Artificial intelligence has a plethora of practical benefits. One of the main ones is how beneficial it can be to healthcare. Historically, healthcare disparities have been a huge issue. Such disparities range from unequal access to quality treatment and the plight of Black women in healthcare to not having enough representation in clinical trials.
Forbes published an article this week touching on how artificial intelligence can be used and what needs to be done so it's used effectively for healthcare.
"The fundamental truth is that data must be both large in scale and diverse in representation to train truly equitable and effective algorithms across different populations. This perspective reminds us that any building is only as strong as its foundation; and to create a meaningful, lasting impact on health equity, we must ensure that our tools are built with the right data." - Mainul Mondal
This is an important aspect as we go down the rabbit hole of artificial intelligence in healthcare. Building these large-scale systems doesn't matter if the data being used to build them isn't from a diverse data point set. If we take a step back, the data point set should at least represent populations that are relative to the ones that are affected by whatever problem the systems are trying to solve.
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