title: Automated Decision-Making and Big Data: Concerns for People With Mental Illness.
abstract: Automated decision-making by computer algorithms based on data from our behaviors is fundamental to the digital economy. Automated decisions impact everyone, occurring routinely in education, employment, health care, credit, and government services. Technologies that generate tracking data, including smartphones, credit cards, websites, social media, and sensors, offer unprecedented benefits. However, people are vulnerable to errors and biases in the underlying data and algorithms, especially those with mental illness. Algorithms based on big data from seemingly unrelated sources may create obstacles to community integration. Voluntary online self-disclosure and constant tracking blur traditional concepts of public versus private data, medical versus non-medical data, and human versus automated decision-making. In contrast to sharing sensitive information with a physician in a confidential relationship, there may be numerous readers of information revealed online; data may be sold repeatedly; used in proprietary algorithms; and are effectively permanent. Technological changes challenge traditional norms affecting privacy and decision-making, and continued discussions on new approaches to provide privacy protections are needed.
authors: Michigan State University College of Human Medicine, Traverse City Campus, 1400 Medical Campus Drive, Traverse City, MI, 49684, USA. monteit2@msu.edu.
authors: Scott
authors: S
authors: Monteith
authors: ChronoRecord Association, Inc., Fullerton, CA, 92834, USA.
authors: Tasha
authors: T
authors: Glenn
mesh_terms: D000465:Algorithms; D003658:Decision Making, Computer-Assisted; D006801:Humans; D001523:Mental Disorders; D018907:Privacy
keywords: Algorithms; Automated decision-making; Big data; Mental illness; Privacy