This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

The aim of this paper is to show that the nascent field of ethics of collegiality may considerably benefit from a symbiosis with virtue and vice epistemology. We start by bringing the epistemic virtue and vice perspective to the table by showing that competence, deemed as an essential characteristic of a good colleague (Betzler & Löschke 2021), should be construed broadly to encompass epistemic competence. By endorsing the anti-individualistic stance in epistemology as well as context-specificity of epistemic traits, we show (...) how the individual vice of a colleague can have a positive epistemic outcome for the team while individual virtue can be damaging if all team members share it, thereby contributing to the negative epistemic outcome. We argue that the evaluation and analysis of collegial relationships should be done through one’s contribution to the team dynamics: without this collectivist perspective, the ethics of collegiality cannot aspire to become encompassing normative theory. (shrink)

In this chapter, I introduce three different types of AI-based moral enhancement proposals discussed in the literature – substitutive enhancement, value-driven enhancement, and value-open moral enhancement. I analyse them based on the following criteria: effectiveness, examining whether they bring about tangible moral changes; autonomy, assessing whether they infringe on human autonomy and agency; and developmental impact, considering whether they hinder the development of natural moral skills. This analysis demonstrates that no single approach to AI enhancement can satisfy all proposed criteria, (...) suggesting a need for pluralism in devising AI-based enhancement tools. The most advisable approach to AI-based enhancement is to explore and develop a variety of tools that cater to the diverse needs of users and address different weaknesses in moral decision-making. (shrink)