My daily experience with recommendation systems are seamless. They recommend what to read on Apple News, listen on Spotify, eat on Uber Eats, purchase on Amazon, watch on Netflix. These software programs take millions of data points, clean and segment the data, weigh different variables, and output recommendations that ensure we stay engaged with the platform for the next selection. As much as we want to believe that machines make all these decisions, data scientists are the ones that are deciding the inputs for these models. Ultimately, these choices introduce bias.
What if I'm missing out on an incredible book or song because the inputs don't capture interests of mine that I didn't even know existed?