Setting the Right Expectations: Algorithmic Recourse Over Time

Author:

Fonseca João1ORCID,Bell Andrew2ORCID,Abrate Carlo3ORCID,Bonchi Francesco3ORCID,Stoyanovich Julia4ORCID

Affiliation:

1. NOVA Information Management School, Portugal

2. New York University, USA

3. CENTAI, Italy

4. New York University, United States

Funder

Portuguese Foundation for Science and Technology

National Science Foundation

Publisher

ACM

Reference36 articles.

1. Patrick Altmeyer , Giovan Angela , Aleksander Buszydlik , Karol Dobiczek , Arie van Deursen , and Cynthia Liem . 2023 . Endogenous Macrodynamics in Algorithmic Recourse. In First IEEE Conference on Secure and Trustworthy Machine Learning. Patrick Altmeyer, Giovan Angela, Aleksander Buszydlik, Karol Dobiczek, Arie van Deursen, and Cynthia Liem. 2023. Endogenous Macrodynamics in Algorithmic Recourse. In First IEEE Conference on Secure and Trustworthy Machine Learning.

2. The hidden assumptions behind counterfactual explanations and principal reasons

3. The need for uncertainty quantification in machine-assisted medical decision making

4. Think about the stakeholders first! Toward an algorithmic transparency playbook for regulatory compliance

5. Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising.;Bottou Léon;Journal of Machine Learning Research,2013

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1. The Game Of Recourse: Simulating Algorithmic Recourse over Time to Improve Its Reliability and Fairness;Companion of the 2024 International Conference on Management of Data;2024-06-09

2. CARMA: A practical framework to generate recommendations for causal algorithmic recourse at scale;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

3. Better Luck Next Time: About Robust Recourse in Binary Allocation Problems;Communications in Computer and Information Science;2024

4. Human-in-the-Loop Personalized Counterfactual Recourse;Communications in Computer and Information Science;2024

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