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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
4
The opportunities presented by
big data
Credit: Shutterstock
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
http://www.diabetesinscotland.org.uk/Publications/SDS%202010.pdf
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 GameStation.com - 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 care.data…
“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: care.data
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 go-science@bis.gsi.gov.uk.
@uksciencechief
www.gov.uk/go-science

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The age of analytics

  • 1. The Age of Analytics Operational Research Society, April 30th 2014 Sir Mark Walport Chief Scientific Adviser to HM Government
  • 2. 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. 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
  • 4. 4 The opportunities presented by big data Credit: Shutterstock
  • 5. 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. 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. 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. 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. 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. 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. 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. 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. 13 PercentageofPatients Data recorded within the previous 15 months http://www.diabetesinscotland.org.uk/Publications/SDS%202010.pdf 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. 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. 15 National security The Age of Analytics, April 30th 2014
  • 16. 16 What about privacy and security? Credit: Maksim Kabakou, Shutterstock
  • 17. 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. 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. 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. 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. 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 GameStation.com - 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. 22 Can we blame people? Source: Which, via Bobby Duffy IPSOS-MORI The Age of Analytics, April 30th 2014
  • 23. 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. 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. 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 care.data… “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: care.data The Age of Analytics, April 30th 2014
  • 26. 26 How do we build capability? Credit: Frank A. Camaratta, Jr, The House of Staunton, Inc
  • 27. 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. 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. 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. 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. 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. 32 We all need to work together Universities Industry Credit: Alamy Credit: Red Spider UK The Age of Analytics, April 30th 2014
  • 33. 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
  • 34. 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 go-science@bis.gsi.gov.uk. @uksciencechief www.gov.uk/go-science