Results 131 to 140 of about 56,159 (288)

AI Alignment Versus AI Ethical Treatment: 10 Challenges

Analytic Philosophy, EarlyView.
ABSTRACT A morally acceptable course of AI development should avoid two dangers: creating unaligned AI systems that pose a threat to humanity and mistreating AI systems that merit moral consideration in their own right. This paper argues these two dangers interact and that if we create AI systems that merit moral consideration, simultaneously avoiding ...
Adam Bradley, Bradford Saad
wiley   +1 more source

Exploration and practice of XAI architecture

大数据
XAI(explainable AI) is an important component of trusted AI.In-depth research on the technology points of XAI has been carried out in the current industry, but systematic research on engineering implementation is lacking.This paper proposed a general XAI
Zhengxun XIA, Jianfei TANG, Yifan YANG, Shengmei LUO, Yan ZHANG, Fenglei TAN, Shengru TAN   +6 more
doaj  

Developing Explainable Artificial Intelligence Models for Space Science Applications

Space: Science & Technology
The integration of explainable artificial intelligence (XAI) in space science has ushered in a new era of transparency and reliability in AI-driven applications.
Ambuj Kumar Agarwal, Rajat Bhardwaj, Gyanendra Tiwary, Abeer A. Aljohani, Ruchi Kawatra, Abhijit Das   +5 more
doaj   +1 more source

Factor analysis of evacuation behavior during heavy rain using eXplainable AI(XAI)

, 2022
Michirou Tsukamoto, Akiyoshi TAKAGI
openalex   +2 more sources

Personalized Model‐Driven Interventions for Decisions From Experience

Topics in Cognitive Science, EarlyView.
Abstract Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance‐based learning ...
Edward A. Cranford, Christian Lebiere, Cleotilde Gonzalez, Palvi Aggarwal, Sterling Somers, Konstantinos Mitsopoulos, Milind Tambe   +6 more
wiley   +1 more source

Explainable Artificial Intelligence (XAI): Classification of Medical Thermal Images of Neonates Using Class Activation Maps

, 2021
Ahmet Haydar Örnek, Murat Ceylan
openalex   +2 more sources

Modeling and generating user‐centered contrastive explanations for the workforce scheduling and routing problem

International Transactions in Operational Research, Volume 33, Issue 3, Page 1525-1558, May 2026.
Abstract In the last decade, explainability has been attracting much attention in the machine learning community. However, this research topic extends beyond this field to encompass others such as operations research and combinatorial optimization (CO).
Mathieu Lerouge, Céline Gicquel, Vincent Mousseau, Wassila Ouerdane   +3 more
wiley   +1 more source

The Role of Explainable Artificial Intelligence (XAI) in Enhancing Strategic Decision-Making: A Mixed-Methods Approach Across Industries [PDF]

Mojtaba Ghorbani Asiabar, Morteza Ghorbani Asiabar, Alireza Ghorbani Asiabar   +2 more
openalex   +1 more source

Artificial Intelligence‐assisted Endoscopy and Examiner Confidence: A Study on Human–Artificial Intelligence Interaction in Barrett's Esophagus (With Video)

DEN Open, Volume 6, Issue 1, April 2026.
ABSTRACT Objective Despite high stand‐alone performance, studies demonstrate that artificial intelligence (AI)‐supported endoscopic diagnostics often fall short in clinical applications due to human‐AI interaction factors. This video‐based trial on Barrett's esophagus aimed to investigate how examiner behavior, their levels of confidence, and system ...
David Roser, Michael Meinikheim, Anna Muzalyova, Robert Mendel, Christoph Palm, Andreas Probst, Sandra Nagl, Markus W. Scheppach, Christoph Römmele, Elisabeth Schnoy, Nasim Parsa, Michael F. Byrne, Helmut Messmann, Alanna Ebigbo   +13 more
wiley   +1 more source

Explainable Artificial Intelligence in Paediatric: Challenges for the Future

Health Science Reports
Background Explainable artificial intelligence (XAI) emerged to improve the transparency of machine learning models and increase understanding of how models make actions and decisions.
Ahmed M. Salih, Gloria Menegaz, Thillagavathie Pillay, Elaine M. Boyle   +3 more
doaj   +1 more source