Explainable analytics in operational research: A defining framework, methods, applications, and a research agenda
[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] pracownik
2024
artykuł naukowy
angielski
- Decision analysis
- XAI
- Explainable artificial intelligence
- Interpretable machine learning
- XAIOR
EN The ability to understand and explain the outcomes of data analysis methods, with regard to aiding decision-making, has become a critical requirement for many applications. For example, in operational research domains, data analytics have long been promoted as a way to enhance decision-making. This study proposes a comprehensive, normative framework to define explainable artificial intelligence (XAI) for operational research (XAIOR) as a reconciliation of three subdimensions that constitute its requirements: performance, attributable, and responsible analytics. In turn, this article offers in-depth overviews of how XAIOR can be deployed through various methods with respect to distinct domains and applications. Finally, an agenda for future XAIOR research is defined.
22.09.2023
249 - 272
CC BY (uznanie autorstwa)
czasopismo hybrydowe
ostateczna wersja opublikowana
przed opublikowaniem
140
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