Meedan has been invited by Partnership on AI (PAI) to join its AI and Media Integrity Steering Committee, a group of institutions that meets every two weeks to advise and collaborate on projects related to the intersection of AI, digital media, and online information.
Steering Committee members are chosen based on their ability to contribute to a diverse and multidisciplinary approach to the responsible development of AI technology.
“We seek representation from established tech companies building generative AI tools, news organizations, academics, and NGOs/Civil Society organizations,” explains PAI.
Ed Bice, Meedan’s CEO will join current committee members from the BBC, Witness, the New York Times, CBC/Radio-Canada, Google, Amazon, Meta, Adobe, and Microsoft.
“We are looking forward to not only providing our input and insight as a technology not-for-profit working towards building a more equitable Internet, but on sharing our use cases for the development of PAI’s guidance materials,” comments Meedan CEO Ed Bice.
PAI is a non-profit partnership of academic, civil society, industry, and media organizations creating solutions so that AI advances positive outcomes for people and society.
Through its AI and Media Integrity Program, PAI is developing best practices for AI to have a positive impact on the global information ecosystem. The AI and Media Integrity Steering Committee is focused on specific projects confronting the threats and opportunities from AI-generated content. The Steering Committee also seeks to increase coordination across organizations implicated by these developments, as these challenge areas affect a broad ecosystem of sectors, organizations, and people around the world.
- Online conversations are heavily influenced by news coverage, like the 2022 Supreme Court decision on abortion. The relationship is less clear between big breaking news and specific increases in online misinformation.
- The tweets analyzed were a random sample qualitatively coded as “misinformation” or “not misinformation” by two qualitative coders trained in public health and internet studies.
- This method used Twitter’s historical search API
- The peak was a significant outlier compared to days before it using Grubbs' test for outliers for Chemical Abortion (p<0.2 for the decision; p<0.003 for the leak) and Herbal Abortion (p<0.001 for the decision and leak).
- All our searches were case insensitive and could match substrings; so, “revers” matches “reverse”, “reversal”, etc.