@inproceedings{8cab879954964c478f111419ab2e48be,
title = "The Game Of Recourse: Simulating Algorithmic Recourse over Time to Improve Its Reliability and Fairness",
abstract = "Algorithmic recourse, or providing recommendations to individuals who receive an unfavorable outcome from an algorithmic system on how they can take action and change that outcome, is an important tool for giving individuals agency against algorithmic decision systems. Unfortunately, research on algorithmic recourse faces a fundamental challenge: there are no publicly available datasets on algorithmic recourse. In this work, we begin to explore a solution to this challenge by creating an agent-based simulation called The Game of Recourse (an homage to Conway's Game of Life) to synthesize realistic algorithmic recourse data. We designed The Game of Recourse with a focus on reliability and fairness, two areas of critical importance in socio-technical systems. You can access the application at https://game-of-recourse.streamlit.app.",
keywords = "algorithmic recourse, data generation, fairness, ranking, reliability, simulation, temporal data",
author = "Andrew Bell and Joao Fonseca and Julia Stoyanovich",
note = "Publisher Copyright: {\textcopyright} 2024 Owner/Author.; 2024 International Conferaence on Management of Data, SIGMOD 2024 ; Conference date: 09-06-2024 Through 15-06-2024",
year = "2024",
month = jun,
day = "9",
doi = "10.1145/3626246.3654742",
language = "English (US)",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
publisher = "Association for Computing Machinery",
pages = "464--467",
booktitle = "SIGMOD-Companion 2024 - Companion of the 2024 International Conferaence on Management of Data",
}