Explainable Ai Xai: Research Area — Prolific Citations Library

Discover 6 peer-reviewed studies in Explainable Ai Xai (2021–2025). Explore research findings powered by Prolific's diverse participant panel.

This page lists 6 peer-reviewed papers in the research area of Explainable Ai Xai in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (6 of 6)

Don't Be Fooled: The Misinformation Effect of Explanations in Human-AI Collaboration

Authors: P Spitzer, J Holstein, K Morrison

Year: 2025

Published in: ... Journal of Human ..., 2025 - Taylor & Francis

Institution: Karlsruhe Institute of Technology, Carnegie Mellon University, University of Bayreuth

Research Area: Human-AI Collaboration, Explainable AI (XAI)

Discipline: Human-Computer Interaction (HCI)

Incorrect explanations in AI-assisted decision-making lead to a misinformation effect, negatively impacting human reasoning, procedural knowledge, and collaboration performance.

Methods: A study on human-AI collaboration involving AI-supported decision-making paired with explainable AI (XAI) to assess the effects of incorrect explanations.

Key Findings: Impact of incorrect explanations on human reasoning strategies, procedural knowledge, and team performance in human-AI collaboration.

Citations: 13

Sample Size: 160
Imperfections of XAI: phenomena influencing AI-assisted decision-making

Authors: P Spitzer, K Morrison, V Turri, M Feng, A Perer

Year: 2025

Published in: ACM Transactions on ..., 2025 - dl.acm.org

Institution: Carnegie Mellon University, Karlsruhe Institute of Technology, University of Bayreuth

Research Area: Explainable AI (XAI), AI-Assisted Decision-Making, Human-AI Collaboration

Discipline: Artificial Intelligence

The study highlights how imperfect explainable AI (XAI), along with human cognitive styles, affects reliance on AI and the performance of human–AI teams, providing design guidelines for better collaboration systems.

Methods: The researchers conducted a study with 136 participants, analyzing the effects of explanation imperfections and cognitive styles on AI-assisted decision-making and human–AI collaboration.

Key Findings: The impact of incorrect explanations and explanation modalities on human reliance, decision-making, and human–AI team performance, as well as the role of cognitive styles.

Citations: 2

Sample Size: 136
I know this looks bad, but I can explain: Understanding when AI should explain actions in human-AI teams

Authors: R Zhang, C Flathmann, G Musick, B Schelble

Year: 2024

Published in: ACM Transactions on ..., 2024 - dl.acm.org

Institution: North Carolina State University, University of North Carolina at Charlotte, University of Georgia, University of Michigan

Research Area: Explainable AI (XAI), Human-AI Teaming, Human-Computer Interaction (HCI)

Discipline: Robotics, Artificial Intelligence

Explored how AI explanations impact human trust and team effectiveness in human-AI teams, finding that explanations increase trust when AI disobeys orders but reduce trust when AI lies, with individual characteristics influencing these perceptions.

Methods: Conducted an online experiment analyzing participant responses to scenarios where AI explained its actions within a teamwork context, comparing trust in AI versus human teammates.

Key Findings: Impact of AI explanations on human trust, team effectiveness, and how these vary with teammate identity (human or AI) and participant characteristics (e.g., gender, ethical framework).

DOI: https://doi.org/10.1145/3635474

Citations: 28

Sample Size: 156
Complementarity in Human-AI Collaboration: Concept, Sources, and Evidence

Authors: P Hemmer, M Schemmer, N Kühl, M Vössing, G Satzger

Year: 2024

Published in: ArXiv

Institution: Karlsruhe Institute of Technology

Research Area: Human-AI Collaboration, Explainable AI (XAI), Complementarity in Decision Making

Discipline: Human-Computer Interaction (HCI)
Explanations can reduce overreliance on ai systems during decision-making

Authors: H Vasconcelos, M Jörke

Year: 2023

Published in: Proceedings of the ..., 2023 - dl.acm.org

Institution: Stanford University, University of Washington

Research Area: Human-AI Interaction, Explainable AI (XAI), Decision-Making

Discipline: Human-Computer Interaction (HCI), Artificial Intelligence

DOI: https://doi.org/10.1145/3579605

Citations: 405
The impact of explanations on layperson trust in artificial intelligence-driven symptom checker apps: experimental study

Authors: C Woodcock, B Mittelstadt, D Busbridge

Year: 2021

Published in: Journal of medical Internet ..., 2021 - jmir.org

Institution: Oxford University, Alan Turing Institute, University of Edinburgh

Research Area: Health Informatics, Explainable AI (XAI), Trust in AI, Digital Health

Discipline: Digital Health

DOI: https://doi.org/10.2196/29386

Citations: 52