It's Time To Recognize That Machines Are Learning All The Wrong Things

Data-driven algorithms govern many aspects of life: university admissions, resume screening, and a person's ability to get a car or home loan. Often, using data leads to more efficient allocation of resources and better outcomes for everyone. But algorithms can come with unintended consequences--and without care, their application can result in a society we don't want. Typically, we think of algorithms as being neutral and objective, but when software is written and trained by humans, it often encodes the biases and prejudices of the people that make and shape it. Ultimately, the biases built into algorithms can be racist and marginalize low-ranking socioeconomic groups.