Bynum, Lucius E.J., Loftus, Joshua R. 
ORCID: 0000-0002-2905-1632 and Stoyanovich, Julia
(2024)
A new paradigm for counterfactual reasoning in fairness and recourse.
In: Larson, Kate, (ed.)
Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024.
IJCAI International Joint Conference on Artificial Intelligence.
International Joint Conferences on Artificial Intelligence, pp. 7092-7100.
ISBN 9781956792041
Abstract
Counterfactuals underpin numerous techniques for auditing and understanding artificial intelligence (AI) systems. The traditional paradigm for counterfactual reasoning in this literature is the interventional counterfactual, where hypothetical interventions are imagined and simulated. For this reason, the starting point for causal reasoning about legal protections and demographic data in AI is an imagined intervention on a legally-protected characteristic, such as ethnicity, race, gender, disability, age, etc. We ask, for example, what would have happened had your race been different? An inherent limitation of this paradigm is that some demographic interventions - like interventions on race - may not be well-defined or translate into the formalisms of interventional counterfactuals. In this work, we explore a new paradigm based instead on the backtracking counterfactual, where rather than imagine hypothetical interventions on legally-protected characteristics, we imagine alternate initial conditions while holding these characteristics fixed. We ask instead, what would explain a counterfactual outcome for you as you actually are or could be? This alternate framework allows us to address many of the same social concerns, but to do so while asking fundamentally different questions that do not rely on demographic interventions.
| Item Type: | Book Section |
|---|---|
| Additional Information: | © 2024 International Joint Conferences on Artificial Intelligence. |
| Divisions: | Statistics LSE |
| Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Date Deposited: | 02 Oct 2024 09:12 |
| Last Modified: | 20 Dec 2024 00:20 |
| URI: | http://eprints.lse.ac.uk/id/eprint/125591 |
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