Results 271 to 280 of about 4,635,657 (309)

Explainable AI for Financial Forecasting

2022
One of the most important steps when employing machine learning approaches is the feature engineering process. It plays a key role in the identification of features that can effectively help modeling the given classification or regression task. This process is usually not trivial and it might lead to the development of handcrafted features.
Salvatore Carta, Alessandro Sebastian Podda, Diego Reforgiato Recupero, Maria Madalina Stanciu   +3 more
openaire   +2 more sources

Human-centered evaluation of explainable AI applications: a systematic review

Frontiers in Artificial Intelligence
Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there's been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations.
Jenia Kim, Henry Maathuis, Danielle Sent
exaly   +2 more sources

Chess and explainable AI

ICGA Journal
Chess, once famously referred to as the drosophila of artificial intelligence (AI) research, has been a significant domain for developing intelligent AI agents capable of achieving super-human performance in domains previously dominated by humans. However, the emphasis on unceasingly improved playing strength has come at the cost of neglecting other ...
openaire   +1 more source

Choose for AI and for Explainability

2020
As an expert in decision support systems development, I have been promoting transparency and self-explanatory systems to close the plan-do-check-act cycle. AI adoption has tripled in 2018, moving AI towards the Gartner-hype-cycle peak. As AI is getting more mainstream, more conservative companies have good reasons to enter this arena.
openaire   +1 more source

Explaining explainable AI for healthcare: a Q-methodology study

Information, Communication & Society
Technological innovations are being developed and introduced at a rapid pace to manage increasing demand on the healthcare system. Artificial intelligence (AI) tools promise to improve patient access to quality care and reduce work burden for staff.
Howe, Sydney, Horbach, Daan, van Rijn, Lucas, Gaff, Morris, van Exel, Job, Wehrens, Rik   +5 more
openaire   +2 more sources

Visualization for AI Explainability

IEEE Computer Graphics and Applications, 2022
L. Miguel Encarnação, Jörn Kohlhammer, Chad A. Steed   +2 more
openaire   +1 more source

Navigating ethical challenges of explainable ai in autonomous systems

International Journal of Science and Research Archive
The rapid integration of autonomous systems, such as vehicles, drones, and robots, into various sectors brings forth significant ethical challenges concerning their decision-making processes.
Joseph Chukwunweike, Oluwarotimi Ayodele Lawal, John Babatope Arogundade, Bolape Alad e   +3 more
semanticscholar   +1 more source

Explainable AI

2020
Abstract Deep connectionist learning has resulted in very impressive accomplishments, but it is unclear how it achieves its results. A dilemma in using the output of machine learning is that the best performing methods are the least explainable. Explainable artificial intelligence seeks to develop systems that can explain their reasoning
openaire   +2 more sources

Explaining explainable AI

2023
Richard Zuroff, Nicolas Chapados
openaire   +1 more source

Using explainable AI to unravel classroom dialogue analysis: Effects of explanations on teachers' trust, technology acceptance and cognitive load

British Journal of Educational Technology
Deep neural networks are increasingly employed to model classroom dialogue and provide teachers with prompt and valuable feedback on their teaching practices.
Deliang Wang, Cunling Bian, Gaowei Chen
semanticscholar   +1 more source