Algorithmic Accountability

by | Mar 27, 2018 | Blog | 0 comments

Google Photos tags two human beings as gorillas. How did that happen? It happened because that was the data that we fed to the algorithm. In the data scientists’ world of 0s and 1s, we are continuously separating the “good” from “bad”. How can we judge where to draw that line of separation? Google Photos is not a common example. In our day to day lives we experience this through credit risk profiling. As we rely more and more on algorithms to tell us whom we are engaging with, what we should invest in etc., data scientists should feel more accountable for how they are “training” the algorithms. It is more than just math