Trustworthy artificial intelligence: a review

D Kaur, S Uslu, KJ Rittichier, A Durresi - ACM computing surveys (CSUR …, 2022 - dl.acm.org
Artificial intelligence (AI) and algorithmic decision making are having a profound impact on
our daily lives. These systems are vastly used in different high-stakes applications like …

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 …

[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 …

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

J Amann, A Blasimme, E Vayena, D Frey… - BMC medical informatics …, 2020 - Springer
Background Explainability is one of the most heavily debated topics when it comes to the
application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have …

Explainability of deep vision-based autonomous driving systems: Review and challenges

É Zablocki, H Ben-Younes, P Pérez, M Cord - International Journal of …, 2022 - Springer
This survey reviews explainability methods for vision-based self-driving systems trained with
behavior cloning. The concept of explainability has several facets and the need for …

[HTML][HTML] Trustworthy AI: closing the gap between development and integration of AI systems in ophthalmic practice

C González-Gonzalo, EF Thee, CCW Klaver… - Progress in retinal and …, 2022 - Elsevier
An increasing number of artificial intelligence (AI) systems are being proposed in
ophthalmology, motivated by the variety and amount of clinical and imaging data, as well as …

The coming of age of interpretable and explainable machine learning models

PJG Lisboa, S Saralajew, A Vellido… - Neurocomputing, 2023 - Elsevier
Abstract Machine-learning-based systems are now part of a wide array of real-world
applications seamlessly embedded in the social realm. In the wake of this realization, strict …

Explainable generative ai (genxai): A survey, conceptualization, and research agenda

J Schneider - Artificial Intelligence Review, 2024 - Springer
Generative AI (GenAI) represents a shift from AI's ability to “recognize” to its ability to
“generate” solutions for a wide range of tasks. As generated solutions and applications grow …

How should the results of artificial intelligence be explained to users?-Research on consumer preferences in user-centered explainable artificial intelligence

D Kim, Y Song, S Kim, S Lee, Y Wu, J Shin… - … Forecasting and Social …, 2023 - Elsevier
Artificial intelligence (AI) has become part of our everyday lives, and its presence and
influence are expected to grow exponentially. Regardless of its expanding impact, the …

Explainable artificial intelligence (XAI) with IoHT for smart healthcare: A review

S Bharati, MRH Mondal, P Podder, U Kose - … Cognitive Internet of Things …, 2023 - Springer
Discussing the use of artificial intelligence (AI) in healthcare, explainability is a highly
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …