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  1. The teaching of computer ethics on computer science and related degree programmes. a European survey.Ioannis Stavrakakis, Damian Gordon, Brendan Tierney, Anna Becevel, Emma Murphy, Gordana Dodig-Crnkovic, Radu Dobrin, Viola Schiaffonati, Cristina Pereira, Svetlana Tikhonenko, J. Paul Gibson, Stephane Maag, Francesco Agresta, Andrea Curley, Michael Collins & Dympna O’Sullivan - 2021 - International Journal of Ethics Education 7 (1):101-129.
    Within the Computer Science community, many ethical issues have emerged as significant and critical concerns. Computer ethics is an academic field in its own right and there are unique ethical issues associated with information technology. It encompasses a range of issues and concerns including privacy and agency around personal information, Artificial Intelligence and pervasive technology, the Internet of Things and surveillance applications. As computing technology impacts society at an ever growing pace, there are growing calls for more computer ethics content (...)
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  • Role-Playing Computer Ethics: Designing and Evaluating the Privacy by Design (PbD) Simulation.Katie Shilton, Donal Heidenblad, Adam Porter, Susan Winter & Mary Kendig - 2020 - Science and Engineering Ethics 26 (6):2911-2926.
    There is growing consensus that teaching computer ethics is important, but there is little consensus on how to do so. One unmet challenge is increasing the capacity of computing students to make decisions about the ethical challenges embedded in their technical work. This paper reports on the design, testing, and evaluation of an educational simulation to meet this challenge. The privacy by design simulation enables more relevant and effective computer ethics education by letting students experience and make decisions about common (...)
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  • Non-empirical problems in fair machine learning.Teresa Scantamburlo - 2021 - Ethics and Information Technology 23 (4):703-712.
    The problem of fair machine learning has drawn much attention over the last few years and the bulk of offered solutions are, in principle, empirical. However, algorithmic fairness also raises important conceptual issues that would fail to be addressed if one relies entirely on empirical considerations. Herein, I will argue that the current debate has developed an empirical framework that has brought important contributions to the development of algorithmic decision-making, such as new techniques to discover and prevent discrimination, additional assessment (...)
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  • What Do We Teach to Engineering Students: Embedded Ethics, Morality, and Politics.Avigail Ferdman & Emanuele Ratti - 2024 - Science and Engineering Ethics 30 (1):1-26.
    In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towards addressing ethics at the societal level. In this article, we propose a tripartite framework to overcome these (...)
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