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Conference Details - Agenda

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2018 Systems that Learn Conference in London

February 27, 2018


Coffee, Registration, & Networking


Welcome & Introduction


Human-Artificial Intelligence Partnerships
In our increasingly connected world, computation is everywhere and we are generating ever more data about everything. These trends will profoundly change the ways in which we work with computers. Specifically, we need the machines to be smarter and more helpful. Central to this vision is the means by which we can forge effective partnerships with such artificial intelligence (AI) systems. Until now, humans have generally been the masters and technology the slave. This needs to change. Today’s AI systems can act on high-level human commands and achieve complex goals in a flexible manner. But, while such systems are good at solving narrowly defined tasks, they don’t know how to collaborate with humans or how to operate as part of a problem-solving team. This talk will explore how humans and AI systems can work together. In such partnerships, the humans and the AI systems complement each other’s strengths and weaknesses, leading to a rise in the humans, as well as in the machines. Drawing on multi-disciplinary work in the areas of AI, autonomous systems, machine learning, crowd sourcing and ubiquitous computing, this talk explores the scientific underpinning of such systems, the applications they have been applied to, and the societal implications of their widespread adoption.
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Computer Systems Arms Races
High stakes arms races abound in computer and cyber systems. As we take ML-based security measures to counter malware, network attacks, intrusion or reconnaissance, the perpetrators develop and exploit unanticipated variations that get the better of them. My research agenda is to approach this problem by using machine learning techniques. My ultimate goal is more robust measures supported by an understanding of arms race dynamics. I will discuss my group's work on DDOS attacks on resilient peer to peer networks, deception vs insider reconnaissance, malware detector vs malware evasion and macro-scale network security conflict modeling.
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Industry Keynote: Creating Value for BT's Customers with AI
BT has always been committed to employing the latest technologies to deliver empower its customers and its people, and partners globally to bring that technology to life. For many years we have used mature AI techniques to underpin our services and operations but emerging technologies are presenting dramatic new possibilities. In this talk I'll outline some of the challenges and opportunities we face, discuss our latest research and outline the key future challenges and opportunities that BT is excited to explore with our partners.


Networking Break


Startup Lightning Talks
John Andrews, CEO at Celect
Arlene Ducao, CEO at Multimer
Tor Jakob Ramsoy, CEO at Arundo Analytics
Eduard Vazquez, Head of Research, Cortexica Vision Systems
Henry Oakes, Co-Founder, TRACK
Francesco Montomoli, Senior Lecturer, UQuant
Maya Pindeus, CEO, Humanising Autonomy


Lunch with Interactive Startup Exhibition


The Human Strategy
Our future will have big data, AIs, and cyberwarfare, so how can we build a world that still has a human feel to it and is a comfortable place to live? The fact that everything is becoming “datafied” together with the emergence of new, more powerful machine learning techniques means that we can now build human-AI ecologies in ways we could never do before. I will describe how we are beginning to use these new tools to design a better framework for human and AI to work together, and how we are beginning to test this framework at scale on four continent with the support of major countries, multilateral agencies, and multinational corporations.
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The Atlas of Behaviour
Our aim is to gain a data-driven understanding of human behaviour and develop human-in-the loop machine learning that helps people in health and disease. Our work is applied to Human Neurotechnology and combines cross-disciplinary machine learning and robotics approaches together with neuroscience to reverse engineer the human perception-action loop in health and disease. To this end my lab is pursuing four research strands:
1. build an Atlas of Behaviour using wearable sensors to capture as much human perceptual input and motor output as possible in daily life (wearable technology)
2. understand human behaviour to predict intention and computational human neuroscience
3. engineer human-robot interfaces that restore motor function in the paralysed (human augmentation)
4. translate our algorithms and devices in application with end-users, such as Muscular Dystrophy, Stroke, Multiple Sclerosis and Spinal Cord Injury survivors with the intention to take our research all the way from algorithm to the bedside (translational engineering)
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Industry Keynote: How AI Can Bring Us Closer to Our Customers
The way people bank has changed but the need to manage their money now and in the future hasn’t. Artificial intelligence has many different uses and in financial services the opportunities are significant, not only for operational improvements, but also to create personal and relevant experiences which help customers make better financial decisions.


Adjournment with Networking Reception