AI-scending the scope: Perspectives on the integration and utilization of artificial intelligence and machine learning in genetic counseling graduate programs

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.