Privacy and brain-computer interfaces: identifying potential privacy disruptions
Brain-Computer Interfaces (BCIs) interpret neural activity, applying it to the control of external devices. As BCIs approach market viability, ethical implications come under consideration. This paper identifies potential privacy disruptions. BCI literature is reviewed in order to identify a BCI typology likely to support a privacy analysis. The typology describes the active, reactive, passive and hybrid types of BCI and, where possible, includes examples that are further classified as existing, prospective or speculative. A review of privacy theory supports an analysis that juxtaposes privacy theory and BCI technologies. The analysis finds that while all four types of BCI have potential for disrupting privacy, disruptions are more likely to arise from the use of reactive, passive and hybrid BCIs. Limitations and directions for future research close the paper.
© ACM, 2016. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in http://doi.acm.org/10.1145/2908216.2908223
Citation : Wahlstrom, K., Fairweather, N.B. and Ashman, H. (2016) Privacy and brain-computer interfaces: identifying potential privacy disruptions. ACM SIGCAS Computers and Society, 46 (1), pp. 41-53
Research Group : Centre for Computing and Social Responsibility
Peer Reviewed : Yes