The Challenge of ensuring trust in online content has intensified with the rise of Artificial Intelligence.
While AI technologies offer numerous advantages to society, the widespread accessibility of AI and machine learning tools, particularly generative models and deepfake technologies, allows individuals to create or alter data with relative ease, minimal expense, and heightened realism. Consequently, distinguishing between authentic and fabricated online content is becoming increasingly difficult.
Content Credentials represents a developing technology aimed at addressing this decline in trust. This technology seeks to trace the origin of data, including its source and editing history, thereby facilitating the preservation and verification of authenticity.
AI tools intended to identify synthetic or inauthentic data often prove to be ineffective and unreliable, necessitating additional technical measures to establish layered defenses for organisations, individuals, and society at large. Techniques for content provenance could play a crucial role in enhancing the integrity of information across various systems.
While Content Credentials can assist organisations, systems, and users in making informed choices regarding the data they engage with, they alone will not fully resolve the issue. Nevertheless, as the technology advances, it will enhance systems’ capabilities to assess the authenticity of content more effectively.
