While AI has ushered in an unprecedented era of knowledge-sharing online, it has also enabled novel forms of misinformation, manipulation, and harassment as well as amplifying harmful digital content’s potential impact and reach. PAI’s AI and Media Integrity Program directly addresses these critical challenges to the quality of public discourse by investigating AI’s impact on digital media and online information, researching timely subjects such as manipulated media detection, misinformation interventions, and content-ranking principles.
Through this Program, PAI works to ensure that AI systems bolster the quality of public discourse and online content around the world, which includes considering how we define quality in the first place. By convening a fit-for-purpose, multidisciplinary field of actors — including representatives from media, industry, academia, civil society, and users that consume content — the AI and Media Integrity Program is developing best practices for AI to have a positive impact on the global information ecosystem.
Our AI and Media Integrity Work
Since its inception in 2019, the AI and Media Integrity Program has focused on projects that empower the public to distinguish between credible information and mis/disinformation. This has ranged from inquiries into how audiences interpret internet content to concrete recommendations for the field of synthetic media detection.
Currently, the Program is pursuing four distinct Workstreams exploring different intervention points for improving the broader quality and integrity of information online. The lifecycle of any piece of internet content begins with its creation. It is then distributed, usually on social media platforms, before finally being interpreted by an end user, also typically on these platforms. Our Synthetic and Manipulated Content, Content Targeting and Ranking, Audience Explanations, and Local News Workstreams investigate what can be done to promote a healthy information ecosystem across these stages.
How to Share the Tools to Spot Deepfakes (Without Breaking Them)
If We Want Platforms to Think Beyond Engagement, We Have to Know What We Want Instead
Fact-Checks, Info Hubs, and Shadow-Bans: A Landscape Review of Misinformation Interventions
From Deepfakes to TikTok Filters: How Do You Label AI Content?
Partnership on AI Awarded Knight Foundation Grant to Support Local News
Labeling Misinformation Isn’t Enough. Here’s What Platforms Need to Do Next.
Warning Labels Won’t Be Enough to Stop Vaccine Misinformation
AI and Media Integrity Steering Committee
The AI and Media Integrity Steering Committee is a formal body of PAI Partner organizations focused on projects confronting the emergent threat of AI-generated mis/disinformation, synthetic media, and AI’s effects on public discourse.
Head of Technology Forecasting
Research and Development Strategist
New York Times
Senior Advisor, Business Strategy
IBM Watson AI XPRIZE
Senior Policy Manager
Senior Program Manager
Director of the Content Authenticity Initiative
Research Software Engineer