Understanding responsibility in Responsible AI. Dianoetic virtues and the hard problem of context

Abstract

During the last decade there has been burgeoning research concerning the ways in which we should think of and apply the concept of responsibility for Artificial Intelligence. Despite this conceptual richness, there is still a lack of consensus regarding what Responsible AI entails on both conceptual and practical levels. The aim of this paper is to connect the ethical dimension of responsibility in Responsible AI with Aristotelian virtue ethics, where notions of context and dianoetic virtues play a grounding role for the concept of moral responsibility. The paper starts by highlighting the important difficulties in assigning responsibility to either technologies themselves or to their developers. Top-down and bottom-up approaches to moral responsibility are then contrasted, as we explore how they could inform debates about Responsible AI. We highlight the limits of the former ethical approaches and build the case for classical Aristotelian virtue ethics. We show that two building blocks of Aristotle’s ethics, dianoetic virtues and the context of actions, although largely ignored in the literature, can shed light on how we could think of moral responsibility for both AI and humans. We end by exploring the practical implications of this particular understanding of moral responsibility along the triadic dimensions of ethics by design, ethics in design and ethics for designers.

Drivers behind the public perception of artificial intelligence: insights from major Australian cities

“…Several studies have already reported the privacy issue as one of the main hurdles in technology adoption, including AI (Mazurek and Małagocka 2019 ; Radhakrishnan and Chattopadhyay 2020 ). While these concerns are valid, particularly when AI practices in some authoritarian regimes are concerned (Stark 2021 ), they also provide an opportunity to place pressure on public authorities and private sector for the development of more ethical and responsible AI frameworks and applications (Constantinescu et al 2021 ; Yigitcanlar et al 2021a ). This finding is in line with other studies that highlighted the public anxiety about AI (Vu & Lim 2021 ).…”

Leverage zones in Responsible AI: towards a systems thinking conceptualization

“…Advances in digital technology, along with debates about biased algorithms and ethical and regulatory challenges of autonomous systems (Baker & Hawn, 2022 ; Coeckelbergh, 2019 ) underscore the fact that management of AI is as much a social and political issue rather than exclusively an engineering challenge (Coeckelbergh, 2022 ; Nabavi, 2019 ). This realization has caused policy, research, and industry actors to take non-technical aspects of AI into account, which can be seen in the increased awareness of ‘responsibility’ in AI systems (Constantinescu et al, 2021 ), defined broadly as including principles such as transparency, fairness, and accountability in creating AI technologies that meet legal requirements and societal expectation, norms and values. Common concerns in this area include privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values (Fjeld et al, 2020 ).…”

A Virtue-Based Framework to Support Putting AI Ethics into Practice

“…In the more specific context of AI applications, however, one has to sort out those virtues that are particularly important in the field of AI ethics. Here, existing literature and preliminary works are spare (Constantinescu et al, 2021;Neubert & Montañez, 2020).…”