Keynote speaker
Prof. Hani Hagras
University of Essex
True Explainable Artificial Intelligence for Health Applications
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, Hani Hagras introduce the concepts of XAI to achieve a significantly positive for the Health sector to deliver human friendly XAI systems which could be easily understood, analysed and augmented by humans.
Bio
Hani Hagras is a Professor of Artificial Intelligence, Head of the Artificial Intelligence Research Group 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), Principal Fellow of the UK Higher Education Academy (PFHEA) and Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA). His major research interests are in Explainable Artificial Intelligence, computational intelligence and data science .He has authored more than 500 papers in international journals, conferences and books. He is Among the top 2% of the most-cited scientists in the world (Scopus August 2023). His work has received funding from major research councils and industry. He has also Elven industrial patents in the field of Explainable AI, computational intelligence and intelligent control.
His research has won numerous prestigious international awards where 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. 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.
https://www.essex.ac.uk/people/HAGRA01400/Hani-Hagras