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Explainable AI for Financial Forecasting
2022One 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 +3 more
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Communications of the ACM, 2018
It is increasingly important to understand how artificial intelligence comes to a decision.
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It is increasingly important to understand how artificial intelligence comes to a decision.
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With the rapid development of Artificial Intelligence (AI) in many areas, demand for explainability and reliability of systems has also increased. AI Explainability (XAI) addresses the study of AI that can be understood by humans, since interpretability is essential for user trust, ethical, and legal issues.
Varnesh Ghildiyal +3 more
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Varnesh Ghildiyal +3 more
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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 ...
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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 ...
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Choose for AI and for Explainability
2020As 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.
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Explaining explainable AI for healthcare: a Q-methodology study
Information, Communication & SocietyTechnological 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 +5 more
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Visualization for AI Explainability
IEEE Computer Graphics and Applications, 2022L. Miguel Encarnação +2 more
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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
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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