<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bringing the People Back In: Contesting Benchmark Machine Learning Datasets · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2007.07399/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2007.07399/feed.xml" rel="self" type="application/rss+xml" /><item><title>Bringing the People Back In: Contesting Benchmark Machine Learning Datasets — mentioned by accraze</title><link>https://news.ycombinator.com/item?id=25350938</link><guid isPermaLink="false">urn:hackerpapers:mention:2007.07399:25350938</guid><pubDate>Tue, 08 Dec 2020 20:31:42 GMT</pubDate><description>&lt;p&gt;Three papers stick out for me in the IML / participatory machine learning space this year: 1) Michael, C. J., Acklin, D., &amp;amp; Scheuerman, J. (2020). On interactive machine learning and the potential of cognitive feedback. ArXiv:2003.10365 [Cs]. http://arxiv.org/abs/2003.10365 2) Denton, E., Hanna, A., Amironesei, R., Smart, A., Nicole, H., &amp;amp; Scheuerman, M. K. (2020). Bringing the people back in: Contesting benchmark machine learning datasets. ArXiv:2007.07399 [Cs]. http://arxiv.org/abs/2007.07399 3) Jo, E. S., &amp;amp; Gebru, T. (2020). Lessons from archives: Strategies for collecting sociocultural…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2007.07399/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CY</category></item></channel></rss>
