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Is Big Data the New Stethoscope? Perils of Digital Phenotyping to Address Mental Illness

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Abstract

Advances in applications of artificial intelligence and the use of data analytics technology in biomedicine are creating optimism, as many believe these technologies will fill the need-availability gap by increasing resources for mental health care. One resource considered especially promising is smartphone psychotherapy chatbots, i.e., artificially intelligent bots that offer cognitive behavior therapy to their users with the aim of helping them improve their mental health. While a number of studies have highlighted the positive outcomes of using smartphone psychotherapy chatbots to handle various anxiety related problems no conclusive data illustrate their effectiveness or warrant their use in mental illness diagnosis and treatment settings. Yet smartphone psychotherapy is highly endorsed by experts in the field of mental health research. In this paper, I focus on the specific features of smartphone psychotherapy chatbots intended for the diagnosis and treatment of mental illness and criticize three popular promises; i.e., (i) they enable early diagnosis and intervention through digital phenotyping; (ii) they defy the stigma of mental illness diagnosis and treatment; (iii) they offer increased access to mental health treatment globally. Going against the popular enthusiasm, I argue smartphone psychotherapy chatbots have epistemic and ethical limitations in the diagnosis and treatment of illnesses. In light of these, I encourage researchers, clinicians, policy makers, patients, and caregivers to pause before jumping on the artificial intelligence bandwagon to seek solutions for mental illness on the grounds of these three promises.

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Notes

  1. In 2010, NIMH launched the Research Domain Criteria (RDoC) initiative aimed at developing, for research purposes, new ways of classifying mental disorders based on behavioral dimensions and neurobiological measures. The goal of RDoC is to create a new conceptual framework for psychiatric research that identifies domains of functioning that can be analyzed at several levels, thereby integrating resources from various basic sciences, especially neuroscience, and cognitive science.

  2. Note that researchers working on developing and using this technology in the US must abide by the statues of the Health Insurance Portability and Accountability Act (HIPAA) legislation, which requires data privacy and security provisions for safeguarding medical information. However, if the researchers are not in the US, they may be exempt from such requirements. At this point, there are no universal guidelines.

  3. More could be said here about the dangers of infosecurity: With increased issues of data breaches, we must be very concerned about these chatbot companies using and selling the data of their users. I merely scratched the surface of these issues here, for reasons of space. I hope that further ethical evaluations of the issue of privacy are raised by other philosophers and ethicists as these technologies become more widespread.

  4. In addition, there are further important questions about evidence. For example, some of these apps are marketed directly to consumers, which do not seem to be as vigilant in relaying the existing evidence for their effectiveness or limitations (for example, Woebot, an app that is discussed in Section 3). Whereas others, especially the ones that are developed by clinicians, seek endorsement by therapists for their patients and are thereby more forthcoming about their limitations (for example, MyCompass).

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Acknowledgments

I would like to acknowledge the three anonymous reviewers for providing tremendously helpful feedback on the earlier drafts of this manuscript. I am also grateful for the questions raised by the participants of the Mellon Foundation Sawyer Seminar on “Human Plasticity and Human–Machine Interface” at Boston University where I presented my early thoughts on the topic.

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  1. Department of Philosophy and Classics, University of Texas at San Antonio, 1 UTSA Circle, San Antonio, TX, 78249, USA

    Şerife Tekin

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Tekin, Ş. Is Big Data the New Stethoscope? Perils of Digital Phenotyping to Address Mental Illness. Philos. Technol. 34, 447–461 (2021). https://doi.org/10.1007/s13347-020-00395-7

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