Ethical Considerations in the Use of AI for Mental Health Providers
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When & Where:
- Date: Friday, January 29, 2027
- If you cannot attend this workshop on 1/29, you can pre-register for the on-demand version here: https://www.theknowledgetree.org/p/ethical-conside...
- Time: 10:30am - 5:30pm Eastern Time
- CE Hours Included: 6 (please see below for details)
- Location: Live Interactive Webinar ("Synchronous") on Zoom
- Investment: $140 before Friday, January 15th at 5:00pm Eastern Time, $160 after
- Presented by: Emily Mouilso, Ph.D. (see bio below)
- Workshop Recording: A recording of this workshop is available to review for 60 days after the presentation. However, participants must attend live to receive the "Synchronous" CE Certificate.
- Instruction Level: Intermediate
- Target Audience: Psychologists, Counselors, Social Workers, Marriage & Family Therapists
Learning Objectives:
After completing this workshop in its entirety, you will be able to:
- Identify the meaning of the terms artificial intelligence (AI), large language models (LLMs), and related terminology relevant to mental health practice.
- Describe how LLMs are trained and identify ways in which training data, model design, and algorithmic processes can contribute to bias and limitations in AI-generated outputs.
- Identify key regulatory, legal, and ethical considerations related to the use of AI in mental health practice, including potential implications for professional liability.
- Analyze ethical considerations associated with the use of AI in common clinical activities, including documentation, diagnosis, psychological assessment, and treatment.
- Describe the current evidence regarding AI-powered chatbots and discuss potential benefits, limitations, and ethical risks associated with their use in mental health care.
- Describe evidence-informed recommendations and best practices for the responsible, ethical, and clinically appropriate use of AI in mental health practice.
Workshop Description:
How confident are you that the AI you’re already using is ethical, accurate, and safe for clinical practice? Are you worried that you might be missing out on the potential AI can offer your practice?
Artificial intelligence (AI) is rapidly changing the landscape of mental health practice, creating new opportunities while raising important questions about ethics, clinical judgment, privacy, bias, and professional liability. This workshop will provide mental health professionals with a practical foundation in AI, including definitions of AI and related terminology and an overview of how large language models (LLMs) are trained. Particular attention will be given to how training data and model design can introduce bias and how these limitations may affect clinical decision-making and patient care. The workshop will also examine emerging regulatory frameworks and their implications for professional responsibility and liability when AI tools are incorporated into clinical practice. The workshop will explore the intersection of AI, professional ethics, and common clinical activities, including documentation, diagnosis, assessment, and treatment. Participants will review the current evidence regarding AI-powered chatbots and consider the ethical implications of their use by both clinicians and clients. Practical recommendations and best practices for the responsible use of AI in mental health settings will be highlighted throughout. Case studies and interactive questions will encourage discussion, critical thinking, and application of ethical and clinical considerations to real-world scenarios.
Workshop Agenda:
I. Introduction, Orientation, and Current Landscape of AI in Mental Health — 30 minutes
- Introduction, agenda, and workshop disclosures
- Audience survey: professional background and work setting, current use and familiarity with AI
- Why AI matters to mental health professionals
II. AI Fundamentals: Definitions, Terminology, and How AI Works — 50 minutes
- What is artificial intelligence?
- Definitions and historical development of AI
- AI as a technological system rather than a human or human-like entity
- Anthropomorphism and the tendency to attribute human qualities to AI
- Core AI terminology
- Artificial intelligence
- Machine learning
- Supervised learning
- Unsupervised learning
- Neural networks
- Deep learning
- Natural language processing
- Expert systems
- Conversational agents and chatbots
- Large language models (LLMs)
- Generative AI and generative pretrained transformers (GPTs)
- Human-in-the-loop and human-on-the-loop systems
- How LLMs work
- Prediction rather than human-like understanding
- Tokens and token-by-token generation
- Context and probability
- Why fluent output does not necessarily indicate accuracy or understanding
- Technology readiness and limitations of emerging AI technologies
III. How LLMs Are Trained: Data, Bias, and Limitations — 70 minutes
- Overview of the model-training process
- Data collection
- Pre-processing
- Embedding
- Pre-training
- Fine-tuning
- Sources and characteristics of training data
- Publicly available information
- Licensed and copyrighted data
- Curated and synthetic data
- Human decisions involved in AI training
- Data selection and weighting
- Human feedback and fine-tuning
- The "black box" problem
- How bias can enter AI systems
- Missing or nonrepresentative data
- Historical and systemic bias
- Human judgments and values
- Measurement and coding errors
- Dataset shift
- Differences between training and clinical populations
- Changes across settings, populations, technology, and time
- Clinical implications of algorithmic bias
- Diagnosis
- Assessment
- Treatment recommendations
- Health disparities and equity
- Strategies for mitigating bias
- Diverse development and validation teams
- Representation of intended users
- Bias assessment and monitoring
- Human oversight
IV. Regulation, Law, Professional Standards, and Liability — 50 minutes
- Current state of AI regulation
- Rapid technological development versus slower regulatory development
- International approaches
- United States federal regulatory and legal frameworks
- State regulation and emerging legislation
- Organizational policies and institutional accountability
- Professional ethics codes and licensing standards
- Professional liability and AI
- Insurance and risk management considerations
V. Ethics of AI in Mental Health Practice — 50 minutes
- Equity, access and the digital divide
- Algorithmic bias
- Informed consent
- Disclosure of AI use and risks and benefits
- Ongoing versus one-time consent
- Transparency and The AI "black box"
- Privacy and confidentiality
- Data collection and storage
- Data sharing and secondary use
- Data used for model training
- De-identification and potential re-identification
- Vendor privacy policies and terms of service
- Beneficence and non-maleficence
- How models respond in high-risk situations
- How models may inadvertently reinforce and perpetuate psychiatric symptoms
- Competence
- AI literacy
- Deskilling
- Automation bias
- Confirmation bias
VI. AI in Common Mental Health Practice Activities — 90 minutes
- Clinical Documentation
- Diagnosis and Clinical Decision-Making
- AI-assisted diagnostic decision-making
- Potential benefits and limitations
- Psychological Assessment
- AI-assisted assessment and scoring
- AI-assisted interpretation and report generation
- Appropriate versus inappropriate uses
- Validity and evidence for intended use
- Training-data fit and cultural considerations
- Privacy and security of assessment data
- Test security and protection of proprietary materials
- Informed consent and transparency
- Human review and professional interpretation
- Guiding questions for evaluating AI-enhanced assessment tools
- Treatment
- AI as an adjunct versus replacement for clinical care
- Potential applications
- Potential benefits and risks
- AI Chatbots and Mental Health
- Types of AI chatbots
- Why clients use AI chatbots
- Current evidence
- Potential benefits and ethical and clinical concerns
- Clinical assessment of patient chatbot use
- AI Agents with Physically Embodied Presence
- Types of AI agents with physically embodied presence
- AI scribes and automated documentation
- Potential benefits
- Risks and limitations
- Evaluating an AI documentation tool
- Ethical and clinical concerns
VII. Summary, Key Takeaways, and Questions — 20 minutes
- Impact of AI on human interactions
- Ethical considerations of the environmental impacts of AI
- Ethical considerations related to workforce changes
- Review of best practices and general recommendations
- Identification of resources for continued learning
- Final audience questions and discussion
Presented by: Emily Mouilso, Ph.D.
Workshop Schedule (Eastern Time):
- 10:00am - 10:30am | Sign-In and Welcome
- 10:30am - 12:00pm | Session
- 12:00pm - 12:10pm | Break
- 12:10pm - 1:40pm | Session
- 1:40pm - 2:20pm | Lunch Break
- 2:20pm - 3:50pm | Session
- 3:50pm - 4:00pm | Break
- 4:00pm - 5:30pm | Session
- 5:30pm | Continuing Education Certificates Available
6 Ethics CE Hours Included - Details by License Type Below:
- PSYCHOLOGISTS: The Knowledge Tree, A Summit Professional Education Company is approved by the American Psychological Association to sponsor continuing education for psychologists. The Knowledge Tree, A Summit Professional Education Company maintains responsibility for this program and its content. For more detailed information on the current CE ruling in Georgia, or if you are licensed in another state or country, please click here.
- COUNSELORS: The Knowledge Tree, A Summit Professional Education Company has been approved by the National Board for Certified Counselors (NBCC) as an Approved Continuing Education Provider (ACEP), ACEP No. 7153. Programs that do not qualify for NBCC credit are clearly identified. The Knowledge Tree, A Summit Professional Education Company is solely responsible for all aspects of the programs. Please click here for more detailed information.
- SOCIAL WORKERS: The Knowledge Tree, a Summit Professional Education Company, provider #2470, is approved as an ACE provider to offer social work continuing education by the Association of Social Work Boards (ASWB) Approved Continuing Education (ACE) program. Regulatory boards are the final authority on courses accepted for continuing education credit. ACE provider approval period: 1/14/2026-1/14/2027. Social workers completing this course receive 6 ethics continuing education credits. Please click here for more detailed information.
- MARRIAGE & FAMILY THERAPISTS: TKT has applied for approval for this workshop through the Georgia Association for Marriage & Family Therapy (GAMFT). If you are licensed in another state or country, please click here for more detailed information.
Registration: To register for individual workshops, we recommend purchasing the course directly on the workshop's page on our website. If you would like to register for multiple workshops at once and receive our multi-workshop discount (detailed below), you may either complete the Multi-Workshop Registration Form (available HERE) and email it to our Customer Service Team at theknowledgetree@summit.zendesk.com or call them at 404-913-2005 to register over the phone. Workshops worth fewer than 3 CE hours are not eligible for the multi-workshop discount and are therefore not listed on the registration form. Workshop registration for live webinars is open until the time the workshop begins, unless otherwise specified.
Multi-Workshop Discount: There is a 10% discount when registering for two workshops, a 15% discount when registering for three or four workshops, and a 20% discount when registering for five or more workshops. To receive this discount, you must use the Multi-Workshop Registration Form (available HERE). The discount only applies to courses purchased in the same transaction; the discount cannot be applied to courses purchased directly on our website, and cannot be applied retroactively to courses previously purchased. As stated above, courses worth fewer than 3 CE hours are NOT eligible for the multi-workshop discount and are therefore not listed on the registration form.
Refund/Cancellation Policy: If you can no longer attend a workshop you have registered for, you can either receive a credit for another workshop or receive a refund if you are within the refund policy period. Refunds will be given for cancellations received at least five days prior to the workshop. More information about refund/cancellation can be found here.
Attendance Policy: 100% attendance and completion of a course evaluation is required at any CE program in order to receive credit for that CE program. No partial credit is given. Certificates of completion will be available in each attendee’s account once the broadcast has ended and the course evaluation completed.
ADA Requests: We will make every effort to accommodate any reasonable ADA request. Please call or email us at least two weeks prior to the event. Payment and registration are required to fulfill an ADA request.
No Conflict Policy: Neither The Knowledge Tree nor its speakers have received any commercial support for this program or its contents and will not receive any commercial support prior to or during this program.
System Requirements: Live Interactive Webinars are facilitated via Zoom. System requirements for the Zoom platform are linked at our FAQ page.
We are an approved vendor for the U.S. Department of Veterans Affairs for easy reimbursement of educational expenses for VA employees.
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