Artificial intelligence (AI) is no longer a back-office analytical tool or niche research subject. It is now generating content that shapes what billions of people see, hear, and believe every day. From AI-generated text to hyper-realistic synthetic video, generative AI has ushered in an era of synthetic media that is simultaneously creative and disruptive. Among the most consequential manifestations of this phenomenon are deepfakes. AI-generated or altered videos, images, and audio that can portray people saying or doing things they never did. While deepfakes have been widely discussed in recent years, the deeper and more strategic risk lies not in the existence of these artifacts, but in the lack of governance infrastructure capable of managing their systemic impact on trust, institutions, and society. In short, traditional AI governance frameworks focus too narrowly on model risk and not enough on what happens when AI produces content that shapes public perception, decision-making, and social norms.
1. The Limits of Traditional AI Governance
Most foundational AI governance frameworks, whether academic, corporate, or regulatory, emphasize internal model characteristics such as bias mitigation, transparency, privacy compliance, and testing procedures. These frameworks are necessary, but they address only the development and deployment of AI models, not the societal impact of the artifacts they produce. When AI models generate content that is indistinguishable from reality, new risk vectors emerge:
- Disinformation that undermines public trust
- Impersonation and identity manipulation
- Legal disputes over liability and attribution
- Corrosion of shared epistemic ground
- Deepfake content proliferating in politics, media, and personal contexts
Scholars argue that this evolution is more than incremental; it is a shift in how information is created, shared, and verified. Research indicates that generative AI threatens to erode verification practices and institutional trust, especially when synthetic content becomes ubiquitous and hard to audit.