Resources · Healthcare & Life Sciences
Trust in Clinical AI
The research behind the healthcare keynote. What is actually authorized, what the evidence does and does not show, and who is accountable when a model is wrong.
Updated September 2026
What is actually approved
US Food and Drug Administration · updated continuouslyAI-Enabled Medical Device List→medRxiv · 2026 · 1,430 devices analyzed; radiology accounts for 76.5%Three decades of FDA authorizations: persistent specialty concentration and the care-delivery gap, 1995–2025→Bipartisan Policy Center · 2025FDA oversight: understanding the regulation of health AI tools→
Where the evidence is thin
PMC · under 4% of authorized devices report the race or ethnicity of their validation cohortsMachine learning-enabled devices authorized in 2024: regulatory characteristics, predicate lineage, and transparency reporting→Obermeyer, Powers, Vogeli & Mullainathan · Science · 2019Dissecting racial bias in an algorithm used to manage the health of populations→Celi et al · PLOS Digital Health · 2022Sources of bias in artificial intelligence that perpetuate healthcare disparities: a global review→
Governance and accountability
World Health Organization · January 2024 · over 40 recommendationsEthics and governance of artificial intelligence for health: guidance on large multi-modal models→Meskó & Topol · npj Digital Medicine · 2023The imperative for regulatory oversight of large language models in healthcare→Zack et al · The Lancet Digital Health · 2024Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care→
Booking
Walk out ready.
Sam Rad is the speaker you book when you are facing change, and you want your people to walk out inspired to shape what comes next.
Book Sam →Managed by Brandy Gibson at Executive Speakers Bureau
CITE