Abstract
The recommendations list that appears after watching a show on Netflix, the ads that come up on Instagram similar to other liked posts, these phenomenons are due to algorithmic decision making. Algorithms are able to help people do simple pattern-based tasks in day-to-day life but they also have implications on our society. Algorithms often make mistakes due to the human error in data they analyze. There are many different sources of algorithmic error in decision making, but the most significant cause by far is error in the data which algorithms are trained from. These errors affect advertisements, jobs, and also technological products. It is hard to get rid of these biases as many times it leads to underrepresentation, another cause of algorithmic error. The way an algorithm is trained has a large impact on the future decisions it makes.
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