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Turing Lecture: Stats, Decision Making and Privacy
Mon 5 December 2016, 13:30 – 17:00 GMT
NOTE: Registration for the event is compulsory; please book to ensure a space. This event will be livestreamed. Prior registration is required and livestreaming details will be sent to all registered livestream attendees shortly before the event. Recordings will also be made available on YouTube after the event.
In this Turing Lecture, the UK’s National Statistician, John Pullinger, will explain how data is helping us make better decisions about out futures, and presents some important questions about data ethics and security. Following on from this, Microsoft Research's Cynthia Dwork will discuss the challenges of privacy and how we can combat them.
Speaker 1: John Pullinger, UK National Statstician
Mobilising the power of data to help Britain make better decisions
‘Good’ data about the state of our economy and society, helps governments, businesses and citizens, to make informed decisions for the future. Demands to generate this data faster, in more detailed and tailored forms are growing, whilst the data revolution is providing rich opportunities for the data science community to come together to identify novel solutions to these demands. It also raises important questions about data ethics, data security and data quality, amongst other concerns. In this talk, John Pullinger will explore the nature of these questions, current responses to them, and the potential for building relationships between The Alan Turing Institute, the Office for National Statistics, the Government Statistical Service, and others who share an interest in developing insights from data to benefit the public.
John Pullinger is the UK National Statistician and most recent Chair of the United Nations Statistical Commission. He has previously been President of the Royal Statistical Society and Chair of the Getstats campaign for statistical literacy. He has worked in statistical, research, policy and leadership roles in the UK government at the Department of Trade and Industry, Department of Environment, and Office of Manpower Economics, as well as the UK Statistics Authority. He also spent ten years leading information services at the UK House of Commons as Librarian of the House, and developing new services to enable the public to engage with Parliament.
Speaker 2: Doctor Cynthia Dwork, Microsoft Research
Privacy-Preserving Data Analysis
Privacy-preserving data analysis has a long history, spanning at least five decades and numerous disciplines. Despite this extensive history, it is only in the last decade that an understanding has formed of the risk that the accumulation of small, seemingly insignificant statistical hints about confidential data, can pose to privacy. In this talk, Cynthia Dwork will discuss the implications of the loss of these ‘breadcrumbs’ of data, and show how differential privacy, a notion of privacy tailored to statistical analysis of large datasets, can control this risk, while at the same time permitting complex data analysis.
Cynthia Dwork, Distinguished Scientist at Microsoft Research, is renowned for placing privacy-preserving data analysis on a mathematically rigorous foundation. A cornerstone of this work is differential privacy, a strong privacy guarantee, frequently permitting highly accurate data analysis. Dr. Dwork has also made seminal contributions in cryptography and distributed computing, and is a recipient of the Edsger W. Dijkstra Prize, recognizing some of her earliest work establishing the pillars on which every fault-tolerant system has been built for decades. She is a member of the US National Academy of Sciences, the US National Academy of Engineering, and the American Philosophical Society, and a Fellow of the American Academy of Arts and Sciences.
Dwork will join Harvard in January, 2017, as the Gordon McKay Professor of Computer Science at the Paulson School of Engineering and Applied Sciences, Radcliffe Alumnae Professor at the Radcliffe Institute for Advanced Study, and an Affiliated Faculty Member at Harvard Law School.