Journal article : Review
Advancing neurotech justice in youth digital mental health: insights from an interdisciplinary and cross-generational workshop
- Abstract:
- Researchers and clinicians are increasingly looking to leverage artificial intelligence (AI) and digital tools to improve psychiatric care. Of particular promise is addressing the youth mental health crisis. Yet, the introduction of AI-enabled digital technologies for psychiatric treatment of young adults raises a host of ethical, legal, and societal issues (ELSI). To provide guidance in addressing these issues, we convened a two-day meeting at the Radcliffe Institute for Advanced Study at Harvard University: Advancing Neurotech Justice in Mental Health: Insights from an Interdisciplinary and Cross-Generational Workshop. The meeting brought together a diverse cohort of 17 experts and 5 students from various fields and different countries. In partnership with the MIT Critical Data team, the workshop engaged participants in an interactive Prompt-a-Thon to explore first-hand the potential benefits, biases, and harms related to the use of Large Language Model chatbots in mental health care. This Perspective reports on five principles of digital psychiatry deployment that the workshop participants determined to be the most essential: ensuring accuracy, remaining human-centric, promoting just access, protecting privacy, and providing transparency. We place these five principles within a “Neurotech Justice” framework and discuss how guardrails can be built to promote neurotech justice in digital psychiatry.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.3MB, Terms of use)
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- Publisher copy:
- 10.1038/s44277-025-00052-x
Authors
- Publisher:
- Springer Nature [academic journals on nature.com]
- Journal:
- NPP—Digital Psychiatry and Neuroscience More from this journal
- Volume:
- 4
- Issue:
- 1
- Article number:
- 7
- Publication date:
- 2026-04-08
- Acceptance date:
- 2025-12-08
- DOI:
- EISSN:
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2948-1570
- ISSN:
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2948-1570
- Language:
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English
- Keywords:
- Subtype:
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Review
- Pubs id:
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2405997
- Local pid:
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pubs:2405997
- Source identifiers:
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3934299
- Deposit date:
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2026-04-09
- ARK identifier:
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Terms of use
- Copyright date:
- 2026
- Licence:
- CC Attribution (CC BY)
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