Machine Learning & Medicine: The Pitfalls of AI in Healthcare
How algorithms introduce gender and racial bias.
Bias in Artificial Intelligence (AI) is the most dangerous factor in the development of AI algorithms. Yes, even more important than that ubiquitous fear immortalized in movies — that robots will kill us all.
Those most at risk for suffering at the hands of bias in AI algorithms are the most vulnerable members of our society. This is no different in healthcare.
According to a study published in the American Medical Association Journal of Ethics,
“In contrast to human bias, algorithmic bias occurs when an AI model, trained on a given dataset, produces results that may be completely unintended by the model creators.”
This differentiates bias in an AI algorithm from bias in a non-AI based algorithm. In a non-AI based algorithm, a software developer can determine the source of the resulting bias and change the formula to remove the bias.
In an AI algorithm, the software arrives at the clinical decision using a method hidden from the software developer. This phenomenon, called black-box learning, makes it more difficult to…
