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.@en

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.@en