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Due to the opacity of machine learning technology, there is a need forexplainability and fairness in the decision support systems used in public orprivate organizations. Although the criteria for appropriate explanations andfair decisions change depending on the values of those who are affected by thedecisions, there is a lack of discussion framework to consider the appropriateoutputs for each stakeholder. In this paper, we propose a discussion frameworkthat we call "stakeholder-in-the-loop fair decisions." This is proposed toconsider the requirements for appropriate explanations and fair decisions. Weidentified four stakeholders that need to be considered to design accountabledecision support systems and discussed how to consider the appropriate outputsfor each stakeholder by referring to our works. By clarifying thecharacteristics of specific stakeholders in each application domain andintegrating the stakeholders' values into outputs that all stakeholders agreeupon, decision support systems can be designed as systems that ensureaccountable decision makings.

Stakeholder-in-the-Loop Fair Decisions: A Framework to Design Decision Support Systems in Public and Private Organizations