Redefining Data Transparency: A Multidimensional Approach

Elisa Bertino, Shawn Merrill, Alina Nesen, Christine Utz

IEEE Computer, Jan. 2019, pp. 16-26, vol. 52


Abstract

The use of big data combined with powerful machine-learning algorithms raises major concerns over potential adverse effects. Consequently, data transparency is critical for many data-intensive applications. We provide a comprehensive definition, elaborate on various concerns, and articulate an initial road map for critical research challenges.

[IEEE] [DOI]

tags: Data Privacy, data transparency, law, machine learning