Aims

What am I hoping to achieve with this initiative?

  • To examine the socio-legal issues raised by AI, machine learning and algorithmic technologies in web-based mental health initiatives.

  • To examine the legal and non-legal obligations of entities designing and deploying algorithmic systems in the mental health context, and the rights of user-subjects of these systems, and how those obligations and rights can be protected and enforced.

  • To bring new perspectives on the fundamental rights dimension of web-based, data-driven technologies in the mental health context. This includes horizontal relationships (between private parties) and vertical relationships (between individuals and the state, be it represented by law enforcement or by public administration).

  • To provide new understanding of the medico-legal issues and develop a set of principles to guide legal frameworks for internet-based mental health technologies that use algorithmic technology.

  • To improve knowledge about emerging issues with algorithmic decision systems in internet-based mental health interventions among those most affected: people who have experienced mental health crises themselves, and who advocate as users of services and for persons with mental health conditions more generally.

  • To promote responsible public governance of algorithmic technologies in responding to people in distress and supporting people with psychosocial disability.

What do I hope to produce by the end of 2020?

  • A scoping review that surveys formal and ‘grey’ literature on AI, machine learning and other algorithmic technologies used in mental health interventions. The search could include industry reports, policy documents, media analysis, mental health organisation materials, as well as the scholarly literature. The aim is to develop a provisional taxonomy of digital health technology—essentially a map of existing and emerging technologies.

    • One part of this resource is available here.

    • A more systematic review of the scholarly literature on the use of web-based, algorithmic technologies in mental health care is underway.

  • The convening of a diverse Global Advisory Panel consisting of primarily service user and survivor advocates, particularly those in prominent advocacy roles who have an interest in the emerging issues of internet-based, machine learning mental health interventions.

  • A Project Website, which updates interested users, and posts research findings in an engaging and accessible way.

  • An iterative list of major human rights issues that emerge with the major forms of technology that are emerging. This list will also be complemented by insights from interviews I will undertake with leading researchers and commentators, including 3-4 individuals who have used internet-based, machine learning mental health technologies.

  • A research brief examining the relevant legal responses in the European Union, the United States and Australia.

  • Amended papers proposing principles for (1) users and (2) providers of internet-based, machine learning mental health technologies.

  • A summarising, globally relevant, open-access journal article on key principles and corresponding legal measures for addressing the risks and promise of internet-based, machine learning mental health technologies.

  • Policy briefs that summarise key issues for governing bodies, professional associations, and user/survivor organisations.

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