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Real Artificial Intelligence - Speakers

Details of the speakers and their presentations will be given below.

Professor Juergen Branke (Warwick Business School)

Learning to optimise - optimal learning

This talk discusses the relationship between machine learning and optimisation. It demonstrates that many machine learning problems are actually optimisation problems, and could benefit from advances in operational research. On the other hand, the latest challenges in optimisation, such as parameter tuning, algorithm selection, Hyper heuristics or handling of uncertainty are actually closely related to machine learning. Furthermore, recent algorithmic developments such as Bayesian Optimisation very much blur the boundary between machine learning and optimisation, as they explicitly combine learning about the search space with optimisation.

Juergen Branke is Professor of Operational Research and Systems at the University of Warwick, UK. He received his PhD from the University of Karlsruhe, Germany, in 2000 and has been an active researcher in the area of nature-inspired optimization for almost 25 years. He has published over 180 articles in international journals and conferences on various topics including multiobjective optimization, handling of uncertainty in optimization, dynamically changing optimization problems, and the design of complex systems. Professor Branke is Area Editor of the Journal of Heuristics and of the Journal of Multi-Criteria Decision Analysis, and Associate Editor of the Evolutionary Computation Journal and of IEEE Transactions on Evolutionary Computation.

Dr Danica Damljanovic (Sentient Machines)

How is AI enhancing the future of human communication?

We have seen a rapid growth of AI-enabled applications in recent years, with breakthroughs in areas from Computer Vision to Speech Processing. Understanding spoken language is one of the most challenging areas of AI, as it involves interpretation of human language which is often ambiguous, but also dependant on many other communication sources such as gesture, previous knowledge, or context. In this talk, you will learn about how AI can be used in practical applications to help people communicate smoothly using natural language. This is especially important in call centres where emotions such as anger or frustration can cause miscommunication and significantly affect agent productivity and customer satisfaction. We will show real-world examples from our case studies to demonstrate the power of AI and how it can be used to empower smarter human communication, through generating bespoke training recommendations for agents, helping them to deliver an excellent service for their customers.

Dr Danica Damljanovic, CEO and Founder of Sentient Machines, is an entrepreneur, computer engineer and experienced research scientist with a PhD in Artificial Intelligence (AI) from the University of Sheffield. Her academic research in Natural Language Processing (NLP) is balanced with industry experience, having worked with the SRI team that developed Apple's Siri, and then Recordsure, analysing human voice. She's featured in more than 50 publications including a book on text analytics, cited over 1600 times. After recognising a growing opportunity to disrupt the global 334 billion pound contact centres industry she used her passion for AI, especially NLP and reasoning to found Sentient Machines - a deep tech company analysing speech and sentiment on a mission to transform the future of human communication. Today they are backed by an award-winning accelerator Entrepreneur First, Innovate UK, GovStart and entrepreneurs from DeepMind/Google.

Richard Moore (Anglia Water)

Leveraging AI for Insights at Anglia Water

Data science has been a hot topic for a few years now, behind the glamour of exciting new models is the not so exciting capabilities that have to be in place to be successful. Results are obviously important, but more important is creating the right environment where results are just inevitable. Find out how an exploration approach and community of practice can help build a sustainable capability, one focused on value and one that doesn't only involve data scientists.

Richard Moore is the Analytics and Insight Manger at Anglian Water, a career developed since joining the company 14 years ago as an analyst. Over the past 3 years Richard has been developing an enterprise-wide analytics community of practice and data science exploration capability.

Prof Lorna McGregor (University of Essex)

AI governance: adopting an ethical and human rights-based approach

The use of machine learning to support decision-making processes has the potential to affect a wide range of human rights, including but beyond privacy and the prohibition of non-discrimination, particularly when used in areas such as employment, housing, detention and social care. This presentation will outline the types of risks to human rights presented by AI and how the existing human rights framework can be integrated into the design, development and deployment of AI as well as governance frameworks and national AI strategies to effectively address these risks.

Lorna McGregor is a Professor of International Human Rights Law and Director of the Human Rights Centre at the University of Essex. Lorna's current research focuses on big data, artificial intelligence (AI) and human rights. She is the PI and Director of the multidisciplinary ESRC Human Rights, Big Data and Technology (HRBDT) project. Her research has been funded by the British Academy, the ESRC and the Nuffield Foundation. Lorna is a Co-Chair of the International Law Association's Study Group on Individual Responsibility in International Law and a Contributing Editor of EJIL Talk!. She has held positions as a Commissioner of the British Equality and Human Rights Commission (2015 - 2019) and as a trustee of the AIRE Centre. Prior to becoming an academic, Lorna held positions at REDRESS, the International Bar Association, and the International Centre for Ethnic Studies in Sri Lanka.

Duncan Russell (Ocado)

AI at Ocado

Artificial Intelligence (AI) offers the prospect of a frictionless existence, making us more efficient, helping us prevent mistakes, spotting the onset of potential problems before they become problems, and enabling us to spend more time on the things that really matter to us. At Ocado, our customers’ orders are picked and packed in highly automated warehouses using swarms of purpose-built robots. These robots are capable of collaborating to pick a typical 50-item order in a matter of minutes. This process makes up part of the Ocado Smart Platform, our end-to-end ecommerce, fulfilment, and logistics platform. Applications of AI and machine learning (ML) pervade this platform. For our customers, our adoption of AI and ML helps them shop faster with less friction and greater delight. We are able to personalize the experience to better fit their individual shopping styles. From our perspective as a retailer, we are able to predict the demand of the 50,000 different products we sell, detect fraud, and keep our customers safe, as well as manage the real-time control and health of the robot swarms and optimize the thousands of delivery routes that we drive each day.

Dr Duncan Russell is the Robotics Research Development Manager, overseeing the research into smart robotic and autonomous systems operations inside and outside the warehouse. Duncan has a varied career history of software, electronic systems and systems architecture in research and development, in both academia and commerce, with publications in grid computing, dependable systems, peer-to-peer information discovery and robotics for benchmarking real picking challenges. The range of experience is now applied to the highly complex environment of cyber physical systems that need to operate in the real world, and require intelligence to cope with all the variations it presents.