The Ethics of Emotion in AI Systems
Luke Stark, Jesse Hoey · 2020
In this paper, we develop a taxonomy of relevant models and proxy data for emotional expression and outline how the combinations and permutations of these models and data impact artificial intelligence (AI) systems deploying them. We should not take computer scientists at their word that the paradigms for human emotions they have developed internally and adapted from other fields are ground truth; instead, we ask how different conceptualizations of what emotions are, and how they can be sensed, measured and transformed into data, shape the way humans interact with and respond to these AI systems.