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Expert recommendations for avoiding bias in AI
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The issue of bias in algorithms receives considerable attention in the United States as their datasets often reflect biases against racial groups that are underrepresented.
Promote health and health care equity during all phases of the health care algorithm life cycle
Ensure that health care algorithms and their use are transparent and explainable
Authentically engage patients and communities during all phases of the health care algorithm life cycle and earn trust
Explicitly identify health care algorithmic fairness issues and tradeoffs
Ensure accountability for equity and fairness in outcomes from health care algorithms
Read the following online article on “Eliminating Racial Bias in Health Care AI: Expert Panel Offers Guidelines” to learn about the recommendations of a committee of experts on reducing the bias in these algorithms:
The panel offered five guiding principles:
Questions:
- Which of these five principles do you think is most important for you and why?
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