Ethical risk prevention in client generative artificial intelligence (genAI) use: Applying the primary...

Area of Science:

• Psychology
• Ethics
• Artificial Intelligence

Background:

• Clients increasingly use generative AI for emotional support, presenting novel ethical challenges for psychologists.
• AI tools offer accessibility and affordability but carry risks like misinformation, sycophancy, cultural bias, and disruption of the therapeutic alliance.

Purpose of the Study:

• To apply a primary risk-management model to address ethical challenges posed by generative AI in psychological practice.
• To develop a forward-looking, preventive approach for psychologists navigating AI-related ethical dilemmas.

Main Methods:

• Conceptual mapping and application of Crowley and Gottlieb's (2012) primary risk-management model.
• Utilized ethical guidelines from the American Psychological Association (2017) and Chenneville et al. (2024).
• Illustrated the model's application through a worst-case scenario analysis.

Main Results:

• The primary risk-management model provides a structured, five-stage approach (resource accumulation, risk detection, appraisal, management, feedback) for ethical challenges.
• Applying this model can enhance psychologists' ethical alertness and reflexive judgment when dealing with generative AI.

Conclusions:

• Proactive, model-based risk management is crucial for addressing the ethical complexities of generative AI in therapy.
• Recommendations are provided for education, professional policy, and research to enhance preparedness and mitigate harm.