Ensuring Platform Transparency and Accountability
Summary
Open-source investigations and public interest research using platform data (e.g., Facebook, YouTube) have enabled the collection of evidence of human rights atrocities, identified the role of foreign adversaries in manipulating public opinion before elections, and uncovered the prevalence and reach of terrorist radicalization and recruitment tactics. Nascent data privacy legislation such as the EU General Data Protection Regulation and the California Consumer Privacy Act have placed increased pressure on platforms to restrict third party access to data. In an overly cautious interpretation of these laws, platforms are increasingly restricting third-party access to the data they collect. In doing so, platforms shield themselves from public scrutiny and accountability.
To support transparency and accountability of platforms, the next administration should work with Congress to ensure that any new data privacy legislation proposed at the federal level does not inadvertently block the ability of third parties to gain access to platform data for open-source investigations and public interest research. The White House Office of Science and Technology Policy should take the lead by convening a workshop among key actors to make progress on these goals. Out of the workshop, a federal working group should be formed to develop principles and operational guides to support ethical third-party access to platform data, including the formation of technical standards to ensure data privacy and security.
AI’s high-stakes outputs directly shape American economic, industrial, and technological outcomes. They must not be accepted entirely on the basis of institutional faith rather than verifiable evidence.
The clearinghouse will also neutrally mediate the assignment of auditors to audits—strengthening independence, trust, and ethical governance across the AI ecosystem.
Soft law was never meant to be a permanent solution. Treating it as one, and letting the sandcastle stand in for the skyscraper indefinitely, is how we end up with a decade of voluntary commitments and no enforceable accountability to show for it.
Jobseekers, employees at smaller organizations, and local public workers need more than a weekend crash course in AI. They need practice choosing useful tasks, protecting data, testing outputs, and explaining where human judgment remains necessary.