The responsibility gap: Ascribing responsibility for the actions of learning automata

By A. Matthias. Ethics and Information Technology, 2004

895 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/05c08de1bf91cd52ea1d22e7238e33958b574a23

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Citations in the corpus

Artificial Intelligence and the Public Sector—Applications and Challenges (2018, background): “Thus, AI systems may defy direct human control, which leads to the so-called responsibility gap, according to which humans cannot be held accountable for the behavior of AI systems due to their lack of control and influence (Matthias, 2004).”
Reframing AI Discourse (2017, background): “The responsibility gap is a concept introduced by Matthias to describe a situation in which no person can be held responsible for the consequences of the behaviour of an artefact (Matthias 2004).”
Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI (2021, background): “49 This claim is contestable, not only because physicians typically operate other technologies and machinery which they do not fully understand or cannot fully explain the inner working of (think of MRI scans, eg), yet they are sufficiently in control and understand enough of the workings to be…”
Towards Transparency by Design for Artificial Intelligence (2020, background): “Automated decision making-systems can have impacts on individuals and society at large, creating novel ethical challenges that open up fundamental questions regarding responsibility, human dignity, and the relation between humans and machines (Coeckelbergh 2020; Matthias 2004; Laton-ero 2018).”
The Philosophical Case for Robot Friendship (2019, background): “People are concerned about ‘responsibility gaps’ that will open up as robotic weapons systems and self-driving cars become widespread in society (Sparrow 2007; Matthias 2004; Bhuta et al 2016).”
Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery (2019, background): “ForMatthias(2004), 42 the traditional rules of liability law would then be unsuitable for unpredictable machines because the human would no longer really have control of the actions of the robot.”
The Ethical Implications of Using Artificial Intelligence in Auditing (2020, background): “Matthias (2004) observes that traditionally, the user of a machine is liable for the resultant consequences of the machine operation.”
Your evidence? Machine learning algorithms for medical diagnosis and prediction (2019, background): “Notably, Matthias (Matthias, 2004) has identified a “ responsibility gap ” that, according to him, cannot be bridged by the received concepts of responsibility.”
Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2023, background): “This pertains to developing “ responsible and ethical AI ” before it is too late [297,301,302].”
The Strategic Robot Problem: Lethal Autonomous Weapons in War (2014, background): “In particular, the complexity required in creating autonomous machines strains the causal chain of responsibility (see Matthias 2004).”
What Do We Want From Explainable Artificial Intelligence (XAI)? - A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research (2021, background): “With increasing use of artificial systems, accountability gaps might emerge [134, 135].”