Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning

Sat, 01 Jul 2023 00:00:00 +0000

Most AI training forces annotators to agree on a single “correct” label, erasing legitimate differences of opinion. But when humans disagree (like on whether a tweet is offensive), that disagreement is often meaningful—not noise. CrowdOpinion solves this by clustering similar content and predicting the full distribution of opinions people might have, rather than picking one “winner.” We tested it on Twitter, Reddit, Gab, and Facebook data, where disagreement is common. This approach ensures minority viewpoints aren’t silenced, which is crucial for building fair AI that respects diverse perspectives—especially important for content moderation and other subjective decisions.

Findings from the Bambara - French Machine Translation Competition (BFMT 2023)

Mon, 01 May 2023 00:00:00 +0000

Sarah Luger | Tharindu Cyril Weerasooriya

Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning

Findings from the Bambara - French Machine Translation Competition (BFMT 2023)