Collaborative intelligence – how many shades of grey do we need?
by Dr Trevor Martin, Professor of Artificial Intelligence, University of Bristol, UK and Senior Research Fellow, BT
Recent years have seen a resurgence in AI, fueled by the combination of computing power, new algorithms, and vastly increased generation and storage of data. The new AI is data-driven where the previous generation of AI was knowledge-driven; however in both cases, we can make a distinction between autonomous and collaborative intelligent systems. In the autonomous case, a system performs tasks without significant human input, with examples ranging from product recommendation and game-playing to control of appliances and driverless vehicles.
|In contrast, collaborative intelligent systems aim to use the complementarystrengths of humans and computers in partnership – for example, in assisted driving, computer-aided diagnosis and in complex data analysis tasks. Situation awareness – where multiple heterogeneous sources of data must be integrated – is ideally suited to a collaborative intelligence approach, in which human analysts provide insight and interpretation, while machines perform data collection, repetitive processing and visualisation. An important aspect of collaborative intelligence is the common definition of terms used by humans and machines to identify and categorise the entities, relations and events under consideration. In this talk we will argue that fuzzy set theory gives a natural framework for the interaction and exchange of information between analysts and machines. We will describe a new approach to the definition of fuzzy hierarchies, and show how this assists collaborative intelligence in the field of situation awareness.|
Trevor Martin is Professor of Artificial Intelligence at the University of Bristol, UK and a BT Senior Research Fellow, working with the Security Futures Practice. His research covers soft computing in artificial intelligence applied to areas such as security analytics, extraction and integration of semi-structured information, soft concept hierarchies, and fundamental approaches to fuzzy uncertainty. In addition to substantial funding from BT, this work has been supported by the European Commission, MOD, GCHQ, EPSRC and DTI. He is a member of the editorial boards of journals such as Fuzzy Sets and Systems and Evolving Systems, and has served on many conference programme and organising committees, including IEEE Fuzzy Systems programme chair in 2007 and technical co-chair in 2010 and 2015. He is a co-organiser of the URSW (Uncertain Reasoning for the Semantic Web) series of workshops, chairs the IEEE Computational Intelligence Society’s Semantic Web Task Force and is a member of the IEEE’s recently established FML (Fuzzy Markup Language) Standards group. He has published over 200 papers in refereed conferences, journals and books, and is named inventor on 12 patents. He is a Chartered Engineer and member of the BCS and IEEE, as well as serving on the UK EPSRC College.