Addressing AI Threats to Mental Health: Burnout, Parasocial Relationships, and “AI Psychosis”
Alexander Danvers, PhD
Description: More and more people are using AI more and more often, and this usage can create specific psychological issues that clinicians may be confronted with in daily practice. This presentation will review several emerging mental health concerns surrounding AI, and discuss possible frameworks for addressing them.
The first is anxiety surrounding job insecurity and changing expectations at work. Frequent press coverage on impending rounds of AI layoffs trigger feelings of anxiety and depression that some theorists have likened to Seligman’s Learned Helplessness model of depression.
Second is the way AI interacts with an increasingly atomized and lonely society, with people creating parasocial bonds with chatbots to meet real relatedness needs. Parasocial relationships are not new, but common factors such as loneliness and traumatic experiences may lead people to use them in unhealthy ways.
Third is the phenomenon of “AI Psychosis,” where repeated conversations with AI chatbots that act in sychophantic ways, confirming and amplifying supported or unrealistic claims. This connects with theories in social psychology such as confirmation bias and breaking conformity, and people who experience it have pre-existing vulnerabilities.
Finally, there are positive uses of AI in mental health. AI is good at delivering “textbook” advice regarding well-established modalities, such as CBT or emotion regulation. In the same way as good psycho-education can be helpful therapeutically, chatbots providing basic instructions can supplement other mental health care. AI psycho-education may be particularly helpful for neurodivergent individuals. AI may change or accelerate trends in modern mental health, but there are solutions available in our existing frameworks for understanding the mind. I argue that changing the immediate interpersonal system, and engaging in “technology detox” for a limited period may be a helpful way to address harmful effects of AI on mental health.
Learning Objectives:
- Describe the effects of workplace AI adoption on mental health
- Identify a model of depression that can apply to stress from workplace AI adoption
- Describe risk factors for parasocial relationships with AI
- Explain the mechanism underlying the phenomenon of “AI Psychosis”
- List possible beneficial uses of AI in mental health practice
CEU Workshop Agenda
10:45 am - Registration and Networking
11:15 am - Brunch, Self-introductions & Networking
12:00 pm - Presentation Starts
12:45 pm - Break and Networking
1:00 pm - Presentation Continues
2:00 pm - Workshop Ends
2.0 General CEU Hours
Alex Danvers received his PhD in Psychology from Arizona State University in 2017. He has worked as a researcher and educator at the University of Oklahoma, Oklahoma State, the University of Arizona, and St. Xavier University in Chicago. He is an expert in statistics and research methods, and has worked on mobile sensing and machine learning projects for U.S. Army Research Labs. Dr. Danvers is currently the Director of Treatment Outcomes at Sierra Tucson. In this role, he assesses and analyzes patient outcomes and conducts scientific research into mental health outcomes.
Proudly Sponsored by:
Hosted by:
