| Abstract: |
Increased utilization of artificial intelligence (AI) and machine learning (ML) in genomic medicine and genetic counseling necessitates a well-trained workforce. However, research on the attitudes toward and uptake of AI/ML education among genetic counseling graduate programs (GCGPs) is limited. This mixed-methods study investigated the attitudes, preparedness, and future plans of GCGP leadership toward the integration of AI/ML into curricula and its effect on core competency proficiency. In Phase 1, a nationwide survey gathered quantitative responses from 15 GCGP leaders holding diverse academic positions in genetic counseling program curriculum development. There were mixed perceptions about AI/ML integration into curricula, despite frequent encounters with these technologies in academic settings. Respondents viewed AI/ML as least impactful on interpersonal, psychosocial, and counseling skills within the Accreditation Council for Genetic Counseling (ACGC) competencies, highlighting the value of human expertise in these areas. Phase 2 explored the goals, logistics, and barriers of incorporating AI/ML into GCGP curricula over the next 5 years. A second nationwide survey collected demographic information from 18 respondents, of which 5 were interviewed. Reflexive thematic analysis identified nine key themes: Resources and Training for AI/ML Integration, Motivations for AI/ML Integration, Confidence in Leadership Foresight, Formats and Applications of AI/ML Education in GCGPs, Stages of AI/ML Integration, Barriers to AI/ML Integration, Trade-offs to new Curricula, Interpreting Competency Requirements, and Relevant Content and Contexts for Learning. Interviewees highlighted the need for support in the form of resources, training, and guidelines for AI/ML applications in genetic counseling. This study uncovers opportunities for enhancing integration of AI/ML in genetic counseling education, emphasizing the importance of collaboration among organizations, professional societies, and topic experts. Developing a competency framework specific to AI/ML in genetic counseling could promote tool development and dissemination, ultimately increasing the impact of GCGPs in this evolving field. © 2025 Elsevier B.V., All rights reserved. |
