Of research and robots: making sense of chance findings
BMJ 2021; 375 doi: https://doi.org/10.1136/bmj.n2915 (Published 16 December 2021) Cite this as: BMJ 2021;375:n2915
- Juan Víctor Ariel Franco, editor in chief, BMJ Evidence-Based Medicine1 2,
- Santiago Esteban, chair, Information Management and Health Statistics Office2 3
- 1Research Department, Instituto Universitario Hospital Italiano de Buenos Aires, Argentina
- 2Family and Community Medicine Division, Hospital Italiano de Buenos Aires, Argentina
- 3Information Management and Health Statistics Office, Health Ministry of the City of Buenos Aires, Argentina
- Correspondence to: J Franco juanfranco{at}bmj.com
“I, a reasoning being, am capable of deducing truth from a priori causes. You, being intelligent but unreasoning, need an explanation of existence supplied to you,” says the robot QT-1 (Cutie) to his perplexed human masters, Donovan and Powell, in Isaac Asimov’s classic book I, Robot.1 Powered by artificial intelligence (AI), the rebellious robot takes control of a space station, believing that humans are too weak to have created such a superior creature.
Users of medical research might feel as perplexed as Donovan and Powell when faced with new and sophisticated analytical methods, especially those related to AI. So, what do we currently understand about AI’s role in clinical research—and how can we make it work better for everyone?
AI can be used in descriptive, diagnostic, and predictive research, in knowledge discovery, and in investigating causal inference.1 It can also provide sophisticated tools to automate tasks usually done by …
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