Chapter IV
Visioning a Technoscientific-Advanced, Data-Rich Ecosystem
A purposeful embrace of the technosciences is the order of the day. For the physician, they must transition from being eclectic add-ons to core competencies.
Recommendation
Recommendation. Convert the technosciences from eclectic add-ons to core competencies embedded in the base training of every specialty, so that data-aware medicine, complexity literacy, and the supervision of physical AI become baseline clinical skills. Educate trainees in complex, dynamic systems thinking. Ask data-aware medicine to address three questions of any system: where its data came from and whom they represent; the objective for which the database was aggregated and optimized; and where its failure envelope lies. Establish an FDA-like certifying function for health data and analytics, certifying provenance and maintenance rather than accuracy per se, built as a federation of societies, academic systems, and boards, with regulators present rather than in charge. Define with specificity the expectations for the human factor as physical AI deploys across an ascending gradient of robotic autonomy. Establish a standing, horizon-scanning function across specialty societies that serves as a coordinating resource to inform and guide strategies and policies related to technology adoption and use-case optimization, and in parallel, require that the number of comparisons behind an opinion travels with the result.
Sections
- 01Technoscientific Disruption: Multilevel, MultimodalTwo distinct waves of technoscience are reshaping medicine, and conflating them obscures both.
- 02Complexity Science Comes to the ForeComplexity science is the study of systems whose collective behavior emerges from the interactions of their parts and cannot be predicted from those parts in isolation.
- 03AI Intelligence Ecosystem: From Data Procurement to Data CurationThe most consequential misconception about AI in medicine is that there is a single thing called AI. By 2050 the physician's competence will rest on understanding that there is not, and on knowing where each kind of intelligence ends.Exhibit 4.11 definition
- 04Physical AI: A Gradient of AutonomyRobotics follows the same logic of bounded competence that governs AI, and a gradient locates the physician within it.Exhibit 4.2
- 05Statistics, Mathematics and Physics Transform BiomedicineBig data in biomedicine is driving a return of mathematics to the center of medicine, and with it the emergence of computational medicine as a discipline in its own right.Moonshots