Talking about Platforms Dimensions of data labor with Hanlin Li
Dec 27, 2023
Hanlin Li, an assistant professor at UT Austin, delves into the complexities of data labor and governance. She discusses how online contributions are monetized and the need for transparency in data practices. Hanlin examines motivations behind volunteer content creation and explores generative AI's impact on creators. She emphasizes the importance of designing effective transparency measures and suggests policy mandates for data usage disclosure. Her insights aim to empower data producers and highlight the societal implications of user-generated content.
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Every Click Can Be Labor
- Many online activities (ratings, posts, edits) produce value that platforms and third parties monetize without direct compensation.
- Recognizing these actions as "data labor" reframes contributors as producers of economic value.
Show Contributors Their Impact
- Provide contributors with transparency about how their content generates value so they can negotiate fair distribution.
- Use impact visibility as a first step toward equitable revenue sharing mechanisms.
Valuing Reddit Moderation Work
- Hanlin measured Reddit moderators' labor by tallying their visible moderation actions and estimating hours worked.
- She valued that labor using market rates for paid moderators to estimate Reddit's unpaid labor subsidy.