Moderating Model Marketplaces: Platform Governance Puzzles for AI
Intermediaries
- URL: http://arxiv.org/abs/2311.12573v2
- Date: Thu, 15 Feb 2024 16:19:33 GMT
- Title: Moderating Model Marketplaces: Platform Governance Puzzles for AI
Intermediaries
- Authors: Robert Gorwa and Michael Veale
- Abstract summary: Hosting intermediaries such as Hugging Face provide easy access to user-uploaded models and training data.
These model marketplaces lower technical deployment barriers for hundreds of thousands of users, yet can be used in numerous potentially harmful and illegal ways.
- Score: 1.813006808606333
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The AI development community is increasingly making use of hosting
intermediaries such as Hugging Face provide easy access to user-uploaded models
and training data. These model marketplaces lower technical deployment barriers
for hundreds of thousands of users, yet can be used in numerous potentially
harmful and illegal ways. In this article, we explain ways in which AI systems,
which can both `contain' content and be open-ended tools, present one of the
trickiest platform governance challenges seen to date. We provide case studies
of several incidents across three illustrative platforms -- Hugging Face,
GitHub and Civitai -- to examine how model marketplaces moderate models.
Building on this analysis, we outline important (and yet nevertheless limited)
practices that industry has been developing to respond to moderation demands:
licensing, access and use restrictions, automated content moderation, and open
policy development. While the policy challenge at hand is a considerable one,
we conclude with some ideas as to how platforms could better mobilize resources
to act as a careful, fair, and proportionate regulatory access point.
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