In this terms Strachey lecture, Professor Monika Henzinger gives an introduction to differential privacy with an emphasis on differential private algorithms that can handle changing input data. Decisions are increasingly automated using rules that were learnt from personal data. Thus, it is important to guarantee that the privacy of the data is protected during the learning process. To formalize the notion of an algorithm that protects the privacy of its data, differential privacy was introduced. It is a rigorous mathematical definition to analyze the privacy properties of an algorithm – or th ..read more

It’s said that Henry Ford’s customers wanted a “a faster horse”. If Henry Ford was selling us artificial intelligence today, what would the customer call for, “a smarter human”? That’s certainly the picture of machine intelligence we find in science fiction narratives, but the reality of what we’ve developed is far more mundane. Car engines produce prodigious power from petrol. Machine intelligences deliver decisions derived from data. In both cases the scale of consumption enables a speed of operation that is far beyond the capabilities of their natural counterparts. Unfettered energy consump ..read more

An introduction to algorithmic aspects of symmetry and similarity, ranging from the fundamental complexity theoretic "Graph Isomorphism Problem" to applications in optimisation and machine learning Symmetry is a fundamental concept in mathematics, science and engineering, and beyond. Understanding symmetries is often crucial for understanding structures. In computer science, we are mainly interested in the symmetries of combinatorial structures. Computing the symmetries of such a structure is essentially the same as deciding whether two structures are the same ("isomorphic"). Algorithmically ..read more

There has been a proliferation of technological developments in the last few years that are beginning to improve how we perceive, attend to, notice, analyse and remember events, people, data and other information. There has been a proliferation of technological developments in the last few years that are beginning to improve how we perceive, attend to, notice, analyse and remember events, people, data and other information. These include machine learning, computer vision, advanced user interfaces (e.g. augmented reality) and sensor technologies. A goal of being augmented with ever more computa ..read more

Mixed Signals: audio and wearable data analysis for health diagnostics Wearable and mobile devices are very good proxies for human behaviour. Yet, making the inference from the raw sensor data to individuals’ behaviour remains difficult. The list of challenges is very long: from collecting the right data and using the right sensor, respecting resource constraints, identifying the right analysis techniques, labelling the data, limiting privacy invasion, to dealing with heterogeneous data sources and adapting to changes in behaviour ..read more

The advantages of computing for society are tremendous. But while new technological developments emerge, we also witness a number disadvantages and unwanted side-effects. The advantages of computing for society are tremendous. But while new technological developments emerge, we also witness a number disadvantages and unwanted side-effects: from the speed with which fake news spreads to the formation of new echo-chambers and the enhancement of polarization in society. It is time to reflect upon the successes and failures of collective rationality, particularly as embodied in modern mechanisms f ..read more

As AI technologies enter our everyday lives at an ever increasing pace, there is a greater need for AI systems to work synergistically with humans. As AI technologies enter our everyday lives at an ever increasing pace, there is a greater need for AI systems to work synergistically with humans. This requires AI systems to exhibit behavior that is explainable to humans. Synthesizing such behavior requires AI systems to reason not only with their own models of the task at hand, but also about the mental models of the human collaborators. At a minimum, AI agents need approximations of human’s tas ..read more

Innovation is the main event of the modern age, the reason we experience both dramatic improvements in our living standards and unsettling changes in our society. Innovation is the main event of the modern age, the reason we experience both dramatic improvements in our living standards and unsettling changes in our society. Forget short-term symptoms like Donald Trump and Brexit, it is innovation itself that explains them and that will itself shape the 21st century for good and ill. Yet innovation remains a mysterious process, poorly understood by policy makers and businessmen, hard to summon ..read more

Medicine and Physiology in the Age of Dynamics: Newton Abraham Lecture 2020 Lecture by Professor Alan Garfinkel (2019-2020 Newton Abraham Visiting Professor, University of Oxford, Professor of Medicine (Cardiology) and Integrative Biology and Physiology, University of California, Los Angeles ..read more

Can we build on our understanding of supervised learning to define broader aspects of the intelligence phenomenon. Strachey Lecture delivered by Leslie Valiant. Supervised learning is a cognitive phenomenon that has proved amenable to mathematical definition and analysis, as well as to exploitation as a technology. The question we ask is whether one can build on our understanding of supervised learning to define broader aspects of the intelligence phenomenon. We regard reasoning as the major component that needs to be added. We suggest that the central challenge therefore is to unify the formu ..read more