The Age of Analytics
Operational Research Society, April 30th 2014
Sir Mark Walport
Chief Scientific Adviser to HM Government
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.
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
The opportunities presented by
big data
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
Sources of data in a smart city
Real-time
Object
sensors
Pollution
sensors
People
Social
media
Housing
Health
Education
Taxes
Admin
data
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The Age of Analytics, April 30th 2014
How a smart city can use data
Optimising flows
of people and
resources
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The Age of Analytics, April 30th 2014
Providing
personalised
services
Planning for
future
requirements
Data can help us get about
Open data - Citymapper
Anonymised crowdsourced data – Google Traffic
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The Age of Analytics, April 30th 2014
Crowdsourced data - Streetbump
Driverless cars
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
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The Age of Analytics, April 30th 2014
Private sector analytics: loyalty cards and
Experian
• 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.
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The Age of Analytics, April 30th 2014
How does government use data?
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Voting
Planning
Taxes
Law enforcement
The Age of Analytics, April 30th 2014
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
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The Age of Analytics, April 30th 2014
Scottish Diabetes Survey – over 90%
capture of key variables since 2007
Recording of Key Biomedical Markers
Percentage of Patients
Data recorded within the previous 15 months
Courtesy of Andrew Morris
http://www.diabetesinscotland.org.uk/Publications/SDS%202010.pdf
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
National security
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The Age of Analytics, April 30th 2014
What about privacy and security?
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The Age of Analytics, April 30th 2014
Information technology has created new ways
of locating or finding us
Image: iPhone tracking data
The consequence of all of this is that we are giving a lot
of information out that others can then use….
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The Age of Analytics, April 30th 2014
Lots of other people are interested in our data.
Who knows the most about us?
Government
Corporations
ONS
Google
HMRC
Experian
NHS
Loyalty Cards
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
• 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”.
Privacy controls are not binary but fall
on spectra
Openly identifiable
Free on the
internet
Obfuscation
Access / Environment
(Everyone)
Little legislation
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Anonymised to the
point of losing
valuable content
Locked in a steellined room
(Accredited researcher)
Governance and
accountability
The Age of Analytics, April 30th 2014
Highly legislated
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 UKbased 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”.
Michael Pacher: St. Augustine and the Devil, 1471-75
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The Age of Analytics, April 30th 2014
• A publicity stunt, but revealed 88% of
customers in the time period had not
read the T&Cs.
Can we blame people?
Source: Which, via Bobby Duffy IPSOS-MORI
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
Governance: data protection legislation
• 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.
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The Age of Analytics, April 30th 2014
The challenge of communicating the
benefits: care.data
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
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The Age of Analytics, April 30th 2014
• 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.
How do we build capability?
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The Age of Analytics, April 30th 2014
Skills pipeline
Mathematics teacher recruitment shortfall/surplus
200
100
0
-100
-200
-300
-400
-500
-600
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
Source: DfE
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The Age of Analytics, April 30th 2014
The Turing Institute
The Mission
The vision
1.
2.
3.
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Promote the development
and use of advanced
mathematics, computer science
and algorithms for human benefit
Conduct first class research and
development
It will be a world leading
institute that will provide a fitting
memorial to Alan Turing
The Age of Analytics, April 30th 2014
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
We need to ensure analysts have space
within their jobs to innovate
Operation
• The day job.
• Few people do this only.
• Doing the same thing
repeatedly, with minimal
failure.
• Finding better ways to do
things.
• Change is risky.
• Success is easy to
measure.
• Return is immediate.
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Innovation
The Age of Analytics, April 30th 2014
• Failures and false starts
are to be expected.
• Fuzzy, conflicting goals.
• Hard to measure.
• Return comes in the future.
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.
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The Age of Analytics, April 30th 2014
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.
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The Age of Analytics, April 30th 2014
We all need to work together
Universities
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The Age of Analytics, April 30th 2014
Industry
Final messages
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
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The Age of Analytics, April 30th 2014