Human Judgment, Machine Assistance: AI in Clinical Practice
Live Event

Human Judgment, Machine Assistance: AI in Clinical Practice

Thu, Feb 25th, 2027
11:00am – 2:15pm US Eastern Time
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About the Event

Artificial intelligence has moved quickly from the margins of mental health practice into its daily routines. Clinicians now encounter AI in ambient scribes that draft progress notes, electronic health record features that summarize charts or flag risk, general-purpose chatbots used to draft letters and treatment plans, and consumer apps and companion chatbots that clients use between sessions. These tools can save time and extend access, but they can also fabricate information, reproduce bias, flatter rather than challenge, and expose confidential client information. Clinicians are left to decide, often without guidance, which tasks AI can safely support and which must remain in human hands.

Using real-world case examples, this workshop helps participants critically evaluate where AI can support clinical work and where professional judgment must remain central. Participants will examine how generative and predictive AI tools actually work, review current evidence on their benefits and failure modes (including hallucination, sycophancy, stigma, algorithmic bias, and automation bias), and apply professional codes of ethics, HIPAA, the American Psychological Association’s 2025 ethical guidance, and emerging state law such as Illinois’ Wellness and Oversight for Psychological Resources Act. A case analysis lab asks participants to work through situations drawn from practice: an ambient scribe that inserts a statement a client never made, a supervisee who pastes session notes into a free chatbot, an agency risk-prediction tool that conflicts with clinical assessment, and a client whose companion chatbot reinforced a harmful belief. Participants leave with a structured decision framework, sample informed consent language, and a plan for responsible AI use in their own practice or agency.

Live Event
This live online event will be held as a Zoom Webinar. Attendees will have the option to interact through features such as the Chat and Q&A, but cameras and microphones will not be enabled.

Live Event Instructor

Kathryn Krase

Kathryn Krase

Kathryn Krase, Ph.D., J.D., M.S.W., is a social worker, lawyer, researcher, educator, and expert on professional ethics. She has significant experience as a family law practitioner, social work supervisor, along with more than 20 years of experience in faculty and administrative roles in undergraduate, masters, and doctoral level social work programs in and around New York City.

Dr. Krase is the Principal Consultant for Krase Consulting, in Brooklyn, New York, where she focuses on educating mental and physical health professionals on their general legal and ethical obligations.

She is an expert on the professional reporting of suspected child maltreatment. She has authored multiple books and articles on the subject. She has years of experience consulting with government and community based organizations to develop policy & practice standards.

Target Audience

This live interactive is intended for Behavioral Health and Addictions professionals, including psychologists, social workers, counselors, marriage & family therapists, art therapists, school psychologists, psychoanalysts, music therapists, behavior analysts, school counselors, and addiction counselors. It is appropriate for all levels of knowledge.

Learning Objectives

After taking this activity, you should be able to:

  1. 1 Distinguish clinical and administrative tasks where AI tools can appropriately support practice from tasks that require the independent judgment of a licensed professional, such as risk assessment, diagnosis, treatment decisions, and mandated reporting determinations.
  2. 2 Evaluate AI-generated content for common failure modes, including fabrication, omission, bias, and sycophancy, using a structured review process.
  3. 3 Apply ethical principles, professional codes, and current guidance and law to real-world case examples of AI use in mental health practice.
  4. 4 Identify confidentiality, data security, and informed consent requirements that must be addressed before adopting an AI tool, including business associate agreements and limits of de-identification.
  5. 5 Develop a practice-level plan for responsible AI use that includes client consent language and an approach to discussing clients’ own use of AI.

American Psychological Association. (2025). Ethical guidance for AI in the professional practice of health service psychology.

Blease, C., & Torous, J. (2023). ChatGPT and mental healthcare: Balancing benefits with risks of harms. BMJ Mental Health, 26(1), e300884. https://doi.org/10.1136/bmjment-2023-300884

Dratsch, T., Chen, X., Rezazade Mehrizi, M., Kloeckner, R., Mähringer-Kunz, A., Püsken, M., Baeßler, B., Sauer, S., Maintz, D., & Pinto dos Santos, D. (2023). Automation bias in mammography: The impact of artificial intelligence BI-RADS suggestions on reader performance. Radiology, 307(4), e222176. https://doi.org/10.1148/radiol.222176

Heinz, M. V., Mackin, D. M., Trudeau, B. M., Bhattacharya, S., Wang, Y., Banta, H. A., Jewett, A. D., Salzhauer, A. J., Griffin, T. Z., & Jacobson, N. C. (2025). Randomized trial of a generative AI chatbot for mental health treatment. NEJM AI, 2(4). https://doi.org/10.1056/AIoa2400802

Moore, J., Grabb, D., Agnew, W., Klyman, K., Chancellor, S., Ong, D. C., & Haber, N. (2025). Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. In Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency (pp. 599–627). Association for Computing Machinery. https://doi.org/10.1145/3715275.3732039

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342

Sedlakova, J., & Trachsel, M. (2023). Conversational artificial intelligence in psychotherapy: A new therapeutic tool or agent? The American Journal of Bioethics, 23(5), 4–13. https://doi.org/10.1080/15265161.2022.2048739

Stade, E. C., Stirman, S. W., Ungar, L. H., Boland, C. L., Schwartz, H. A., Yaden, D. B., Sedoc, J., DeRubeis, R. J., Willer, R., & Eichstaedt, J. C. (2024). Large language models could change the future of behavioral healthcare: A proposal for responsible development and evaluation. npj Mental Health Research, 3, Article 12. https://doi.org/10.1038/s44184-024-00056-z

Tierney, A. A., Gayre, G., Hoberman, B., Mattern, B., Ballesca, M., Kipnis, P., Liu, V., & Lee, K. (2024). Ambient artificial intelligence scribes to alleviate the burden of clinical documentation. NEJM Catalyst Innovations in Care Delivery, 5(3). https://doi.org/10.1056/CAT.23.0404

Wellness and Oversight for Psychological Resources Act, Pub. Act 104-0054 (2025).

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The following relevant financial relationships have been disclosed by this activity's planners, faculty, and the reviewer:

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The planners of this activity have reported that they have no relevant financial relationships.

Faculty

There are no known relevant financial relationships to disclose.

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Event Agenda

Agenda times are listed in US Eastern Time. That is 3 hours later than US Pacific Time. The event starts at 8:00am US Pacific Time.

11:00–11:15 AM: 1. Introductions & Framing

Participants’ current AI use and concerns; what “AI” means in practice: generative models, predictive algorithms, ambient scribes, and chatbots; how large language models produce text (prediction, not knowledge)


11:15–11:40 AM: 2. Where Machines Help

Evidence on documentation support and ambient scribes; administrative and psychoeducational uses; measurement-based care; early trial evidence for therapy chatbots and its limits


11:40 AM–12:10 PM: 3. Where Judgment Must Remain Central

Hallucination and omission; sycophancy and the validation of harmful beliefs; stigma in model responses; algorithmic bias; automation bias; risk assessment, diagnosis, and the therapeutic relationship


12:10–12:40 PM: 4. Ethics, Law & Professional Guidance

Competence, informed consent, confidentiality, and justice under professional codes; HIPAA and business associate agreements; limits of de-identification; APA’s 2025 ethical guidance; Illinois’ 2025 Wellness and Oversight for Psychological Resources Act and other emerging state law


12:40–12:55 PM: Break


12:55–1:45 PM: 5. Case Analysis Lab

Small-group and whole-group analysis of real-world cases: an ambient scribe error; AI-drafted treatment plans and diagnostic impressions; a supervisee’s use of a public chatbot; an agency risk-prediction flag; a client’s companion chatbot use; AI and mandated reporting decisions


1:45–2:05 PM: 6. Building Responsible Practice

A decision framework (task, risk, tool, data, consent, review, documentation); sample informed consent language; asking clients about their AI use; elements of a practice or agency AI policy


2:05–2:15 PM: 7. Summary & Questions

Key takeaways; resources; questions and discussion

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