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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1711.08536/</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/1711.08536/feed.xml" rel="self" type="application/rss+xml" /><item><title>No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World — mentioned by johnny313</title><link>https://news.ycombinator.com/item?id=19372500</link><guid isPermaLink="false">urn:hackerpapers:mention:1711.08536:19372500</guid><pubDate>Tue, 12 Mar 2019 20:13:23 GMT</pubDate><description>&lt;p&gt;This reminds me of a paper put out by a few researchers at Google Brain: `No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing World` [0] The take away was that existing open image datasets are biased toward western contexts (eg what a wedding looks like), leading to low performance when applied in non-western contexts. [0] https://arxiv.org/abs/1711.08536&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1711.08536/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
