom.us/j/95184948637?pwd=bXBIc2U5MEZ0QmRUb01WQ0o0SXRCdz09
STATUS:CONFIRMED
DTSTART:20230331T170000Z
DTEND:20230331T180000Z
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