Trust The AI? You Decide

Earlier this year, I wrote about fatal flaws in algorithms that were developed to mitigate the COVID-19 pandemic. Researchers found two general types of flaws. The first is that model makers used small data sets that didn't represent the universe of patients which the models were intended to represent leading to sample selection bias. The second is that modelers failed to disclose data sources, data-modeling techniques and the potential for bias in either the input data or the algorithms used to train their models leading to design related bias. As a result of these fatal flaws, such algorithms were inarguably less effective than their developers had promised.