The Need for Fuzzy AI by Prof Jonathan Garibaldi
Abstract
Artificial intelligence (AI) is once again a topic of huge interest around the world. Whilst advances in the capability of machines are being made at an incredible rate, there is also increasing focus on the need for computerised systems to be able to explain their decisions, at least to some degree. It is also clear that data and knowledge in the real world are characterised by uncertainty.
Fuzzy systems based on Zadeh's Fuzzy Sets introduced in 1965 can provide decision support systems, which both handle uncertainty and have explicit representations of uncertain knowledge and inference processes. However, it is not yet clear how any decision support systems, including those featuring fuzzy methods, should be evaluated as to whether their use is permitted.
In this talk, I will present how uncertainty pervades all aspects of real-world data, knowledge and decision making; and discuss how we can evaluate when AI systems are ready for deployment in the real world. In doing so, I will argue for the need for ‘fuzzy AI’ in two senses: (i) the need to use fuzzy methodologies within knowledge-based systems to represent and reason with uncertainty; and (ii) the need for fuzziness in evaluating AI systems, including acceptance of imperfect performance.
Biography
Professor Garibaldi initially completed a BSc in Physics at the University of Bristol UK. He completed his MSc and PhD in ‘Artificial Intelligence’ at the University of Plymouth UK. He joined the School of Computer Science, University of Nottingham UK in 2002, becoming full Professor in 2012. He became the Head of School of Computer Science in Jan 2016.
Professor Garibaldi's main research interest is in developing intelligent computational techniques to model human reasoning in uncertain environments, with a particular emphasis on the medical domain. He also has interests in data analysis, particularly of complex and uncertain data, data mining, clustering and classification, and in the deployment of decision support systems in practical real-world applications.
Over his career, he has been Principal Investigator on research projects worth over £3.5m, and Co-Investigator on a multi-disciplinary portfolio of grants worth over £82m. He has published over 400 academic research papers, including around 200 journal papers. He was Editor-in-Chief of IEEE Transactions on Fuzzy Systems from 2017–2022, is currently Vice-President of Publications in the IEEE Computational Intelligence Society, and is a Fellow of the IEEE. He is also currently a Senior Editor of IEEE Access.