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Mohammad Naiseh
Mohammad Naiseh
Bournemouth University
Zweryfikowany adres z bournemouth.ac.uk - Strona główna
Tytuł
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How the different explanation classes impact trust calibration: The case of clinical decision support systems
M Naiseh, D Al-Thani, N Jiang, R Ali
International Journal of Human-Computer Studies 169, 102941, 2023
1012023
Personalising explainable recommendations: literature and conceptualisation
M Naiseh, N Jiang, J Ma, R Ali
Trends and Innovations in Information Systems and Technologies: Volume 2 8 …, 2020
502020
Explainable recommendation: when design meets trust calibration
M Naiseh, D Al-Thani, N Jiang, R Ali
World Wide Web 24 (5), 1857-1884, 2021
472021
Explainable Recommendations in Intelligent Systems: Delivery Methods, Modalities and Risks
M Naiseh, N Jiang, J Ma, R Ali
The 14th International Conference on Research Challenges in Information Science., 2020
372020
Explainable recommendations and calibrated trust: two systematic user errors
M Naiseh, D Cemiloglu, N Jiang, D Althani, R Ali
The Computer Journal, 2021
332021
Nudging through Friction: an Approach for Calibrating Trust in Explainable AI
M Naiseh, RS Al-Mansoori, D Al-Thani, N Jiang, R Ali
8th International Conference on Behavioral and Social Computing (BESC), 2021
322021
The fine line between persuasion and digital addiction
D Cemiloglu, M Naiseh, M Catania, H Oinas-Kukkonen, R Ali
International conference on persuasive technology, 289-307, 2021
232021
Trustworthy autonomous systems (TAS): Engaging TAS experts in curriculum design
M Naiseh, C Bentley, SD Ramchurn
2022 IEEE global engineering education conference (EDUCON), 901-905, 2022
142022
Explainability design patterns in clinical decision support systems
M Naiseh
Research Challenges in Information Science: 14th International Conference …, 2020
132020
C-XAI: A conceptual framework for designing XAI tools that support trust calibration
M Naiseh, A Simkute, B Zieni, N Jiang, R Ali
Journal of Responsible Technology 17, 100076, 2024
82024
Outlining the design space of explainable swarm (xswarm): Experts’ perspective
M Naiseh, MD Soorati, S Ramchurn
International symposium on Distributed autonomous robotic systems, 28-41, 2022
72022
Trust, Risk Perception, and Intention to Use Autonomous Vehicles: An Interdisciplinary Bibliometric Review
M Naiseh, J Clark, T Akarsu, Y Hanoch, M Brito, M Eald, T Webster, ...
AI & Society, 2024
62024
The effect of data visualisation quality and task density on human-swarm interaction
AO Abioye, M Naiseh, W Hunt, J Clark, SD Ramchurn, MD Soorati
2023 32nd IEEE International Conference on Robot and Human Interactive …, 2023
52023
Industry Led Use-Case Development for Human-Swarm Operations
JR Clark, M Naiseh, J Fischer, M Galvez Trigo, K Parnell, M Brito, ...
AAAI 2022 Spring Symposium Series (Putting AI in the Critical Loop: Assured …, 2022
52022
C-XAI: Design Method for Explainable AI Interfaces to Enhance Trust Calibration.
M Naiseh
Bournemouth University, 2021
52021
Digital Wellbeing for All: Expanding Inclusivity to Embrace Diversity in Socio-Emotional Status
RS Al-Mansoori, M Naiseh, D Al-Thani, R Ali
34th British HCI Conference (HCI2021), 2021
52021
Enabling trustworthiness in human-swarm systems through a digital twin
MD Soorati, M Naiseh, W Hunt, K Parnell, J Clark, SD Ramchurn
Putting AI in the Critical Loop, 93-125, 2024
42024
The well-being of Autonomous Vehicles (AVs) users under uncertain situations
M Naiseh, P Shukla
Proceedings of the first international symposium on trustworthy autonomous …, 2023
42023
Adaptive Human-Swarm Interaction based on Workload Measurement using Functional Near-Infrared Spectroscopy
AO Abioye, A Landowska, W Hunt, H Maior, SD Ramchurn, M Naiseh, ...
arXiv preprint arXiv:2405.07834, 2024
32024
XAI for group-AI interaction: towards collaborative and inclusive explanation
M Naiseh, C Webb, T Underwood, G Ramchurn, Z Walters, N Thavanesan, ...
In the Second World Conference of Explainable Artificial Intelligence: XAI …, 2024
32024
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