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Navigating ethical challenges of explainable ai in autonomous systems
International Journal of Science and Research ArchiveThe 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 +3 more
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What does explainable AI explain?
2023Machine Learning (ML) models are increasingly used in industry, as well as in scientific research and social contexts. Unfortunately, ML models provide only partial solutions to real-world problems, focusing on predictive performance in static environments.
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Explainable AI (XAI): Explained
2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 2023G. Pradeep Reddy, Y. V. Pavan Kumar
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AI Matters, 2018
The power network is the largest operating machine on earth, generating more than US$400bn a year 1 keeping the lights on for our homes, offices, and factories. A significant concern in power networks is for the energy providers to be able to generate enough power to supply the demands at any
Ferdinando Fioretto, William Yeoh
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The power network is the largest operating machine on earth, generating more than US$400bn a year 1 keeping the lights on for our homes, offices, and factories. A significant concern in power networks is for the energy providers to be able to generate enough power to supply the demands at any
Ferdinando Fioretto, William Yeoh
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Gradient based Feature Attribution in Explainable AI: A Technical Review
arXiv.orgThe surge in black-box AI models has prompted the need to explain the internal mechanism and justify their reliability, especially in high-stakes applications, such as healthcare and autonomous driving.
Yongjie Wang +3 more
semanticscholar +1 more source
Explainable AI (XAI) in healthcare: Enhancing trust and transparency in critical decision-making
World Journal of Advanced Research and ReviewsThe integration of artificial intelligence (AI) in healthcare is revolutionizing diagnostic and treatment procedures, offering unprecedented accuracy and efficiency.
Adewale Abayomi Adeniran +2 more
semanticscholar +1 more source
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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IEEE Internet of Things Journal
Detecting botnets is an essential task to ensure the security of Internet of Things (IoT) systems. Machine learning (ML)-based approaches have been widely used for this purpose, but the lack of interpretability and transparency of the models often limits
Rajesh Kalakoti +2 more
semanticscholar +1 more source
Detecting botnets is an essential task to ensure the security of Internet of Things (IoT) systems. Machine learning (ML)-based approaches have been widely used for this purpose, but the lack of interpretability and transparency of the models often limits
Rajesh Kalakoti +2 more
semanticscholar +1 more source