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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1712.00193/</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/1712.00193/feed.xml" rel="self" type="application/rss+xml" /><item><title>InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity — mentioned by phillipcarter</title><link>https://news.ycombinator.com/item?id=36814189</link><guid isPermaLink="false">urn:hackerpapers:mention:1712.00193:36814189</guid><pubDate>Fri, 21 Jul 2023 14:27:20 GMT</pubDate><description>&lt;p&gt;&amp;gt; AI ethics always end up just throwing out &amp;quot;bias&amp;quot; as an ill defined term that could mean whatever they want it to, the way people like to use &amp;quot;harm&amp;quot; and &amp;quot;toxicity&amp;quot; There&amp;#x27;s a lot of specific examples of different kinds bias in models and things that can be done to improve them. A lot of that work was published in the past 10 years. One small example: https://arxiv.org/abs/1712.00193 I don&amp;#x27;t believe there&amp;#x27;s a lack of specificity going on here, at least not by those whose boots on the ground doing work on the topic.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1712.00193/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
