Pith. sign in

REVIEW 1 cited by

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

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2102.05460 v2 pith:CN6XJCHT submitted 2021-02-10 cs.HC cs.AI

classification cs.HCcs.AI
keywords decision-makingpeoplescenariosexplanationrelationshipai-systembuildingdecision
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Engaging with AI: How Interface Design Shapes Human-AI Collaboration in High-Stakes Decision-Making

    cs.HC 2025-01 reject novelty 5.0 of 10

    In a controlled comparison, AI confidence levels and text explanations improved human-AI decision accuracy, while reflective questions and human feedback increased effort and reduced trust.

Pith tools