Addressing the Growing Need for Algorithmic Transparency

Today, many organizations use personal data and algorithms for ads, recommendations, and decisions. However, some have expressed concern that this use negatively impacts individual privacy and poses a risk to individuals and society. In response, many have called for greater algorithmic transparency; that is, for organizations to be more public and open about their use of personal data and algorithms. To better understand algorithmic transparency, we reviewed the literature and interviewed 10 experts. We identified the factors that influence algorithmic transparency, the Association for Computing Machinery's principles for ensuring that one uses personal data and algorithms fairly, and recommendations for company best practices. We also speculate about how personal data and algorithms may be used in the future and suggest research opportunities.