Towards Algorithmic Transparency: A Diversity Perspective

Diversity is a key driver of algorithmic transparency needs: The paper argues that diversity in society creates different perspectives and needs that algorithmic systems must account for, making transparency essential—not just as a technical requirement, but as a practical necessity for managing bias across different social groups.

Transparency alone is insufficient without considering multiple perspectives: The authors emphasize that algorithmic transparency must be designed with perspective-taking in mind, meaning systems need to be transparent in ways that are meaningful to diverse stakeholders, not just technical experts or system designers.

Bias and diversity are interconnected problems: Rather than treating bias and diversity as separate issues, the paper positions diversity as central to understanding why bias occurs in algorithms and why transparency solutions must account for different viewpoints and experiences across social groups.

A conceptual framework can guide transparency implementation: The paper proposes a framework to characterize both the problems and solutions in algorithmic transparency, suggesting that organizations can use structured approaches to think through how to make their systems more transparent across different domains and stakeholder groups.

Current research has overlooked diversity in transparency discussions: The paper identifies a gap in existing algorithmic bias research, noting that while transparency and fairness have received significant attention, the role of diversity in shaping transparency needs has been largely neglected in the field.