The Risks Posed by AI-Powered Mental Health Chatbots
Introduction
The use of digital information and communication technologies for healthcare access has been on the rise in recent times. Mental health care is increasingly being provided through online platforms by remote practitioners, and even by AI-powered chatbots, which use natural language processing (NLP) and machine learning (ML) processes to simulate conversations between the platform and a user. Thus, AI chatbots can provide mental health support from the comfort of the home, at any time of the day, via a mobile phone. While this has great potential to enhance the mental health care ecosystem, such chatbots can present technical and ethical challenges as well.
Background
According to the WHO’s World Mental Health Report of 2022, every 1 in 8 people globally is estimated to be suffering from some form of mental health disorder. The need for mental health services worldwide is high but the supply of a care ecosystem is inadequate both in terms of availability and quality. In India, it is estimated that there are only 0.75 psychiatrists per 100,000 patients and only 30% of the mental health patients get help. Considering the slow thawing of social stigma regarding mental health, especially among younger demographics and support services being confined to urban Indian centres, the demand for a telehealth market is only projected to grow. This paves the way for, among other tools, AI-powered chatbots to fill the gap in providing quick, relatively inexpensive, and easy access to mental health counseling services.
Challenges
Users who seek mental health support are already vulnerable, and AI-induced oversight can exacerbate distress due to some of the following reasons:
- Inaccuracy: Apart from AI’s tendency to hallucinate data, chatbots may simply provide incorrect or harmful advice since they may be trained on data that is not representative of the specific physiological and psychological propensities of various demographics.
- Non-Contextual Learning: The efficacy of mental health counseling often relies on rapport-building between the service provider and client, relying on circumstantial and contextual factors. Machine learning models may struggle with understanding interpersonal or social cues, making their responses over-generalised.
- Reinforcement of Unhelpful Behaviors: In some cases, AI chatbots, if poorly designed, have the potential to reinforce unhealthy thought patterns. This is especially true for complex conditions such as OCD, treatment for which requires highly specific therapeutic interventions.
- False Reassurance: Relying solely on chatbots for counseling may create a partial sense of safety, thereby discouraging users from approaching professional mental health support services. This could reinforce unhelpful behaviours and exacerbate the condition.
- Sensitive Data Vulnerabilities: Health data is sensitive personal information. Chatbot service providers will need to clarify how health data is stored, processed, shared, and used. Without strong data protection and transparency standards, users are exposed to further risks to their well-being.
Way Forward
- Addressing Therapeutic Misconception: A lack of understanding of the purpose and capabilities of such chatbots, in terms of care expectations and treatments they can offer, can jeopardize user health. Platforms providing such services should be mandated to lay disclaimers about the limitations of the therapeutic relationship between the platform and its users in a manner that is easy to understand.
- Improved Algorithm Design: Training data for these models must undertake regular updates and audits to enhance their accuracy, incorporate contextual socio-cultural factors for profile analysis, and use feedback loops from customers and mental health professionals.
- Human Oversight: Models of therapy where AI chatbots are used to supplement treatment instead of replacing human intervention can be explored. Such platforms must also provide escalation mechanisms in cases where human-intervention is sought or required.
Conclusion
It is important to recognize that so far, there is no substitute for professional mental health services. Chatbots can help users gain awareness of their mental health condition and play an educational role in this regard, nudging them in the right direction, and provide assistance to both the practitioner and the client/patient. However, relying on this option to fill gaps in mental health services is not enough. Addressing this growing —and arguably already critical— global health crisis requires dedicated public funding to ensure comprehensive mental health support for all.
Sources
- https://www.who.int/news/item/17-06-2022-who-highlights-urgent-need-to-transform-mental-health-and-mental-health-care
- https://health.economictimes.indiatimes.com/news/industry/mental-healthcare-in-india-building-a-strong-ecosystem-for-a-sound-mind/105395767#:~:text=Indian%20mental%20health%20market%20is,access%20to%20better%20quality%20services.
- https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2023.1278186/full