Non-Asimov Explanations Regulating AI through Transparency
Chris Reed, Keri Grieman, Joseph Early

TL;DR
This paper argues that AI explanations should move beyond traditional narrative stories inspired by Asimov, advocating for diverse narratives that align with legal and regulatory concepts like fairness and reasonableness.
Contribution
It introduces a new perspective on AI explanations, emphasizing the need for diverse narrative forms that serve legal and regulatory understanding, challenging the Asimov-inspired storytelling approach.
Findings
Current AI explanations rely on narrative logic similar to Asimov's stories.
Law and regulation require different narrative types for concepts like fairness.
A dual approach is needed: technologists craft stories, law accepts varied narratives.
Abstract
An important part of law and regulation is demanding explanations for actual and potential failures. We ask questions like: What happened (or might happen) to cause this failure? And why did (or might) it happen? These are disguised normative questions - they really ask what ought to have happened, and how the humans involved ought to have behaved. To answer the normative questions, law and regulation seeks a narrative explanation, a story. At present, we seek these kinds of narrative explanation from AI technology, because as humans we seek to understand technology's working through constructing a story to explain it. Our cultural history makes this inevitable - authors like Asimov, writing narratives about future AI technologies like intelligent robots, have told us that they act in ways explainable by the narrative logic which we use to explain human actions and so they can also be…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Ethics and Social Impacts of AI · Law in Society and Culture
