Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

by   Edward A. Small, et al.

Counterfactuals operationalised through algorithmic recourse have become a powerful tool to make artificial intelligence systems explainable. Conceptually, given an individual classified as y – the factual – we seek actions such that their prediction becomes the desired class y' – the counterfactual. This process offers algorithmic recourse that is (1) easy to customise and interpret, and (2) directly aligned with the goals of each individual. However, the properties of a "good" counterfactual are still largely debated; it remains an open challenge to effectively locate a counterfactual along with its corresponding recourse. Some strategies use gradient-driven methods, but these offer no guarantees on the feasibility of the recourse and are open to adversarial attacks on carefully created manifolds. This can lead to unfairness and lack of robustness. Other methods are data-driven, which mostly addresses the feasibility problem at the expense of privacy, security and secrecy as they require access to the entire training data set. Here, we introduce LocalFACE, a model-agnostic technique that composes feasible and actionable counterfactual explanations using locally-acquired information at each step of the algorithmic recourse. Our explainer preserves the privacy of users by only leveraging data that it specifically requires to construct actionable algorithmic recourse, and protects the model by offering transparency solely in the regions deemed necessary for the intervention.


page 2

page 3

page 5


Disagreement amongst counterfactual explanations: How transparency can be deceptive

Counterfactual explanations are increasingly used as an Explainable Arti...

Simple Steps to Success: Axiomatics of Distance-Based Algorithmic Recourse

We propose a novel data-driven framework for algorithmic recourse that o...

Counterfactual Analysis by Algorithmic Complexity: A metric between possible worlds

Counterfactuals have become an important area of interdisciplinary inter...

Counterfactual Explanations as Interventions in Latent Space

Explainable Artificial Intelligence (XAI) is a set of techniques that al...

Endogenous Macrodynamics in Algorithmic Recourse

Existing work on Counterfactual Explanations (CE) and Algorithmic Recour...

Please sign up or login with your details

Forgot password? Click here to reset