A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques

M Nazar, MM Alam, E Yafi, MM Su'ud - IEEE Access, 2021 - ieeexplore.ieee.org
Artificial intelligence (AI) is one of the emerging technologies. In recent decades, artificial
intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual …

How cognitive biases affect XAI-assisted decision-making: A systematic review

A Bertrand, R Belloum, JR Eagan… - Proceedings of the 2022 …, 2022 - dl.acm.org
The field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to complex AI
systems. Although it is usually considered an essentially technical field, effort has been …

[HTML][HTML] Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions

L Longo, M Brcic, F Cabitza, J Choi, R Confalonieri… - Information …, 2024 - Elsevier
Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …

Explainable artificial intelligence: objectives, stakeholders, and future research opportunities

C Meske, E Bunde, J Schneider… - Information Systems …, 2022 - Taylor & Francis
Artificial Intelligence (AI) has diffused into many areas of our private and professional life. In
this research note, we describe exemplary risks of black-box AI, the consequent need for …

Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability

LV Herm, K Heinrich, J Wanner, C Janiesch - International Journal of …, 2023 - Elsevier
Abstract Machine learning algorithms enable advanced decision making in contemporary
intelligent systems. Research indicates that there is a tradeoff between their model …

Who should i trust: Ai or myself? leveraging human and ai correctness likelihood to promote appropriate trust in ai-assisted decision-making

S Ma, Y Lei, X Wang, C Zheng, C Shi, M Yin… - Proceedings of the 2023 …, 2023 - dl.acm.org
In AI-assisted decision-making, it is critical for human decision-makers to know when to trust
AI and when to trust themselves. However, prior studies calibrated human trust only based …

The pragmatic turn in explainable artificial intelligence (XAI)

A Páez - Minds and Machines, 2019 - Springer
In this paper I argue that the search for explainable models and interpretable decisions in AI
must be reformulated in terms of the broader project of offering a pragmatic and naturalistic …

Deciding fast and slow: The role of cognitive biases in ai-assisted decision-making

C Rastogi, Y Zhang, D Wei, KR Varshney… - Proceedings of the …, 2022 - dl.acm.org
Several strands of research have aimed to bridge the gap between artificial intelligence (AI)
and human decision-makers in AI-assisted decision-making, where humans are the …

Trustworthy ai

R Chatila, V Dignum, M Fisher, F Giannotti… - Reflections on artificial …, 2021 - Springer
Modern AI systems have become of widespread use in almost all sectors with a strong
impact on our society. However, the very methods on which they rely, based on Machine …

Personalized explanation in machine learning: A conceptualization

J Schneider, J Handali - arxiv preprint arxiv:1901.00770, 2019 - arxiv.org
Explanation in machine learning and related fields such as artificial intelligence aims at
making machine learning models and their decisions understandable to humans. Existing …