Climbing the ladder: How agents reach counterfactual thinking

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We increasingly rely on automated decision-making systems to search for information and make everyday choices. While concerns regarding bias and fairness in machine learning algorithms have high resonance, less addressed is the equally important question of to what extent we are handing our own role of agents over to artificial information-retrieval systems. This paper aims at drawing attention to this issue by considering what agency in decision-making processes amounts to. The main argument that will be proposed is that a system needs to be capable of reasoning in counterfactual terms in order for it to be attributed agency. To reach this step, automated system necessarily need to develop a stable and modular model of their environment.
Original languageEnglish
Title of host publicationProceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022) - Volume 3
EditorsAna Paula Rocha, Luc Steels, Jaap van den Herik
PublisherSCITEPRESS
Pages555-560
Number of pages6
ISBN (Electronic)9789897585470
DOIs
Publication statusPublished - 3 Feb 2022

Publication series

NameProceedings of the International Conference on Agents and Artificial Intelligence
ISSN (Electronic)2184-433X

Keywords / Materials (for Non-textual outputs)

  • counterfactuality
  • agency
  • decision-making
  • causal reasoning
  • robustness

Fingerprint

Dive into the research topics of 'Climbing the ladder: How agents reach counterfactual thinking'. Together they form a unique fingerprint.

Cite this