This study examines leadership challenges and ethical responsibilities surrounding the dual use of artificial intelligence in healthcare and biotechnology. Conducted in the United States in 2024, the research used a qualitative focus-group design with twenty participants representing healthcare professionals, developers, and ethicists. Guided discussions addressed responsible innovation, risk management, and social impact. Transcripts were coded and analyzed thematically to identify convergent leadership practices and persistent gaps. Findings show that leaders prioritize transparency, inclusive decision-making, and continuous ethical review to balance innovation with safety. Participants described safeguards – such as multidisciplinary ethics boards, stakeholder-informed development processes, and algorithmic audits – as crucial for accountability and trust. The analysis indicates that leadership models centered on ethical foresight and equity are necessary to mitigate risks including bias, data misuse, and unequal access to care. The paper provides evidence-based guidance on governance mechanisms that can be embedded across the innovation lifecycle, from problem framing and data stewardship to deployment monitoring and rollback criteria.
Delores Springs (2025) studied this question.