As the amount of synthetic content online increases, it becomes more challenging for technology companies that operate platforms to scale methods for identifying and disclosing “meaningfully altered synthetic content.”
While Google recommends prominent labeling when the risk of harm from deceptive content is high, in some cases, direct disclosure that provides a “is this made or edited with AI or not” label can actually undermine users’ ability to determine trustworthiness.
Distributors should evaluate the benefits and drawbacks of providing direct disclosure, along with considering which platform they use, to ensure users receive meaningful context that helps them make informed decisions.

This is Google’s case submission as a supporter of PAI’s Synthetic Media Framework. Explore the other case studies

How an AI-manipulated video caused harm during South African elections

An analysis by digital democracy nonprofit Code for Africa

In May 2024, ahead of the South African general elections, the then-leading opposition party broadcast and shared an advertisement featuring a computer generated version of a South African flag burning.
Due to the burning flag, the video sparked public backlash, condemnation from the South African president, and fueled fear of synthetic content’s impact on elections.
Direct disclosure by the video’s creator could have helped mitigate harm and ensured the public’s attention was placed on the political message the opposition party was attempting to convey via the ad — that “life would only get worse” under the ruling party – instead of the controversial flag depiction.

This is Code for Africa’s case submission as a supporter of PAI’s Synthetic Media Framework. Explore the other case studies

How an investigation in South Asia uncovered harmful synthetic media

An analysis by technology nonprofit Meedan

As part of a research project, Meedan partnered with three regional organizations to study harmful, gendered content in South Asia.
By using Check, Meedan’s closed-messaging app tool that can help users identify and debunk synthetic content, the organizations were able to identify that the content contained synthetic components.
Through these findings, Meedan and its partners identified that, in order to better combat harmful content, social media platforms should make platform data more accessible to researchers and establish stronger ties with local community organizations seeking to do the same.

This is Meedan’s case submission as a supporter of PAI’s Synthetic Media Framework. Explore the other case studies