Towards an Argumentative Foundation for Evaluative AI

面向评估式人工智能的论证基础

Abstract: Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting competing hypotheses together with evidence for and against each.

摘要： 评估式人工智能（Evaluative AI, EAI）作为一种支持人类决策的新方法被提出，它不再仅仅提供单一的建议，而是通过呈现相互竞争的假设，并提供支持或反对各项假设的证据来辅助决策。

In this position paper, we advocate (computational) argumentation as a particularly suitable paradigm to provide a formal, computable foundation for forms of EAI that are explainable and contestable, setting the ground for a long-term research agenda towards distributed and human-centred EAI systems.

在这篇立场论文中，我们主张将（计算）论证作为一种特别合适的范式，为可解释且可质疑的评估式人工智能提供形式化、可计算的基础，从而为实现分布式和以人为本的评估式人工智能系统的长期研究议程奠定基础。