Regulatory frameworks relating to data privacy and algorithmic decision making in the context of emerging standards on algorithmic bias
By:
Abhik Chaudhuri (Tata Consultancy Services), Adam Leon Smith (Piccadilly Labs), Allison Gardner (Keele University), Linda Gu
(Fresco Partners Ltd.), Malek Ben Salem (Accenture Labs),
Maroussia Lévesque (Attorney)
(Fresco Partners Ltd.), Malek Ben Salem (Accenture Labs),
Maroussia Lévesque (Attorney)
Abstract
This paper examines the current state of the regulatory frameworks relating to the use of personal data and algorithmic decision making in India, the United States of America and the European Union. In conclusion, it outlines how the IEEE P7003 (1) standard can make a unique contribution by narrowing the gap between high-level data protection regimes and implementation roadblocks by providing specific guidelines to developers and users of algorithmic systems.
References:
Smith, A.L., Chaudhuri, A., Gardner, A., Gu, L., Salem, M.B. and Lévesque, M., Regulatory frameworks relating to data privacy and algorithmic decision making in the context of emerging standards on algorithmic bias. 2018.
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