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学术报告第202025期

发布时间:2020-12-18 编辑:张惠兰 来源:科研

报告题目:TOWARDS HUMAN-FRIENDLY EXPLAINABLE ARTIFICIAL INTELLIGENCE

人:Hani Hagras教授(University of Essex

报告时间:202012201800

报告地点:线上报告


Abstract: The recent advances in computing power coupled with the rapid increases in the quantity of available data has led to a resurgence in the theory and applications of Artificial Intelligence (AI). However, the use of complex AI algorithms could result in a lack of transparency to users which is termed as black/opaque box models. Thus, for AI to be trusted and widely used by governments and industries, there is a need for greater transparency through the creation of human friendly explainable AI (XAI) systems. XAI aims to make machines understand the context and environment in which they operate, and over time build underlying explanatory models that allow them to characterize real-world phenomena. The XAI concept provides an explanation of individual decisions, enables understanding of overall strengths and weaknesses, and conveys an understanding of how the system will behave in the future and how to correct the system’s mistakes. In this keynote speech, we introduce the concepts of XAI by moving towards “explainable AI” (XAI) to achieve a significantly positive impact on communities and industries all over the world and we will present novel techniques enabling to deliver human friendly XAI systems which could be easily understood, analysed and augmented by humans. This will allow to the wider deployment of AI systems which are trusted in various real world applications


Bio: Hani Hagras is a Professor of Explainable Artificial Intelligence, Director of Research and Director of the Computational Intelligence Centre in the University of Essex, UK. He is a Fellow of Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the Institution of Engineering and Technology (IET) and Principal Fellow of the UK Higher Education Academy (PFHEA)

His major research interests are in Explainable Artificial Intelligence, computational intelligence and data science . His research interests also include ambient intelligence, pervasive computing and intelligent buildings. He is also interested in embedded agents, robotics and intelligent control.

He has authored more than 350 papers in international journals, conferences and books. His work has received funding from major research councils and industry. He has also Ten industrial patents in the field of Explainable AI, computational intelligence and intelligent control.

His research has won numerous prestigious international awards where most recently he was awarded by the IEEE Computational Intelligence Society (CIS), the 2013 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems and also he has won the 2004 Outstanding Paper Award in the IEEE Transactions on Fuzzy Systems. He was also awarded the 2015 and 2017 Global Telecommunications Business award for his joint project with British Telecom. In 2016, he was elected as Distinguished Lecturer by the IEEE Computational Intelligence Society. He was also the Chair of the IEEE CIS Chapter that won the 2011 IEEE CIS Outstanding Chapter award. His work with IP4 Ltd has won the 2009 Lord Stafford Award for Achievement in Innovation for East of England. His work has also won the 2011 Best Knowledge Transfer Partnership Project for London and the Eastern Region. His work has also won best paper awards in several conferences including the 2014 and 2006 IEEE International Conference on Fuzzy Systems and the 2012 UK Workshop on Computational Intelligence.

He is an Associate Editor of the IEEE Transactions on Fuzzy Systems. He is also an Associate Editor of the International Journal of Robotics and Automation.

Prof. Hagras chaired several international conferences where he will act as the Programme Chair of the 2021 IEEE International Conference on Fuzzy Systems and he served as the programme chair of the 2017 IEEE International Conference on Fuzzy Systems. He served as the Co-Chair of the 2014, 2013, 2011 and 2009 IEEE Symposium on Intelligent Agents, and the 2011 IEEE International Symposium on Advances to Type-2 Fuzzy Logic Systems. He was also the General Co-Chair of the 2007 IEEE International Conference on Fuzzy systems.




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