Decision-Maker Alignment: Benchmark Datasets

Anik Sen; Rosina O Weber; Christopher B. Rauch; Mallika Mainali; J T Turner; John Meyer; Michael W. Floyd; Matthew Molineaux

doi:10.1109/CAI64502.2025.00212

Conference proceeding

Decision-Maker Alignment: Benchmark Datasets

Anik Sen, Rosina O Weber, Christopher B. Rauch, Mallika Mainali, J T Turner, John Meyer, Michael W. Floyd and Matthew Molineaux

2025 IEEE Conference on Artificial Intelligence (CAI), pp 1221-1229

05 May 2025

DOI: https://doi.org/10.1109/CAI64502.2025.00212

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Abstract

AI alignment

Benchmark testing

cognitive attributes

Decision making

decision-maker alignment

Insurance

ITM

Synthetic data

Uncertainty

Machine Learning

While alignment in artificial intelligence (AI) is broadly concerned with how AI systems align with human values, decision-maker alignment refers to how algorithms align with the values of individual decision makers. Consequently, the values targeted in decision-maker alignment are attributes that influence the decision-making process employed by humans. Example of a cognitive attribute is risk tolerance. The ideal environments for investigating decision-maker alignment are those in which the optimal decision may not be available, forcing humans to compromise and select a suboptimal decision. An optimal decision may not be available due to environment constraints such as limited resources, uncertainty, or some source of pressure. In contrast with supervised machine learning, decision-maker alignment can be investigated with labeled data in which decisions are made by different decision makers who are influenced by cognitive attributes. The problem is that datasets to study decision-maker alignment are difficult and expensive to create and they result in a small number of samples. For this reason, this paper proposes an approach to extend existing datasets for the purpose of studying decision-maker alignment. We exemplify our proposed approach by extending a dataset of health insurance alternatives.

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Title: Decision-Maker Alignment: Benchmark Datasets
Creators: Anik Sen - Drexel University
Rosina O Weber - Drexel University
Christopher B. Rauch - Drexel University
Mallika Mainali - Drexel University
J T Turner - Knexus Research
John Meyer - Knexus Research
Michael W. Floyd - Knexus Research
Matthew Molineaux - Parallax Research
Publication Details: 2025 IEEE Conference on Artificial Intelligence (CAI), pp 1221-1229
Publisher: IEEE
Resource Type: Conference proceeding
Language: English
Academic Unit: Information Science (Informatics); College of Computing and Informatics
Scopus ID: 2-s2.0-105011294640
Other Identifier: 991022064706604721

Decision-Maker Alignment: Benchmark Datasets

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