The age of analytics
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The age of analytics



Presentation by Sir Mark Walport at the Operational Research Society on 30 April 2014.

Presentation by Sir Mark Walport at the Operational Research Society on 30 April 2014.




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The age of analytics The age of analytics Presentation Transcript

  • The Age of Analytics Operational Research Society, April 30th 2014 Sir Mark Walport Chief Scientific Adviser to HM Government
  • 2 WW2 origins of operational research: learning to think counter-intuitively • Add armour to the parts of bombers that come back damaged by flak, or the undamaged parts? • Better to protect the parts that stay undamaged. If the plane gets hit there, it never comes back for inspection. Credit: USAAF The Age of Analytics, April 30th 2014
  • 3 Patrick Blackett • Answers like this were developed by Patrick Blackett (1897-1974) and team. • Blackett was a key founder of the Operational Research Society in 1947. • His career nearly ended in 1925, when a young Robert Oppenheimer attempted to give him a poisoned apple. Copyright: Stephen Burch The Age of Analytics, April 30th 2014 View slide
  • 4 The opportunities presented by big data Credit: Shutterstock View slide
  • 5 What is big data? • Rule of thumb definition is a dataset that can’t be mapped on an Excel spreadsheet. • More technically, the four Vs: velocity, variety, volume and veracity, are the key characteristics of big data. The Age of Analytics, April 30th 2014
  • 6 Sources of data in a smart city Real-time Admin data Object sensors Pollution sensors People Social media Housing Health TaxesEducation Credit: NPR Credit: University of California Credit: AIA Credit: HM TreasuryCredit: Brian Rose Credit: KRoock74 (CC BY-SA 3.0) Credit: Editor5807 (PD) The Age of Analytics, April 30th 2014
  • 7 How a smart city can use data Optimising flows of people and resources Planning for future requirements Providing personalised services The Age of Analytics, April 30th 2014
  • 8 Data can help us get about Open data - Citymapper Crowdsourced data - Streetbump Driverless carsAnonymised crowdsourced data – Google Traffic Credit: Ultra Global PRT The Age of Analytics, April 30th 2014
  • 9 Data opens up a world of possibilities for our entertainment, education and efficiency Finding things out Telling other people things Listening and watching things Navigating the real world Navigating fictional worlds Buying and selling stuff Playing games Storing stuff Recording our lives and those of friends/families Socialising with others Stealing things Plotting and causing harm The Age of Analytics, April 30th 2014
  • 10 • Companies make it easier and cheaper for consumers to get the goods they want, in return for access to data about their spending habits. • That data can be used on an individual level, e.g. to target advertising, or to develop more sophisticated insights into how people shop. Private sector analytics: loyalty cards and Experian Credit: nectar The Age of Analytics, April 30th 2014
  • 11 How does government use data? Voting Taxes Planning Law enforcement Credit: ClassicStock Credit: Phlip Ingham/CC BY-ND 2.0 Credit: South Yorkshire Police Credit: Shutterstock The Age of Analytics, April 30th 2014
  • 12 Harnessing ICT: A national diabetes system for Scotland Total Scottish Population 5.2M People with diabetes : 251,132 (4.9%) People with Type 1 DM : ~27,000 (0.5%) All patients nationally are registered onto a single register; the SCI-DC register SCI-DC used in all 38 hospitals Nightly capture of data from all 1043 primary care practices across Scotland Courtesy of Andrew Morris The Age of Analytics, April 30th 2014
  • 13 PercentageofPatients Data recorded within the previous 15 months Courtesy of Andrew Morris Scottish Diabetes Survey – over 90% capture of key variables since 2007 Recording of Key Biomedical Markers The Age of Analytics, April 30th 2014
  • 14 Tax data to home in on fraud • HMRC uses sophisticated software to collect and analyse many sources of information about the finances of corporations and individuals, to identify cases that warrant investigation. • Connect, running since 2010, combines over 1 billion records and has yielded over £2bn in tax. The Age of Analytics, April 30th 2014
  • 15 National security The Age of Analytics, April 30th 2014
  • 16 What about privacy and security? Credit: Maksim Kabakou, Shutterstock
  • 17 Information technology has created new ways of locating or finding us The consequence of all of this is that we are giving a lot of information out that others can then use…. Image: iPhone tracking data The Age of Analytics, April 30th 2014
  • 18 Lots of other people are interested in our data. Who knows the most about us? Government Corporations ONS Google NHS Loyalty Cards HMRC Experian The Age of Analytics, April 30th 2014
  • 19 • Released anonymised film rental data and set a $1m prize, hoping to improve recommendation algorithms. • People’s viewing taste beyond usual blockbusters is highly individual. • Triangulating with IMDB data, bloggers identified individual users and were able to reveal their full list of rentals, not just those they had “rated”. Dangers of releasing data into the wild • Released anonymised search data for research purposes. • Journalists were able to pick up clues to name and location, then triangulate with embarrassing search queries. • Programme was halted, its initiators sacked. The Age of Analytics, April 30th 2014
  • 20 Privacy controls are not binary but fall on spectra Obfuscation Openly identifiable Anonymised to the point of losing valuable content Access / Environment Free on the internet Locked in a steel- lined room Governance and accountabilityLittle legislation Highly legislated (Everyone) (Accredited researcher) The Age of Analytics, April 30th 2014
  • 21 The myth of consent - do we really read and understand the full terms and conditions? • In 2008, researchers calculated it would take 76 working days to read all the privacy policies you encounter in a year. If everyone in the US did so, it would cost the country more than the GDP of Florida. • In 2010 - a UK- based games retailer - added a clause to their T&Cs, “to grant Us a non transferable option to claim, for now and for ever more, your immortal soul”. • A publicity stunt, but revealed 88% of customers in the time period had not read the T&Cs.Michael Pacher: St. Augustine and the Devil, 1471-75 Credit: Google Credit: PD The Age of Analytics, April 30th 2014
  • 22 Can we blame people? Source: Which, via Bobby Duffy IPSOS-MORI The Age of Analytics, April 30th 2014
  • 23 Social intelligence on personalisation vs. privacy • Personalisation vs. Privacy was a major IPSOS MORI international poll, 16,000 interviews, results released early 2014. • Up to 90% of people are concerned about how their (online) information is used. • People are more outraged by companies being cavalier with their data than they are by companies exploiting foreign workers, damaging the environment, overcharging for their products or paying huge bonuses. Credit: Maksim Kabakou, Shutterstock The Age of Analytics, April 30th 2014
  • 24 • Harm can be done by sharing and not sharing data • DPA law provides exemptions for research. The proposed EU Data Protection Regulation, which would replace the DPA, remains a concern. The Parliament’s draft text would make some current medical research illegal. • HMG and the UK academic community are united in lobbying for a final text that does not overly restrict important research. Governance: data protection legislation Credit: EU dpi The Age of Analytics, April 30th 2014
  • 25 • In the USA, preventable medical errors are the third leading cause of death (440,000 per year – Journal of Patient Safety, 2013). Data analytics can identify and address the underlying causes. • Countries all around the world are currently wrestling with the same issue of how to share medical data while protecting privacy. • We need to be more open with people on how their data may and may not be used, and communicate the benefits. On… “This information helps us identify the causes of cancer and heart disease; it helps us to spot side-effects from beneficial treatments, and switch patients to the safest drugs; it helps us spot failing hospitals, or rubbish surgeons; and it helps us spot the areas of greatest need in the NHS. Numbers in medicine are not an abstract academic game: they are made of flesh and blood, and they show us how to prevent unnecessary pain, suffering and death.” Ben Goldacre, Guardian 21 February The challenge of communicating the benefits: The Age of Analytics, April 30th 2014
  • 26 How do we build capability? Credit: Frank A. Camaratta, Jr, The House of Staunton, Inc
  • 27 Skills pipeline Source: DfE -600 -500 -400 -300 -200 -100 0 100 200 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10 2010/11 2011/12 2012/13 Mathematics teacher recruitment shortfall/surplus The Age of Analytics, April 30th 2014
  • 28 The Turing Institute The Mission 1. To undertake research and knowledge sharing in the key disciplines of mathematics, computer and data science 2. To develop networks between leaders 3. To enable industry and academia to work together on research with practical applications 4. To provide advice to policy makers on the wider implications of research 5. To provide strategic oversight and leadership The vision 1. Promote the development and use of advanced mathematics, computer science and algorithms for human benefit 2. Conduct first class research and development 3. It will be a world leading institute that will provide a fitting memorial to Alan Turing Credit: Duane Wessels (CC-BY-NC-SA-2.0) The Age of Analytics, April 30th 2014
  • 29 We need to ensure analysts have space within their jobs to innovate Operation • The day job. • Doing the same thing repeatedly, with minimal failure. • Change is risky. • Success is easy to measure. • Return is immediate. Innovation • Few people do this only. • Finding better ways to do things. • Failures and false starts are to be expected. • Fuzzy, conflicting goals. • Hard to measure. • Return comes in the future. The Age of Analytics, April 30th 2014
  • 30 Enabling legislation • An open consultation on data sharing, led by Francis Maude. • Aiming for an agreed approach between parties and involving privacy groups, for a White Paper at the end of the year. • Laying the ground for a Data Sharing Bill after the 2015 election. Credit: Cabinet Office The Age of Analytics, April 30th 2014
  • 31 What is needed from the OR Society? • Research to stay at the cutting edge. • Augment analytical skills with coding skills. • Plug into the world of big data: volume, velocity, variety and veracity. Credit: Petr Ivanov, Fotolia The Age of Analytics, April 30th 2014
  • 32 We all need to work together Universities Industry Credit: Alamy Credit: Red Spider UK The Age of Analytics, April 30th 2014
  • 33 There is no going back – the world has been shaped by the digital revolution There are new tools for understanding ourselves and the world Huge opportunities for the data science and operational research profession, to be right at the centre of policymaking There are unforeseen benefits and harms: need a sophisticated level of debate Final messages
  • Every effort has been made to trace copyright holders and to obtain their permission for the use of copyright material. We apologise for any errors or omissions in the included attributions and would be grateful if notified of any corrections that should be incorporated in future versions of this slide set. We can be contacted through @uksciencechief