35 citations · 52 across the 5 of their papers we have counts for
5 papers
Aligning Trustworthy AI with Democracy: A Dual Taxonomy of Opportunities and Risks
Oier Mentxaka, Natalia Díaz-Rodríguez, Mark Coeckelbergh +5
Artificial Intelligence (AI) poses both significant risks and valuable opportunities for democratic governance. This paper introduces a dual taxonomy to evaluate AI's complex relat…
Relational Norms for Human-AI Cooperation
Brian D. Earp, Sebastian Porsdam Mann, Mateo Aboy +59
How we should design and interact with social artificial intelligence depends on the socio-relational role the AI is meant to emulate or occupy. In human society, relationships suc…
Towards an Environmental Ethics of Artificial Intelligence
Nynke van Uffelen, Lode Lauwaert, Mark Coeckelbergh +1
In recent years, much research has been dedicated to uncovering the environmental impact of Artificial Intelligence (AI), showing that training and deploying AI systems require lar…
Challenging the Human-in-the-loop in Algorithmic Decision-making
Sebastian Tschiatschek, Eugenia Stamboliev, Timothée Schmude +2
We discuss the role of humans in algorithmic decision-making (ADM) for socially relevant problems from a technical and philosophical perspective. In particular, we illustrate tensi…
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation
Natalia Díaz-Rodríguez, Javier Del Ser, Mark Coeckelbergh +3
Trustworthy Artificial Intelligence (AI) is based on seven technical requirements sustained over three main pillars that should be met throughout the system's entire life cycle: it…