Keynotes

Super-Human and Super-AI Cognitive Augmentation of Human and Human-AI Teams Assisted by Brain Computer Interfaces

Abstract

In the last 10 years a major strand of my research within the Essex Brain-Computer Interfaces and Neural Engineering (BCI-NE) laboratory has focused on the idea of combining brain signals (and other physiological and behavioral information) across multiple people to achieve a form of emergent, perceptual and, more generally cognitive, group augmentation, which is more than the sum of the parts.

Over this period (in projects funded mostly by the UK Ministry of Defense and also US DOD) we have developed a technology which has delivered significant (and in fact in some cases remarkable) improvements over the group performance achieved by more
traditional methods of integrating information applying it successfully to progressively more and more real-world applications.

Our efforts have particularly focused on the area of decision making. Decisions (for example made by government, military or hospital management) are often made with limited amounts of information, or indeed too much information for any single person to take in, hence involving a high degree of uncertainty. Yet, such decisions can be highly critical in nature, with mistakes possibly resulting in extremely adverse outcomes, including loss of lives. So, any improvements in accuracy or speed of decisions in such conditions is vitally important.

In the last 5 years we have also started to study hybrid human-AI decision-making groups by the inclusion of one or more AI-based teammates which act as peers to the humans. We found that when the conditions are right (more on this in the talk), human-AI groups produce super-human and super-AI performance.

In this presentation, I will review BCIs and our approach, and will discuss some of the applications we explored including the identification of visual targets in cluttered environments, the comprehension of military radio communication, face recognition, military recognisance missions, military outposts and strategic resource allocation in a pandemic.

I will finally look at potential future developments.

Speaker Bio

Prof Riccardo Poli is with the School of Computer Science and Electronic Engineering (6th in the UK for Research Power) at Essex University. He is a biomedical engineer specialised in BCIs and an expert in machine learning and computational intelligence. After his PhD in 1993, he joined the School of Computer Science of the University of Birmingham, as a Lecturer in AI (1994-1999) and a Reader in Evolutionary and Emergent Behaviour Intelligence and Computation (1999-2001). He joined Essex University in 2001 as a full professor. At Essex he co-founded the Brain Computer Interface and Neural Engineering Laboratory in 2004, which he co-directs since 2016. The lab is one of the world’s largest and better equipped for non-invasive BCIs. It also offers the first BEng in Neural Engineering worldwide.
Prof Poli co-authored 400+ articles (and 2 books) and has approx. 26,000 Scholar citations and an H index of 67. He is on the advisory board of Evolutionary Computation, an Associate Editor for Frontiers in Neuroergonomics and a former associate editor of Genetic Programming and Evolvable Machines, Applied Soft Computing and Swarm Intelligence.

AI for Scientific Discovery and a Sustainable Future

Abstract

Artificial Intelligence (AI) is a rapidly progressing field, achieving remarkable breakthroughs in areas ranging from computer vision and machine translation to world champion-level Go gameplay, autonomous vehicles, and Chat-GPT. The continuously expanding capabilities of AI present promising opportunities for advancements in various domains. I will discuss our AI research directed at accelerating scientific discovery for a sustainable future. Specifically, I'll delve into our work in the emerging interdisciplinary field of Computational Sustainability, which focuses on developing computational methods to tackle pressing sustainability challenges. I will illustrate examples of computational sustainability challenges, including biodiversity conservation, strategic planning for hydropower dams in the Amazon basin, and the discovery of renewable energy materials. I will highlight cross-computational themes and AI challenges, emphasizing the potential for groundbreaking advancements in our pursuit of a sustainable future.

Speaker Bio

Carla Gomes is the Ronald C. and Antonia V. Nielsen Professor of Computing and Information Science, the director of the Institute for Computational Sustainability at Cornell University, and co-director of the Cornell University AI for Science Institute. Gomes received a Ph.D. in computer science in artificial intelligence from the University of Edinburgh. Her research area is Artificial Intelligence with a focus on large-scale constraint reasoning, optimization, and machine learning. Recently, Gomes has become deeply immersed in research on scientific discovery for a sustainable future and, more generally, in research in the new field of Computational Sustainability. Computational Sustainability aims to develop computational methods to help solve some of the key environmental, economic, and societal challenges to help put us on a path toward a sustainable future. Gomes was the lead PI of two NSF Expeditions in Computing awards. Gomes has (co-)authored over 200 publications, which have appeared in venues spanning Nature, Science, and a variety of conferences and journals in AI and Computer Science, including five best paper awards. Gomes was named the “most influential Cornell professor” by a Merrill Presidential Scholar (2020). Gomes was also the recipient of the Association for the Advancement of Artificial Intelligence (AAAI) Feigenbaum Prize (2021) for “high-impact contributions to the field of artificial intelligence, through innovations in constraint reasoning, optimization, the integration of reasoning and learning, and through founding the field of Computational Sustainability, with impactful applications in ecology, species conservation, environmental sustainability, and materials discovery for energy” and of the 2022 ACM/AAAI Allen Newell Award, for contributions bridging computer science and other disciplines. Gomes is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a Fellow of the Association for Computing Machinery (ACM), and a Fellow of the American Association for the Advancement of Science (AAAS).

Evolutionary Computation Evolving

Abstract

I have had the privilege of involvement in this field from its early days. The result is a rather unique and comprehensive perspective on its development and growth. In this talk I use that perspective to highlight some important milestones, discuss some current issues and suggest some directions for the future.

Speaker Bio

Kenneth A. De Jong received his Ph.D. in computer science from the University of Michigan in 1975. He has held faculty positions at the University of Pittsburgh and George Mason University. He is currently a Professor Emeritus of Computer Science at George Mason University. His research interests include evolutionary computation, machine learning, and complex adaptive systems. He is an active member of the Evolutionary Computation research community, the author of a wide variety of publications including a book on evolutionary computation, and has been involved in organizing many of the workshops and conferences in this area. He is the founding editor-in-chief of the journal Evolutionary Computation (MIT Press), and a member of the board of ACM SIGEVO. He is the recipient of an IEEE Pioneer award in the field of Evolutionary Computation and a lifetime achievement award from the Evolutionary Programming Society.