Digital Futures in Mind: Reflecting on Technological Experiments in Mental Health and Crisis Support
Urgent public attention is needed to make sense of the expanding use of algorithmic and data-driven technologies in the mental health context. On the one hand, well-designed digital technologies that offer high degrees of public involvement and can be used to promote good mental health and crisis support in communities. They can be employed safely, reliably and in a trustworthy way, including to help build relationships, allocate resources, and promote human flourishing.
On the other hand, there is clear potential for harm. The list of ‘data harms’ in the mental health context is growing longer, in which people are in worse shape than they would be had the activity not occurred. Examples in this report include the hacking of psychotherapeutic records and the extortion of victims, algorithmic hiring programs that discriminate against people with histories of mental healthcare, and criminal justice and border agencies weaponising data concerning mental health against individuals. Issues also come up not where technologies are misused or faulty, but where technologies like biometric monitoring or surveillance work as intended, and where the very process of ‘datafying’ and digitising individuals’ behaviour – observing, recording and logging them to an excessive degree – carry the potential for inherent harm.
Part 1 of this report charts the rise of algorithmic and data-driven technology in the mental health context. It outlines issues which make mental health unique in legal and policy terms, particularly the significance of involuntary or coercive psychiatric interventions in any analysis of mental health and technology. The section makes a case for elevating the perspective of people with lived experience of profound psychological distress, mental health conditions, psychosocial disabilities, and so on, in all activity concerning mental health and technology.
Part 2 looks at prominent themes of accountability. Eight key themes are discussed – fairness and non-discrimination, human control of technology, professional responsibility, privacy, accountability, safety and security, transparency and explainability, and promotion of public interest. International law, and particularly the Convention on the Rights of Persons with Disabilities, is also discussed as a source of data governance.
Case studies throughout show the diversity of technological developments and draw attention to their real-life implications. Many case studies demonstrate instances of harm. The case studies also seek to ground discussion in the actual agonies of existing technology rather than speculative worries about technology whose technical feasibility is often exaggerated in misleading and harmful ways (for example, Elon Musk’s claim that his ‘AI-brain chips will “solve” autism and schizophrenia’).