Towards an Argumentative Foundation for Evaluative AI

The evaluative artificial intelligence (IAE) approach is a recent development aimed at supporting human decision-making, not by providing a single recommendation, but by presenting opposing hypotheses along with evidence for and against each one. In this work, the use of computational argumentation is defended as a particularly suitable paradigm for providing a formal and calculable basis for explainable and question-able forms of IAE. This lays the groundwork for a long-term research agenda focused on developing human-centered and distributed IAE systems. The application of computational argumentation in this context may enable the creation of more transparent and reliable IAE systems. This news is significant because IAE has the potential to significantly improve decision-making in various areas, and research in this field could lead to substantial advancements in how artificial intelligence supports humans in making informed decisions.

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