top of page

Ethical Considerations with AI-Integrated Emotional Wellness in Mental Health Care


by Mark D. Lerner, Ph.D.

Chairman, The National Center for Emotional Wellness


AI-Integrated Emotional Wellness (AIEW) addresses the intersection of the cognitive capabilities of artificial intelligence (AI) and human emotions. One area where AIEW shows great potential is in supplementing the provision of mental health care—particularly with its ability to provide immediate support across geographical locations at little or no cost to the user. However, it's critical to focus on the ethical considerations of AIEW as they apply to mental health care. By addressing these concerns, we can ensure that technology is utilized responsibly, providing the best possible support for users.


AI can never replace the professional practice of psychiatry, psychology, social work, or other mental health professions. The uniqueness of people will always surpass the rapidly growing cognitive abilities of computers. Even so, AIEW provides guidance on how to supplement traditional face-to-face care with the additional support of AI and an understanding of the ethics of doing so.


One significant ethical consideration is privacy and data protection. Research has focused on safeguarding personal and sensitive information when utilizing AI technologies (Cheung et al., 2020). When users engage with AIEW tools, their emotional and mental health data may be collected. Establishing privacy policies is essential to ensuring that this data remains confidential and is not misused or accessed without consent. Additionally, informed consent is crucial—users should know how their data will be collected, used, and stored. AI companies should also stay apprised of applicable laws; careful consideration should be given as to what user information is retained. Furthermore, cybersecurity must remain top of mind, especially relating to such personal matters.


Transparency and explainability are also key ethical concerns in the application of AIEW in mental health care. Users should understand how AI algorithms are making decisions and providing recommendations. The explainability of AI systems ensures that users can trust the technology and have insight into how it operates. AI researchers, engineers, architects, and developers should design AI models that provide clear explanations for the generated recommendations or advice, enabling users to understand the rationale behind the system's suggestions (Holzinger et al., 2020). This transparency helps build trust between users and AI systems, reducing potential ethical dilemmas and avoiding cases of blind reliance.


Another significant ethical concern is bias and discrimination. Biases and prejudices can unintentionally be embedded within AI systems if trained on biased datasets (Holzinger et al., 2020). Emotional wellness is a deeply personal and diverse area where gender, culture, language, and other attributes influence individual experiences. Therefore, it's essential to ensure that AI algorithms are trained with diverse and representative datasets and are regularly audited for potential biases. By addressing issues related to bias and discrimination, AIEW tools can offer inclusive support for users from diverse populations.


Additionally, responsibility and accountability arise when using AIEW tools. Who is ultimately responsible if something goes wrong? While technology can provide valuable support, it must not replace traditional face-to-face interpersonal human interaction. Users must be aware of the limitations of AI and understand that these tools are intended to supplement rather than replace professional support. As I have shared, mental health professionals should play an integral role in designing AIEW systems, ensuring that ethical standards are maintained and that users receive appropriate care.


AIEW holds tremendous potential for improving mental health. However, it's crucial to address the ethical considerations accompanying this development. Privacy and data protection, transparency and explainability, bias and discrimination, and responsibility and accountability must be carefully examined to ensure that AIEW technologies are implemented ethically and responsibly. By addressing these concerns, we can harness the power of AI to provide comprehensive support for users' emotional well-being while maintaining the highest ethical standards.








bottom of page