Automating dynamic consent decisions for the processing of social media data in health research
MetadataShow full item record
Social media have become a rich source of data, particularly in health research. Yet, the use of such data raises significant ethical questions about the need for the informed consent of those being studied. Consent mechanisms, if even obtained, are typically broad and inflexible, or place a significant burden on the participant. Machine learning algorithms show much promise for facilitating a ‘middle ground approach: using trained models to predict and automate granular consent decisions. Such techniques, however, raise a myriad of follow-on ethical and technical considerations. In this paper, we present an exploratory user study (n= 67) in which we find that we can predict the appropriate flow of health-related social media data with reasonable accuracy, while minimising undesired data leaks. We then attempt to deconstruct the findings of this study, identifying and discussing a number of real-world implications if such a technique were put into practice
Norval , C & Henderson , T 2020 , ' Automating dynamic consent decisions for the processing of social media data in health research ' , Journal of Empirical Research on Human Research Ethics , vol. 15 , no. 3 , pp. 187-201 . https://doi.org/10.1177/1556264619883715
Journal of Empirical Research on Human Research Ethics
Copyright © 2019 the Author(s). This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1177/1556264619883715
DescriptionFunding: This work was supported by the Wellcome Trust [UNS19427].
Items in the St Andrews Research Repository are protected by copyright, with all rights reserved, unless otherwise indicated.