Reframing the meaning of truth in AI generated content
This is an interactive session, which discusses how AI models have contributed to the ambiguity of the meaning of truth, thus generating challenges when verifying the authenticity of evidence.
On one hand, GenAI images and videos had a role in thinning one’s trust in what we see and hear in digital media. On the other hand, these models have accelerated innovation. To ensure safe usage and mitigate or prevent truth-related challenges, it is necessary to disentangle digital visual and audio content from reality, as seeing can no longer imply believing.
In this session, participants will be invited to discuss how to reconcile the loss of truth by (1) reframing its meaning in the context of AI tools for evidence production; (2) outlining possible solutions and strategies that can be implemented in AI models used for evidence collection and protection.