As generative AI continues to evolve, its potential to reshape mental health care is becoming increasingly clear.

This two-part webinar series explores how Gen-AI is transforming the mental health landscape by opening new paths of support for individuals around the world and expanding access to personalized care on a scale never seen before. As AI becomes integrated into therapy, support systems, and the lives of hundreds of millions of people, it’s essential to understand both the exciting opportunities and the challenges that lie ahead.

Part II takes on the tough questions about ethics in AI and mental health. Topics include privacy concerns, the risk of bias - especially related to culture and the tendency to favor mainstream perspectives that may exclude neurodiverse and underrepresented groups - and the crucial need for transparency and fairness in AI development and use.

Key Discussion Points:

• Privacy and Data Security in AI Mental Health Tools
  How can we protect sensitive user data while leveraging AI for personalized care? What standards should govern storage, sharing, and consent in AI-driven mental health applications?

• Bias, Representation, and Equity
  How can we identify and mitigate biases in AI models that may marginalize neurodiverse individuals, underrepresented cultural groups, or non-mainstream perspectives?

• Transparency and Explainability
  How important is it for users and clinicians to understand how AI makes decisions, and what strategies can ensure AI recommendations are interpretable and trustworthy?

• Ethical Boundaries of AI in Therapy
  Where should we draw the line between AI as a supportive tool versus AI making autonomous decisions in mental health care? What are the risks of over-reliance or misapplication?

• Regulation, Accountability, and Oversight
  Who is responsible when AI fails or causes harm in a mental health context? How can policy, professional guidelines, and ethical frameworks keep pace with rapid technological development?