Author: Saurabh Mishra
Publisher: Medium
Publication Year: 2020
Summary: The following article discusses how data is very important when it comes to artificial intelligence (AI) and machine learning as it acts as the fuel source for these methods. One of the few unethical examples that the article made reference to was an unethical use of facial recognition where the U.S.’s Immigration and Customs Enforcement (ICE) used facial recognition to analyze the activities of immigrant communities. If you were to ask me, this is considered stalking and abusing the privacy of others. There has been no consent of immigrants to allow ICE to analyze their daily activities so thus their actions and use of data are unethical. There are many consequences to using data unethically, so as data scientists it is important to notice when a model or algorithm is being used for bad. It is important to ask ourselves questions about the purpose of the project we are working on. We should also ask ourselves if individuals will be harmed by the product we are creating. Not only should we question the work, but we need to make sure that the group of data scientists we are working with is a diverse group of people. Sometimes if there is no diversity and there is always consesus in the work we are doing, we may create a biased model even when we did not intend for it to happend.