New report of the Forum on Information and Democracy: more than 200 policy recommendations to ensure democratic control of AI
Presentation of the report on AI as a Public Good by the Forum on Information and Democracy

New report of the Forum on Information and Democracy: more than 200 policy recommendations to ensure democratic control of AI

On February 28th 2024, the Forum on Information and Democracy launched the report “AI as a Public Good: Ensuring Democratic Control of AI in the Information Space”.

The policy recommendations were developed by an international Policy Working Group with 14 members from diverse disciplines and 13 countries on all continents. Suzanne Vergnolle, Holder of the Chair on Online Content Moderation, was one of the experts contributing to this report.

The report contains more than 200 recommendations addressed to governments, the industry and relevant stakeholders, on four different topics: Design, Liability, Ethics, and Governance. Over 6 months, experts worked through an inclusive and consultative process, receiving inputs from contributors worldwide.

It takes a comprehensive approach calling for safe and inclusive AI systems, putting in place accountability mechanisms and incentives for ethical AI as well as governance mechanisms.  

Among the key recommendations, we can notably cite:

  • Foster the creation of a tailored certification system for AI companies inspired by the success of the Fair Trade certification system.
  • Establish standards governing content authenticity and provenance, including for author authentication.
  • Implement a comprehensive legal framework that clearly defines the rights of individuals including the right to be informed, to receive an explanation, to challenge a machine-generated outcome, and to non-discrimination.
  • Provide users with an easy and user-friendly opportunity to choose alternative recommender systems that do not optimize for engagement but build on ranking in support of positive individual and societal outcomes, such as reliable information, bridging content or diversity of information.
  • Set up a participatory process to determine the rules and criteria guiding dataset provenance and curation, human labeling for AI training, alignment, and red-teaming to build inclusive, non-discriminatory and transparent AI systems.

📄 Link to the full report