Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.
Journal:
Journal of diabetes science and technology
Published Date:
Jan 1, 2019
Abstract
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on personal phenotypic and genotypic information will lead to selections of tailored, effective therapies that will transform health care. However, decision-making processes based exclusively on quantitative metrics that ignore qualitative factors could create a quantitative fallacy. Difficult to quantify inputs into AI-based therapeutic decision-making processes include empathy, compassion, experience, and unconscious bias. Failure to consider these "softer" variables could lead to important errors. In other words, that which is not quantified about human health and behavior is still part of the calculus for determining therapeutic interventions.
Authors
Keywords
Access to Information
Artificial Intelligence
Big Data
Computational Biology
Data Collection
Decision Making
Decision Support Systems, Clinical
Diabetes Mellitus, Type 1
Diabetes Mellitus, Type 2
Ethnicity
Genotype
Healthcare Disparities
Humans
Language
Phenotype
Precision Medicine
Public Health
Racial Groups
Reproducibility of Results