In my view, the foundation for discussions about the use of artificial intelligence in mental health care is not technological capability, but fundamental ethical questions. In light of reports that popular chatbots may fail to recognize suicidal signals, and given that Illinois has become the first U.S. state to ban the use of AI in therapy sessions, we face a crucial dilemma: how can we harness the potential of technology without exposing people to underestimated risks? This is only one of many ethical concerns. Let us not forget about digital stigmatization or social isolation driven by the deepening human dependence on technology.

Skepticism around AI and scientific work

On the other hand, skepticism toward AI in therapy may give way in the face of scientific evidence. A 2023 meta-analysis by Li and colleagues, involving 17,000 patients, showed a statistically significant reduction in depression (Hedges’ g = 0.64) and stress (g = 0.7). The number of scientific studies providing justification for blending therapeutic approaches with technology is growing rapidly.

The mental health support crisis is real

Of course, business is not standing still, and the market is responding to the crisis in mental health care accessibility. Paradoxically, it is precisely this crisis of access to traditional care that drives the development of AI in psychiatry and psychology. Hundreds of millions of people worldwide struggle with mental disorders, yet only a fraction of them have access to professional help when it is truly needed.

Dynamic growth in the AI industry - over 300%

The aforementioned market response is highly dynamic. The value of the AI mental health sector is expected to grow from $1.39 billion in 2023 to a projected $5.08 billion in 2030 (CAGR 24.10%). It is worth stressing that this growth does not stem from speculative venture capital activity, but rather from addressing a genuine social need. To add to this point, 43% of professionals already use AI tools, mainly to support diagnostics and documentation.

Conclusions

In conclusion, broadly understood technology (not only forms directly linked to AI) can address the very social and health challenges that, to a large extent, it also helps to create. In the years ahead, it will or indeed must be employed more widely as a complementary element, enhancing the capacity of mental health professionals. The utilitarian dimension of this statement is dictated by the drastic increase in human needs in this domain. Personally, I direct my research interests toward the concept of the digital phenotype and its application in detecting and preventing mental health issues, and in my work, I place strong emphasis on solving problems rather than creating new ones.

Sources:

1. https://hai.stanford.edu/news/exploring-the-dangers-of-ai-in-mental-health-care
2. https://www.psychiatrist.com/news/illinois-outlaws-ai-in-therapy-sessions/
3. https://www.nature.com/articles/s41746-023-00979-5
4. https://www.grandviewresearch.com/industry-analysis/ai-mental-health-market-report
5. https://www.apaservices.org/practice/news/artificial-intelligence-psychologists-work