Framing Transparency as AI Races on Down the Road at Double Exponential Speed

AI Transparency is a concept centered on openness, comprehensibility, and accountability in technological systems. In the context of AI, transparency refers to the extent to which the inner workings and decision-making processes of AI systems are made accessible and understandable to users and other stakeholders. This includes insights into the data training, algorithms employed, and the rationale behind specific decisions made by AI systems. The goal is to ensure these systems can be scrutinized and trusted, especially when their decisions significantly impact individuals and society. 

Two new reports have been released to evolve the early conceptual phase of “AI Transparency” into a structural implementation that is eventually fully operational.  The Harvard Kennedy School’s Shorenstein Center on Media, Politics, and Public Policy and Microsoft’s Corporate Social Responsibility (CSR) thought leadership and research efforts released these recent reports, “Documentation Framework for AI Transparency” and a “2024 Responsible AI Transparency Report”, respectively.