When data scientists talk about bias, we talk about quantifiable bias that is a result of let’s say incomplete or incorrect data. And data scientists love living in that world—it’s very comfortable. Why? Because once it’s quantified if you can point out the error you just fix the error. What this does not ask is should you have built the facial recognition technology in the first place?
Exploring (Semantic) Space With (Literal) Robots
presented by Allison Parrish
I’ve made it my goal as a computer poet not to imitate existing poetry but to find new ways for poetry to exist. So what I’m going to do in this talk is take this metaphor of exploring literature to its logical conclusion. Read more →