The human-AI relationship in decision-making: AI explanation to support people on justifying their decisions

TL;DR

This paper discusses how explainable AI can support human decision-makers by providing explanations that help justify decisions, thereby strengthening trust and the human-AI relationship.

Contribution

It offers a perspective on the role of XAI in decision-making, emphasizing the importance of AI explanations in justifying decisions and building trust.

Findings

XAI can enhance decision justification processes.

AI explanations influence trust and transparency.

The paper highlights the importance of human-AI relationship in decision scenarios.

Abstract

The explanation dimension of Artificial Intelligence (AI) based system has been a hot topic for the past years. Different communities have raised concerns about the increasing presence of AI in people's everyday tasks and how it can affect people's lives. There is a lot of research addressing the interpretability and transparency concepts of explainable AI (XAI), which are usually related to algorithms and Machine Learning (ML) models. But in decision-making scenarios, people need more awareness of how AI works and its outcomes to build a relationship with that system. Decision-makers usually need to justify their decision to others in different domains. If that decision is somehow based on or influenced by an AI-system outcome, the explanation about how the AI reached that result is key to building trust between AI and humans in decision-making scenarios. In this position paper, we discuss the role of XAI in decision-making scenarios, our vision of Decision-Making with AI-system in the loop, and explore one case from the literature about how XAI can impact people justifying their decisions, considering the importance of building the human-AI relationship for those scenarios.