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We review practical challenges in building and deploying ethical AI at the scale of contemporary industrial and societal uses. Apart from the purely technical concerns that are the usual focus of academic research, the operational…
This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital…
Case studies are typically used to teach 'ethics', but in quantitative courses it can seem distracting, for both instructor and learner, to introduce a case analysis. Moreover, case analyses are typically focused on issues relating to…
We show how to assess a language model's knowledge of basic concepts of morality. We introduce the ETHICS dataset, a new benchmark that spans concepts in justice, well-being, duties, virtues, and commonsense morality. Models predict…
In this paper, we situate the educational movement of "Ethics in Mathematics," as outlined by the Cambridge University Ethics in Mathematics Project, in the wider area of mathematics ethics education. By focusing on the core message coming…
Moral responsibility is a major concern in autonomous systems, with applications ranging from self-driving cars to kidney exchanges. Although there have been recent attempts to formalise responsibility and blame, among similar notions, the…
In recent years, the availability of massive data sets and improved computing power have driven the advent of cutting-edge machine learning algorithms. However, this trend has triggered growing concerns associated with its ethical issues.…
Case studies are typically used to teach 'ethics', but when the content of a course is focused on formulae and proofs, a case analysis and the knowledge, skills, and abilities they require can be distracting. Moreover, case analyses are…
How has recent AI Ethics literature addressed topics such as fairness and justice in the context of continued social and structural power asymmetries? We trace both the historical roots and current landmark work that have been shaping the…
Why are we good? Why are we bad? Questions regarding the evolution of morality have spurred an astoundingly large interdisciplinary literature. Some significant subset of this body of work addresses questions regarding our moral psychology:…
Numerous AI ethics checklists and frameworks have been proposed focusing on different dimensions of ethical AI such as fairness, explainability, and safety. Yet, no such work has been done on developing transparent AI systems for real-world…
This paper presents a newly-developed robotics programming course and reports the initial results of software engineering education in robotics context. Robotics programming, as a multidisciplinary course, puts equal emphasis on software…
Ethics as embodied by technology practitioners resists simple definition, particularly as it relates to the interplay of identity, organizational, and professional complexity. In this paper we use the linguistic notion of languaging as an…
In recent years, the idea of formalising and modelling fairness for algorithmic decision making (ADM) has advanced to a point of sophisticated specialisation. However, the relations between technical (formalised) and ethical discourse on…
Artificial intelligence (AI) is becoming increasingly widespread in system development endeavors. As AI systems affect various stakeholders due to their unique nature, the growing influence of these systems calls for ethical considerations.…
When large language models make ethical judgments, do their internal representations distinguish between normative frameworks, or collapse ethics into a single acceptability dimension? We probe hidden representations across five ethical…
One part of complying with norms, rules, and preferences is incorporating constraints (such as knowledge of ethics) into one's goal formulation and planning processing. We explore in a simple domain how the encoding of knowledge in…
Fair machine learning research has been primarily concerned with classification tasks that result in discrimination. However, as machine learning algorithms are applied in new contexts the harms and injustices that result are qualitatively…
In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. Across academia, industry, and government bodies, a variety of endeavours are…
With the increase in adoption of machine learning tools by organizations risks of unfairness abound, especially when human decision processes in outcomes of socio-economic importance such as hiring, housing, lending, and admissions are…