Responsibility of AI Systems

Mehdi M. Dastani · Vahid Yazdanpanah

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Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI)Safety Systems Engineering in Autonomy

Abstract

Abstract To support the trustworthiness of AI systems, it is essential to have precise methods to determine what or who is to account for the behaviour, or the outcome, of AI systems. The assignment of responsibility to an AI system is closely related to the identification of individuals or elements that have caused the outcome of the AI system. In this work, we present an overview of approaches that aim at modelling responsibility of AI systems, discuss their advantages and shortcomings to deal with various aspects of the notion of responsibility, and present research gaps and ways forward.

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2017Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy 2019Responsible Artificial Intelligence 1980Moral Responsibility of Public Officials: The Problem of Many Hands 2017Machine learning, social learning and the governance of self-driving cars 2014Shared Agency: A Planning Theory of Acting Together 2019Geographies of Algorithmic Violence: Redlining the Smart City 2011The Relation Between Forward-Looking and Backward-Looking Responsibility 2015Moral Responsibility and the Problem of Many Hands

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