This systematic literature review explores the ethical challenges associated with implementing artificial intelligence (AI) in the field of clinical psychology, addressing three key research questions: (1) How can issues of privacy, confidentiality, and informed consent be effectively managed? (2) How can algorithmic bias and fairness be assessed and mitigated? (3) What strategies ensure ethical AI design and deployment, focusing on fairness, accountability, and transparency? One hundred peer-reviewed articles are included in the preliminary search. This review highlights the multifaceted ethical landscape of AI in clinical psychology. Findings reveal persistent concerns over data privacy and confidentiality, emphasizing the need for robust security measures and transparent consent processes. Algorithmic bias poses significant risks, potentially exacerbating health disparities and necessitating rigorous bias assessment and mitigation strategies. Furthermore, the review identifies the importance of interdisciplinary collaboration and adherence to ethical guidelines to foster fairness, accountability, and transparency in AI applications. The review concludes with recommendations for developing comprehensive ethical frameworks and best practices that align technological innovation with ethical imperatives. These insights aim to guide practitioners, policymakers, and developers in responsibly integrating AI into mental health care, ensuring that advancements enhance patient outcomes while upholding ethical standards.

Authors:
Rabeea Baloch, Prairie View A&M University, United States
Alaina L. Warrior, Prairie View A&M University, United States
Ayesha F. Baloch, University of Houston, United States

About the Presenter(s)
Rabeea Baloch, LPC, LCDC, NCC, Doctoral Student; Intimate Partner Violence, Post-traumatic Stress Disorder, Trauma, Artificial Intelligence; "The Ethical Utilization of AI in Clinical Psychology: A systemic Review"

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