Ethics & AI: A systematic review on ethical concerns and related strategies for designing with AI in healthcare

F Li, N Ruijs, Y Lu - Ai, 2022 - mdpi.com
In modern life, the application of artificial intelligence (AI) has promoted the implementation
of data-driven algorithms in high-stakes domains, such as healthcare. However, it is …

Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives

A Rawal, J McCoy, DB Rawat… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …

Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success

Y Chen, S Jensen, LJ Albert, S Gupta, T Lee - Information Systems …, 2023 - Springer
In higher education, low teacher-student ratios can make it difficult for students to receive
immediate and interactive help. Chatbots, increasingly used in various scenarios such as …

[HTML][HTML] Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities

W Saeed, C Omlin - Knowledge-based systems, 2023 - Elsevier
The past decade has seen significant progress in artificial intelligence (AI), which has
resulted in algorithms being adopted for resolving a variety of problems. However, this …

What do we want from Explainable Artificial Intelligence (XAI)?–A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research

M Langer, D Oster, T Speith, H Hermanns, L Kästner… - Artificial intelligence, 2021 - Elsevier
Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

[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 …

A manifesto on explainability for artificial intelligence in medicine

C Combi, B Amico, R Bellazzi, A Holzinger… - Artificial Intelligence in …, 2022 - Elsevier
The rapid increase of interest in, and use of, artificial intelligence (AI) in computer
applications has raised a parallel concern about its ability (or lack thereof) to provide …

The ethics of algorithms: key problems and solutions

A Tsamados, N Aggarwal, J Cowls, J Morley… - Ethics, governance, and …, 2021 - Springer
Research on the ethics of algorithms has grown substantially over the past decade.
Alongside the exponential development and application of machine learning algorithms …

A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences

M Graziani, L Dutkiewicz, D Calvaresi… - Artificial intelligence …, 2023 - Springer
Since its emergence in the 1960s, Artificial Intelligence (AI) has grown to conquer many
technology products and their fields of application. Machine learning, as a major part of the …

Towards explainable artificial intelligence

W Samek, KR Müller - … AI: interpreting, explaining and visualizing deep …, 2019 - Springer
In recent years, machine learning (ML) has become a key enabling technology for the
sciences and industry. Especially through improvements in methodology, the availability of …