The presentation will highlight a wide range of important aspects of Explainable Artificial Intelligence.
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Synopsis
The presentation will highlight a wide range of important aspects of Explainable Artificial Intelligence (XAI) such as informativeness, trustworthiness, fairness, transparency, causality, transferability, reliability, accessibility, privacy, safety, verifiability and accountability. The topics discussed will be mainly related but only not limited to the following aspects of XAI: local and global scope, specific and agnostic models, pre, intrinsic and post-hoc stages as well as global, local, constructive, what-if, counterfactual and example-based explanations.
Other topics discussed will be related to real-world bias of Artificial Intelligence (AI), how this bias is reflected in data bias, the encoding of the latter in algorithmic bias and its uncovering by XAI which can then be used to close the loop by mitigating real-world bias.
The presentation will also highlight challenges and future directions in XAI such as formalisation and evaluation of explanations, their adoption in the industry, their potential for improving human-machine collaboration, as well as their ability to facilitate collective intelligence, responsibility, security and causality in AI.
About the speaker
Dr Alex Gegov
Associate Professor in Computational Intelligence in the School of Computing at the University of Portsmouth. Visiting Professor in Control Theory in the English Faculty of Engineering at the Technical University of Sofia. Been Associate Dean Research for the Faculty of Technology at the University of Portsmouth.
PhD in Cybernetics and a DSc in Artificial Intelligence – both from the Bulgarian Academy of Sciences. Been a recipient of a national award for best young researcher from the Bulgarian Union of Scientists.
Humboldt Guest Researcher at the Universities of Duisburg and Wuppertal in Germany. Also been EU Visiting Researcher at the Delft University of Technology in the Netherlands. Research interests are in the development of artificial intelligence and machine learning methods as well as their application for modelling and simulation of complex systems and networks.
Guest edited several special issues of journals and books with conference proceeding published by IEEE and Springer. Authored 5 research monographs and more than 20 book chapters published by Springer. More than 100 articles and papers in a wide range of peer-reviewed specialised journals and international conferences including IEEE journals and conferences. Presented more than 20 invited lectures and tutorials at international scientific events including IEEE, EPSRC and NATO Conferences and Summer Schools on Artificial Intelligence, Fuzzy Systems, Neural Networks, Intelligent Systems, Computational Intelligence, Cybernetics and Complexity Science. Been actively involved as PhD Supervisor and PhD Examiner. Been Principal Investigator and Co-Investigator on research projects funded by NATO, EU, EPSRC and Innovate UK.
Associate Editor for the IEEE Transactions on Artificial Intelligence, the IEEE Transactions on Fuzzy Systems, the International Journal of Intelligent Systems, the Journal of Fuzzy Sets and Systems, the Journal of Intelligent and Fuzzy Systems, and the International Journal of Computational Intelligence Systems. Reviewer for several journals including IEEE Transactions on Neural Networks and Assessor for several national research councils including EPSRC.
Currently Member of the Soft Computing Technical Committee of the IEEE Society of Systems, Man and Cybernetics and the Outstanding Paper Award Committee of the IEEE Computational Intelligence Society.
Member of the IEEE Working Groups on Explainable Artificial Intelligence and Trustworthy Artificial Intelligence as well as the IEEE Task Forces on Explainable Fuzzy Systems and Fuzzy Systems Software.
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