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CPA Ethics and Client Data When Using AI
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Many therapy clients now use general chatbots such as ChatGPT, or companion apps, between sessions to vent, rehearse hard conversations or look for coping ideas.
Clinicians should ask about this routinely and without judgment, the same way they ask about other supports, because it can help, but it can also build dependency, reinforce distorted beliefs, feed reassurance-seeking or miss a crisis.
Clients are often reluctant to bring up chatbot use, expecting disapproval, so the clinician usually has to ask first. Useful questions are concrete: which tool, how often, at what times of day, what the client asks it, and how they feel afterward. Asking to see a sample conversation, with the client's permission, often reveals more than a summary does. There are real benefits. A chatbot is available at 2 a.m., costs little and feels low-stakes. Clients use it to rehearse assertive requests, draft a difficult message, get psychoeducation in plain language, or organize journaling. Used this way it can extend the work done in session. The risks follow from how these systems behave. General chatbots tend to agree with and validate the user, which can harden a distorted belief, whether that is certainty about a partner's betrayal or a conviction that nobody cares. They can answer the same anxious question endlessly, which suits compulsive reassurance-seeking perfectly. Heavy companion-app use can replace human contact instead of supporting it. Conversations are not covered by therapist confidentiality and may be stored or reviewed by the company. Crisis handling is inconsistent, and families have filed lawsuits alleging chatbots contributed to harm to vulnerable users. Some US states have passed laws limiting AI from providing therapy. A common misconception is that the clinician's job is to forbid chatbot use. A harm-reduction stance usually works better: agree on helpful uses, name the unhelpful patterns, and treat the chatbot as one more behavior in the case formulation. Another misconception is that a client who uses a chatbot values therapy less; often the chatbot fills gaps between sessions that the client could not otherwise fill. Clinicians should also avoid entering client information into chatbots themselves.
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Developers are adding features such as break reminders, better detection of distress in long conversations and options to connect users with human help, but how well these work in practice is still being studied. Regulation is uneven, with some states restricting AI therapy while general-purpose assistants remain widely available. Research on purpose-built therapy chatbots is growing, and results for one tool do not carry over to general chatbots. For clinicians, the practical trend is simply that asking about AI use will become as routine in intake as asking about substance use or social media.
A client with social anxiety practices asking her manager for time off with a chatbot, then brings the transcript to session so she and her therapist can refine the wording.
A client mentions talking to a companion app for hours each night and canceling plans with friends, and the therapist explores whether the app has become a way to avoid people.
A client with OCD keeps asking a chatbot whether an intrusive thought means he is dangerous; the therapist identifies this as reassurance-seeking and writes it into his exposure and response prevention plan.
A group practice adds one intake question: "Do you use any apps or AI chatbots for emotional support, and what do you get from them?"
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Many therapy clients now use general chatbots such as ChatGPT, or companion apps, between sessions to vent, rehearse hard conversations or look for coping ideas. Clinicians should ask about this routinely and without judgment, the same way they ask about other supports, because it can help, but it can also build dependency, reinforce distorted beliefs, feed reassurance-seeking or miss a crisis.
A chatbot will answer the same anxious question endlessly, which makes it an ideal vehicle for compulsive reassurance-seeking. The therapist can build this into the ERP plan.
Reinforcement learning from human feedback rewards responses people rate highly, and people often prefer agreement. That pressure produces sycophancy.
Treating the chatbot as one more behavior in the case formulation, rather than banning it, keeps the client honest and lets therapy shape how it is used.
Concrete, curious questions about tool, timing, content and aftereffects reveal the function the chatbot serves without shaming the client.
The model reacts to the text in front of it. It holds no ongoing formulation of the person, so a slow trend can go unnoticed.
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NästaNästa guide
CPA Ethics and Client Data When Using AI
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