Increasingly pervasive data about people enables fundamentally new computational research. Simultaneously, changes in scale, scope, speed, and depth of data availability require reconsideration of ethics for computational research. Much work addressing ethics for big and pervasive data proceeds from first principles, applying traditional tenets of research ethics to computational data research. This work has hit roadblocks caused by a lack of empirical knowledge of the variables at play in computational research environments. The proposed collaborative research project addresses this gap by answering questions such as: How can the risks of pervasive data be quantified, ameliorated, and communicated? What factors impact willingness to contribute data to research? How do computational researchers with diverse methods and backgrounds address core research ethics values such as safety, autonomy, and justice? How are regulators adjusting to the new burdens they face in governing computational research? Just as computational research increasingly relies on assemblages of pervasive data, attention to research ethics must be equally pervasive, encompassing multiple perspectives, stakeholders, and approaches.
September 2017 - August 2021
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