Algorithmic transparency is the degree to which an algorithmic system’s data, design, operation, and decision processes are understandable and inspectable. It is a central goal of responsible AI governance, alongside fairness, privacy, data protection, and human oversight. section 10.33
Transparency supports accountability, but it can conflict with proprietary intellectual property and competitive advantage. Companies may withhold details about how their AI systems are built, leaving a gap between public-interest goals and voluntary corporate disclosure. section 10.28 section 10.33
Algorithmic transparency appears within broader efforts to govern AI by:
- Addressing shared concerns about how AI systems are developed, deployed, and used. section 10.28
- Supporting mechanisms of accountability when voluntary self-policing does not provide sufficient public safeguards. section 10.33
