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Co-authored by Jill Noorily, Mason Granof, and Kathryn Ledley at the Division of Digital Psychiatry at BIDMC.
This post is part 2 of a series.
A patient you’ve been seeing for a few weeks comes in looking noticeably worse. She is presenting with symptoms of depression and grief. She hasn’t been sleeping, she’s withdrawn from coworkers and family, and she’s isolating herself, explaining that “No one else gets me.” She slowly reveals that these changes began after she lost access to her AI chatbot companion following a system reset. She had spent the last 3 months talking daily with the chatbot for emotional support and daily life companionship. She tells you she’s been rereading their conversations because she doesn’t want to “lose the sound” of how he talked to her.
We used this hypothetical case in our Society of Digital Psychiatry AI Clinical Learning Collaborative. In this group, clinicians from across the globe came together to discuss approaches and insights for navigating patient AI use. Responding to the example, some clinicians first thought about grief. Others saw depression, dependence, social isolation, or delusional thinking. We spent less time deciding which label was most prominent and more time discussing how to approach the patient in front of us.
Approaches that clinicians agreed on:
- Avoid stigma and judgment: Approach the conversation with curiosity instead of skepticism. Even mild disapproval can shut these disclosures down quickly. Patients are often unsure how their clinician will react. An open, accepting approach makes it easier to understand what role AI is playing in their life.
- Take an AI History: Take an AI history just like you would a medication or substance use history. What chatbot or app are you using? How often do you use it? What do you usually use it for? Does it have a name or personality? Did it remember previous conversations, or did you start fresh each time?
- React to the feelings first: Acknowledge the emotion before trying to explain it. Validating the experience makes it easier to have an honest conversation about the chatbot and the role it was playing.
- AI relationships reveal unmet needs: Ask what need the chatbot was meeting. For many patients, AI companionship is filling a gap that already existed, so redirecting to use their other support structures might not be helpful; they turned to AI because their other support was not meeting their needs. This can be a good way to explore that.
The Type of Chatbot Matters:
Different products are optimized for different objectives, and those design choices shape both the potential benefits and the potential risks.
- Companion chatbots: designed to foster ongoing relationships. They often feature persistent memory, customizable personalities, and conversations that continue over time (e.g., Replika, Character.AI). Because engagement is a primary design goal, these systems may encourage emotional attachment and prolonged use. Clinicians may want to assess for excessive reliance, reinforcement of distorted beliefs through sycophantic responses, withdrawal from offline relationships, and romantic or sexual interactions, particularly among younger users.
- General-purpose chatbot: designed to answer questions, generate content, and support a wide range of everyday tasks (e.g., ChatGPT, Claude, Gemini). Patients may use them for emotional support, problem solving, or health information, even though that is not their sole purpose. Rather than relationship-building, concerns often center on overreliance, misplaced confidence in the model’s advice, cyclical reassurance seeking, and creating maladaptive mental health coping skills.
- Mental health-specific chatbots: designed with therapeutic intentions and often incorporate elements of evidence-based interventions (e.g., Wysa, Youper). These tools raise different clinical questions: Is the patient seeking diagnostic or medication advice beyond the app’s intended scope? Has AI begun to substitute for contact with clinicians or other sources of care?
Scale
This hypothetical patient is one of many who are affected by the loss of their AI companion. There are large online communities, many on Reddit, that act as a place to connect over AI companionship (r/MyBoyfriendIsAI, r/MyGirlfriendIsAI, r/AIRelationships, r/AIPartners). When a model changes, those communities often fill with people describing grief, anger, betrayal, and loss. Knowing these communities exist and exploring them can help clinicians better understand how patients use chatbots and to get insights into how communities discuss this. Is your patient active in these spaces? Are they finding a connection there?
For many patients, these tools are filling a void. They may turn to them during lonely periods, use them to practice difficult conversations, or rely on them for emotional support and help with everyday life. Understanding what role the chatbot is playing makes it easier to determine whether it is becoming a source of risk, serving as a useful support, or both. One of the recurring conversations in our Learning Collaborative was how to help patients benefit from these tools while recognizing and reducing potential harms.
What’s Next
We wanted to make those conversations available to more people. The Society of Digital Psychiatry and the Division of Digital Psychiatry turned the material into a free interactive course at ai-digital-literacy.net. The content comes from the same discussions we had in the collaborative and is designed to keep changing with the technology.
If you work with patients using AI, we encourage you to take the free interactive training.
