Work

The Missing Link: Allocation Performance in Causal Machine Learning

Year: 2024

Type: preprint

Abstract: Automated decision-making (ADM) systems are being deployed across a diverse range of critical problem areas such as social welfare and healthcare. Recent work highlights the importance of causal ML models in ADM systems, but implementing them in complex social environments poses significant challenges. Research on how these challenges impact the performance in specific downstream decision-making tasks is limited. Addressing this gap, we make use of a comprehensive real-world dataset of jobseekers to illustrate how the performance of a single CATE model can vary significantly across different decision-making scenarios and highlight the differential influence of challenges such as distribution shifts on predictions and allocations.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2407.10779

Authors: Fischer-Abaigar, Unai, Kern, Christoph, Kreuter, Frauke

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Reduced inequalities

Open Access status: green

Funders: Deutscher Akademischer Austauschdienst, Bundesministerium für Bildung und Forschung

OpenAlex ID: W4400717825

Cites:

Cited by:

Related to: 10