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The Ethics of Emotion in Artificial Intelligence Systems

141 Citations2021
Luke Stark, Jesse Hoey
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A taxonomy of conceptual models and proxy data used for digital analysis of human emotional expression is developed and how the combinations and permutations of these models and data impact their incorporation into artificial intelligence (AI) systems are outlined.

Abstract

In this paper, we develop a taxonomy of conceptual models and proxy data used for digital analysis of human emotional expression and outline how the combinations and permutations of these models and data impact their incorporation into artificial intelligence (AI) systems. We argue we should not take computer scientists at their word that the paradigms for human emotions they have developed internally and adapted from other disciplines can produce ground truth about human emotions; instead, we ask how different conceptualizations of what emotions are, and how they can be sensed, measured and transformed into data, shape the ethical and social implications of these AI systems.