Minding the Moral Gap in Human-Machine Interaction

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Join the Centre for Advancing Responsible and Ethical Artificial Intelligence for a virtual conversation with Dr. Shannon Vallor on Minding the Moral Gap in Human-Machine Interaction.

Abstract: Given the enduring challenges of interpretability, explainability, fairness, safety, and reliability of machine learning systems, as well as expanding legal and ethical constraints imposed on such systems by regulators and standards bodies, it will be the case for the foreseeable future that AI/ML systems deployed in many high-stakes decision contexts will be required to operate under human oversight, what is often called ‘meaningful human control.’

Oversight is increasingly demanded in a broad range of application areas, from medicine and banking to military uses. However, this reassuring phrase conceals grave difficulties. How can humans control or provide effective oversight for ML system operations or machine outputs for which human supervisors lack deep understanding—an understanding often precluded by the very same causes (speed, complexity, opacity and non-verifiability of machine reasoning) that necessitate human supervision in the first place?

This quandary exposes a gap in AI safety and ethics governance mechanisms that existing methods are unlikely to close. In this talk I explore two dimensions of this gap which are frequently underappreciated in research on AI safety, explainable AI, or ‘human-friendly AI’: the absence of a capacity for ‘moral dialectic’ between human and machine experts, and the absence of an affective dimension to machine reasoning.

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