Daniel Russel - Google

Augmenting learning with smart design, smart systems, and intelligence

We all want better educational systems, no matter what the implementation might be. We tend to think of building ever more capable AI systems as the way to do this, but what is AI? It’s rapidly becoming fancy software engineering: the definition continues to shift over time. What CAN we do in education to help students? My answer: Provide great, well-designed content; put it in a framework where others can use it; wrap it within a social system that lets students learn effectively, no matter the place or time; teach students how to learn. From my perspective, we have already built enormously effective information providing systems, but teaching students how to teach themselves remains key.

Daniel Russell is Google’s Senior Research Scientist for Search Quality and User Happiness in Mountain View.  He earned his PhD in computer science, specializing in Artificial Intelligence.  These days he realizes that amplifying human intelligence is his real passion.  His day job is understanding how people search for information, and the ways they come to learn about the world through Google.  Dan’s current research is to understand how human intelligence and artificial intelligence can work together to better than either as a solo intelligence.  His 20% job is teaching the world to search more effectively.  His MOOC,, is currently hosting over 3,000 learners / week in the course. In the past 3 years, 4.5 million students have attended his online search classes, augmenting their intelligence with AI.  His instructional YouTube videos have a cumulative runtime of over 350 years (24 hours/day; 7 days/week; 365 weeks/year).  His new book, The Joy of Search, tells intriguing stories of how to be an effective searcher by going from a curious question to a reliable answer, showing how to do online research with skill and accuracy.  (MIT Press) 

Judy Kay - University of Sydney

Scrutability, control and learner models: foundations for learner-centred design in AIED

There is a huge, and growing, amount of personal data that has the potential to help people learn. There is also a growing and broad concern about the ways that personal data is harvested and used. This makes it timely to draw on the decades of the AIED research towards creating systems and interfaces that enable learners to truly harness and control their learning data. This invited keynote will present a whirlwind tour of my learner modelling research and a selection of other work that has influenced my own towards the goal of putting people in control of their own learning data and its use. I will explain the rationale for my focus on scrutability, as a foundation for users to harness and control their learning data, especially for learning contexts.

I will share key lessons from my work for creating AIED systems that are deeply learner centred. Building on this, I will present a vision for AIED, one that takes a learner-centred perspective to designing AIED systems and recognises the inherent limitations of learning data. This is a broad view of AIED that returns its founding goals to create advanced learning technologies.

Judy Kay is Professor of Computer Science in the Faculty of Engineering, University of Sydney. She heads the Human Centred Technology Research Cluster, a large multi-disciplinary research group that conducts fun- damental research, design, engineering and evaluation of new technologies. She is a Payne-Scott Distinguished Professor at the University of Sydney, in recognition of her contributions to both multi-disciplinary, high-impact and deployed research and to education. A core focus of her research has been to create in- frastructures and interfaces for personalisation, especially to support people in lifelong, life-wide learning. This ranges from formal education settings to sup- porting people in using their long-term ubicomp data to support self-monitoring, reflection and planning. Central to this has been in the design of the Personis user modelling systems and interfaces that enable people to control their own long-term personal information from diverse sensors on devices be they worn, carried, embedded in the environment or conventional desktops. She has integrated this into new forms of interaction including virtual reality, surface computing, wearables and ambient displays. Her research has been commercialised and deployed and she has extensive publications in leading venues for research in user modelling, AIED, human computer interaction and ubicomp. She has had leadership roles in top conferences in these areas and is Editor-in-Chief of the IJAIED, International Journal of Artificial Intelligence in Education (IJAIED) and Editor of IMWUT, Interactive Mobile Wearable and Ubiquitous Technology (IMWUT).