‘AI gone mental’: engagement and ethics in data-driven technology for mental health

References

• AI HLEG. (2019). Ethics Guidelines for Trustworthy AI. Brussels: European Commission.
   Google Scholar
• Artificial Lawyer. (2019a, October 31). UK Government faces court over ‘biased’ visa algorithm. Artificial Lawyer. Retrieved from https://www.artificiallawyer.com/2019/10/31/uk-government-faces-court-over-biased-visa-algorithm/ (Accessed 11 November 2019).
   Google Scholar
• Artificial Lawyer. (2019b, June 4). Create a National Register of Algorithms – Law Society AI Commission. Artificial Lawyer. Retrieved from https://www.artificiallawyer.com/2019/06/04/create-a-national-register-of-algorithms-law-society-ai-commission/ (Accessed 11 November 2019).
   Google Scholar
• Barnett, P., Mackay, E., Matthews, H., Gate, R., Greenwood, H., Ariyo, K., … Smith, S. (2019). Ethnic variations in compulsory detention under the Mental Health Act: A systematic review and meta-analysis of international data. The Lancet Psychiatry, 6(4), 305–317. doi:10.1016/S2215-0366(19)30027-6
   PubMed Web of Science ®Google Scholar
• Bauer, S., & Moessner, M. (2012). Technology-enhanced monitoring in psychotherapy and e-mental health. Journal of Mental Health , 21(4), 355–363. doi:10.3109/09638237.2012.667886
   PubMed Web of Science ®Google Scholar
• Becker, D., van Breda, W., Funk, B., Hoogendoorn, M., Ruwaard, J., & Riper, H. (2018). Predictive modeling in e-mental health: A common language framework. Internet Interventions, 12, 57–67. doi:10.1016/j.invent.2018.03.002
   PubMedGoogle Scholar
• Beresford, P. (2003). It's Our Lives: A short theory of knowledge, distance and experience. London: OSP/Citizen Press.
   Google Scholar
• Bhugra, D., Tasman, A., Pathare, S., Priebe, S., Smith, S., Torous, J., … Ventriglio, A. (2017). The WPA-Lancet Psychiatry Commission on the Future of Psychiatry. The Lancet. Psychiatry, 4(10), 775–818. doi:10.1016/S2215-0366(17)30333-4
   PubMed Web of Science ®Google Scholar
• Borgesius, F.Z. (2018). Discrimination, artificial intelligence and algorithmic decision-making. Strasbourg: Council of Europe.
   Google Scholar
• Bradstreet, S., Allan, S., & Gumley, A. (2019). Adverse event monitoring in mHealth for psychosis interventions provides an important opportunity for learning. Journal of Mental Health, 28(5), 461–466. doi:10.1080/09638237.2019.1630727
   PubMed Web of Science ®Google Scholar
• Brundage, M., Avin, S., & Clark, J. (2018). The malicious use of artificial intelligence: Forecasting, prevention and mitigation. Oxford: University of Oxford.
   Google Scholar
• Callard, F., & Wykes, T. (2008). Mental health and perceptions of biomarker research – possible effects on participation. Journal of Mental Health, 17(1), 1–7. doi:10.1080/09638230801931944
   Web of Science ®Google Scholar
• CII. (2019). Shaping the Future of Medical Records and Protection Insurance. London: Chartered Insurance Institute.
   Google Scholar
• Eubanks, V. (2017). Automating Inequality. New York: St Martin’s Press.
   Google Scholar
• Foley, T., & Woollard, J. (2019). The digital future of mental healthcare and its workforce. London: Health Education England.
   Google Scholar
• Frey, W., Patton, D., Gaskell, M., & McGregor, K. (2018). Artificial intelligence and inclusion: Formerly gang-involved youth as domain experts for analyzing unstructured Twitter data. Social Science Computer Review, 38(1), 1–15. doi:10.1177/0894439318788314
   Web of Science ®Google Scholar
• Fry, H. (2018). How to be Human in the Age of the Machine. London: Black Swan.
   Google Scholar
• Hancock, M. (2018, September 6). My vision for a more tech-driven NHS. Gov.uk. Retrieved from https://www.gov.uk/government/speeches/my-vision-for-a-more-tech-driven-nhs (Accessed 2 August 2019).
   Google Scholar
• Henderson, R. C., Corker, E., Hamilton, S., Williams, P., Pinfold, V., Rose, D., … Thornicroft, G. (2014). Viewpoint survey of mental health service users’ experiences of discrimination in England 2008-12. Social Psychiatry and Psychiatric Epidemiology, 49(10), 1599–1608. doi:10.1007/s00127-014-0875-3
   PubMed Web of Science ®Google Scholar
• HM Government. (2018). Code of conduct for data-driven health and care technology. London: DHSC.
   Google Scholar
• Hodgson, L., Berry, N., Wearne, N., & Ellis, M. (2018, July 6). AI and insurance: Planning for an intelligent future. Insurance Law Tomorrow. Retrieved from https://www.insurancelawtomorrow.com/2018/07/ai-and-the-insurance-planning-for-an-intelligent-future/ (Accessed 2 August 2019).
   Google Scholar
• Hollis, C., Sampson, S., Simons, L., Davies, E. B., Churchill, R., Betton, V., … Tomlin, A. (2018). Identifying research priorities for digital technology in mental health care: Results of the James lind alliance priority setting partnership. The Lancet Psychiatry, 5 (10), 845–854. doi:10.1016/S2215-0366(18)30296-7
   PubMed Web of Science ®Google Scholar
• House of Lords. (2019). Select Committee on Artificial Intelligence Report of Session 2017-19: AI in the UK: Ready, willing and able? London: House of Lords.
   Google Scholar
• IBM. (2017). With AI, our words will be a window into our mental health. IBM Research. Retrieved from https://www.research.ibm.com/5-in-5/mental-health/ (Accessed 2 august 2019).
   Google Scholar
• Islam, M., Hasan, M., Wang, X., Germack, H., & Noor-E-Alam, M. (2018). A systematic review of healthcare analytics: Application and theoretical perspective of data mining. Healthcare, 6(2), 54. doi:10.3390/healthcare6020054
   Web of Science ®Google Scholar
• Kaminski, M.E. (2019). The right to explanation, explained. Berkeley Technology Law Journal, 34, 189–128.
   Google Scholar
• Komorowski, M., Celi, L. A., Badawi, O., Gordon, A. C., & Faisal, A. A. (2018). The artificial intelligence clinician learns optimal treatment strategies for sepsis in intensive care. Nature Medicine, 24(11), 1716–1720. doi:10.1038/s41591-018-0213-5
   PubMed Web of Science ®Google Scholar
• Leightley, D., Williamson, V., Darby, J., & Fear, N. (2019). Identifying probable post-traumatic stress disorder: Applying supervised machine learning to data from a UK military cohort. Journal of Mental Health, 28 (1), 34–41. doi:10.1080/09638237.2018.1521946
   PubMed Web of Science ®Google Scholar
• NewMind. (no date). NewMind Research Roadmap. Retrieved from http://www.newmindnetwork.org.uk/media/1399/newmind-research-roadmap-final.pdf (Accessed 2 August 2019).
   Google Scholar
• Price, C. (2019, November 7). Genomic medicine: A tool for population health? The Kings Fund. Retrieved from https://www.kingsfund.org.uk/blog/2019/11/genomic-medicine-population_health?utm_source=twitter&utm_medium=social&utm_term=thekingsfund (Accessed 11 November 2019).
   Google Scholar
• Rose, D., Fleischmann, P., & Tonkiss, F. (2003). User and carer involvement in change management in a mental health context: Review of the literature. London: NCCSDO.
   Google Scholar
• Rosso, C. (2018, June 13). The future of AI in health care. Psychology Today UK. Retrieved from https://www.psychologytoday.com/gb/blog/the-future-brain/201806/the-future-ai-in-health-care (Accessed 2 August 2019).
   Google Scholar
• RSA. (2018). Artificial intelligence: Real public engagement. London: RSA.
   Google Scholar
• Sayce, L. (2015). From psychiatric patient to citizen revisited. Basingstoke: Palgrave Macmillan.
   Google Scholar
• Schmidt, U., & Wykes, T. (2012). E-mental health – a land of unlimited possibilities. Journal of Mental Health, 21(4), 327–331. doi:10.3109/09638237.2012.705930
   PubMed Web of Science ®Google Scholar
• Szmukler, G. (2015). Compulsion and “coercion” in mental health care. World Psychiatry, 14(3), 259–261. doi:10.1002/wps.20264
   PubMed Web of Science ®Google Scholar
• Szmukler, G., & Appelbaum, P.S. (2008). Treatment pressures, leverage, coercion, and compulsion in mental health care. Journal of Mental Health, 17(3), 233–244. doi:10.1080/09638230802052203
   Web of Science ®Google Scholar
• Szmukler, G., Daw, R., & Callard, F. (2014). Mental health law and the UN Convention on the rights of persons with disabilities international. International Journal of Law and Psychiatry, 37(3), 245–252. doi:10.1016/j.ijlp.2013.11.024
   PubMed Web of Science ®Google Scholar
• Thornicroft, G. (2009). Shunned: Discrimination against people with mental illness. Oxford: Oxford University Press.
   Google Scholar
• Tran, V., Riveros, C., & Ravaud, P. (2019). Patients’ views of wearable devices and AI in healthcare: Findings from the ComPaRe e-cohort. Npj Digital Medcine, 2, Article 53. doi:10.1038/s41746-019-0132-y
   PubMed Web of Science ®Google Scholar
• UNCRPD. (2018). Committee on the Rights of Persons with Disabilities General comment No. 7 (2018) on the participation of persons with disabilities, including children with disabilities, through their representative organizations, in the implementation and monitoring of the Convention. Geneva: UNCRPD.
   Google Scholar
• UNHRC. (2017). Report of the Special Rapporteur on the right of everyone to the enjoyment of the highest attainable standard of physical and mental health. New York: UNHRC
   Google Scholar
• Wellcome Trust. (2018). Ethical, social and political challenges of artificial intelligence in health. London: Wellcome Trust.
   Google Scholar
• Wykes, T. (2019). Racing towards a digital paradise or a digital hell? Journal of Mental Health, 28(1), 1–3. doi:10.1080/09638237.2019.1581360
   PubMed Web of Science ®Google Scholar