This paper proposes and reflects on a teaching methodology for introducing relational ethics in the engineering curriculum based on a pilot at TU Delft in the Netherlands in a course for robotics engineers. Differently from prevalent models of ethics courses, we shifted from having students apply ethical theories to technologies to having them reflect on different aspects of human-robot relations from a more-than-human perspective. This redesign was prompted by conceptual and practical motivations related to (1) a lack of methodological examples of relational ethics in engineering ethics education, (2) a call for more experiential education, and (3) a push to re-evaluate course assessment due to Generative AI. Aside from the lecture content, students explored various dimensions of relational ethics in a thinking-through-doing manner by crafting a companion robot in the tutorials. This culminated in an individual essay in which students reflected on the question ‘How to live well with robots?,’ reflecting on their developing relations with their robotic companion and supported by visual evidence of their human-robot interactions throughout the course. Finally, we provide reflections on this experimental course redesign, outlining several considerations for those intending to integrate relational ethics into their curricula and suggesting avenues for further work.

The following paper offers a political and philosophical reading of ethically informed technological design practices to critically tackle the implicit regulative ideal in the design of social media as a means to digitally represent the liberal public sphere. The paper proposes that, when it comes to the case of social media platforms, understood along with the machine learning algorithms embedded in them as algorithmic technologies, ethically informed design has an implicit conception of democracy that parallels that of Jürgen Habermas’ procedural democracy (Habermas, J. (1994). THREE NORMATIVE MODELS OF DEMOCRACY. Jurgen Habermas, 1(1).). That is, that democratic practices are encodable as procedures that produce valid discussion forums. Opposed to this, this paper suggests a turn to philosopher Jacques Rancière’s conception of politics as a guiding attitude towards technological design. This is done by, on the one side, using Rancière’s notions of “disagreement” and “distribution of the sensible” as the political starting point for the practice of design of algorithmic technologies. And, on the other, inspired by Karen Barad’s theories on agential realism (Barad, K. (2003). Posthumanist Performativity: Toward an Understanding of How Matter Comes to Matter. Signs: Journal of Women in Culture and Society, 28(3), 801–831. https://doi.org/10.1086/345321), by putting forward a political ontology of algorithmic technologies that reconceptualizes them in terms of how they assemble open-ended practices between human bodies and technological devices.

Recommender systems are among the most widely used applications of artificial intelligence. Since they are so widely used, it is important that we, as practitioners and researchers, think about the impact these systems may have on users, society, and other stakeholders. To that effect, the NORMalize workshop seeks to introduce normative thinking, to consider the norms and values that underpin recommender systems in the recommender systems community. The objective of NORMalize is to bring together a growing community of researchers and practitioners across disciplines who want to think about the norms and values that should be considered in the design and evaluation of recommender systems; and further educate them on how to reflect on, prioritise, and operationalise such norms and values. NORMalize offers a comprehensive program designed to cater to both the norm-curious and the norm-active. The morning session is on-site and features a lecture on normative thinking and an interactive workshop. The afternoon is a hybrid program focused on the dissemination of results. NORMalize publishes proceedings, as well as a technical report that summarises the outcomes of the interactive morning session.