Personal Data and Trust Network inaugural Event 11 march 2015 - record

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Inaugural Event
Digital Catapult Centre, 101 Euston Road, London, 11 March 2015

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Executive summary Slide 3
What happened Slides 4-13
What was discussed / produced Slides 14-29
Annex: presentations and notes Slides 30-122

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Executive summary
Around 100 experts in the field of personal
data, privacy and trust met at the Digital
Catapult Centre to
• Learn about the purpose and aims of the
network
• Hear perspectives from industry on the key
issues
• Hear examples of the world-leading research in
this topic that has been conducted in the UK
over the last few years
• Identify the most important priorities for the
network …
• … and make a start on determining how the
network would address them
Priorities identified were:
• How can we share best practice?
• What are the implications of digital social
innovation?
• How should we deal with (EU) regulation?
• How can consent in pervasive environments
best be managed?
• Who owns the rights to use personal data?
Groups worked to begin to answer these questions:
their work is presented in this document
There was great energy in the room from
participants representing many different types of
organisation, and a clear commitment to work
together
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What happened Slides 4-13
Read the slide headings to get an overview in 30 seconds

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Andy and Matt welcomed delegates
Andy Green briefly explained the role of the Catapult and the
centres around the UK (Sunderland, Bradford and Brighton),
and stressed the significance of the personal data and trust
issue
He said there was an opportunity for network members to
gain insight from each other and contribute to greater
understanding
Matt Stroud explained the genesis of the network, and its role
in helping to unlock value for multiple parties from personal
data
He explained how the network drew together members with
multiple perspectives on the issues
5
What we need is for the
innovators in the room to
come together and
contribute new ways to
think about the issues
There are practical
issues here – but
also ethical issues
See slides 31-37 for more detail

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Jon introduced Alex Craven who presented professional
and personal perspectives on personal data and trust
Jon Kingsbury ran through the agenda, and pointed out that the
room contained representative of a world-class research base,
businesses (innovative, data-focused SMEs and larger companies
for whom the issue was becoming more important, and professional
services companies working in this area), policy makers, public-
sector organisations and trade associations in multiple sectors
Alex Craven spoke about how ad agencies increasingly make use of
personal data in their work, and about the potential for measurable
public good in its use.
He spoke about how he believed that there could be a way to give
individuals proper control over the use of their data. His idea is
called “Our Data Mutual”
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Privacy is dead …
we must move on

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Rav spoke about his work with banks, and the
approach taken by corporations to data and trust …
Rav spoke about “conduct risk” and compliance
with regulations – including the impact this is
having on systems and processes
He said the issues faced were similar in other
big companies with huge volumes of data, and
said they are pretty good at managing data
He said that big financial services companies
and their consultants don’t have all the bright
ideas, and that he hoped the network would help
build consensus and also a critical mass of
thinking
7
I’m not sure how the market is
turning – it’s like a kids’ football
match … we are all chasing
the ball wherever it goes

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… and Jon led a discussion of the main issues arising
from these presentations
Questions and discussion points range
across many topics:
• Personalised online advertising and mashups
of multiple data sets
• Trust frameworks
• Making sense of ‘big data’
• Examples of the use of personal data for good
• Language used within the network
• Privacy and EU regulations
• Who owns ‘personal’ data?
• The special case of health data in specific
contexts
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After a networking lunch, delegates heard about funding
opportunities from Innovate UK competitions …
Jon explained that much public funding was based
around collaboration; he promoted the KTN’s Digital
Business Briefing, and three colleagues spoke briefly
about their competition-based funding programmes:
• Jonny Voon – Protecting data in industry looking at
digital disruption (cyber attacks) – opening 31
March (GBP4 million)
• Tom Fiddian – Enhancing user experience using
personal data opens 16 March; a feasibility design
study (GBP2M)
• Agata Samojlowicz – Enhancing user experience in
retail (up to GBP4M two-stage collaborative R&D)
opens 16 March
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… and heard three presentations on personal
data research
Jerome Ma explained the purpose of the
Research Council’s Digital Economy theme, and
introduced thee speakers from the digital
economy research hubs:
• Derek McAuley (Horizon Digital Economy
Research Institute)
• Paul Watson (SiDE Hub)
• Pete Edwards (dot.rural Digital Economy
Hub)
They gave thought-provoking details of some of
the personal data and trust issues of their
research work
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I can tell if you
didn’t have a
shower this
morning
Sometimes giving people more
control over the use of their data
might increase their personal risk
Rural bus service
planning might result in
individuals being traced

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Groups then thought about how they might work together
on specific priority issues …
The initial five priority areas identified were:
1. Sharing best practice
2. Digital social innovation
3. Dealing with (EU) regulation
4. Consent in pervasive environments
5. Who owns the rights to use the data
Groups note down key points from their
discussions
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… and briefly fed back their discussions to
all delegates
Sharing best practice
• Objective models of risk; voluntary certification
Digital social innovation
• There is a “pyramid of trust”
Dealing with (EU) regulation
• Let’s make use of it – there are good bits
Consent in pervasive environments
• It’s not informed, and it’s not consent
Who owns the rights to use the data
• It’s complicated!
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Matt explained possible next steps for the network
and thanked participants for their work
Jon said he felt the day had generated some very
interesting debate. He said there were two ways to
take this conversation forward:
• The website
• Sharing personal contact details (delegates would be
emailed to ask if they were happy to share their details)
Jon said he had realised there was a very large
cohort of people that really understand the issues
and the technicalities of the issues
Matt closed by saying where the network might go
from here. He said there were several things that
might happen:
• Future regular meetings – quarterly? And thematic
meetings – around the country; may use the National
Virtual Incubator (teleconferencing facility); he asked if
anyone might like to host a meeting
• Digital presence (website, a quarterly digital journal)
• Community interest groups – vertical or horizontal, e.g.,
a privacy working group (or security or psychology) –
who might want to lead or get involved?, and a PIMS
provider forum
• Grow the membership base – writing papers and
working with the media, as well as spreading the word
within relevant organisations
• Other? Suggestions please
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What was discussed / produced Slides 14-29

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Notes from the morning plenary Q&A session [1]
Q: Advertising and big data – where is the cutting edge of personal data use?
A: [Alex] It’s personalised advertising online (e.g., mashing online activity data with datasets from Experian for instance).
This sort of thing is diverting advertising revenue from traditional channels
Q: What about IoT? We are all becoming generators of our own data – is this a service provider data gold rush? And what
are the killer apps?
A: It should be a gold rush – but the trust framework needs to be in place first
Q: Fintech Innovation Lab – how many innovations are coming here that are geared around mining personal data?
A: [Rav] I haven’t seen many … but … personal data has always been there – what’s changed is the way the data can be
captured, and quantified. But there’s too much, it’s fractured and siloed. This creates opportunities for arbitrage between
data silos, for the consumer and for organisations. The big game-changer is when companies work out how to use this
data in different ways to create and sell products. One of the biggest issues we have is the capture of social media data;
social media is highly qualitative and you need to interpret it to use it. We need to have a discussion about trust that looks
at this. The next killer apps will be those that make sense of qualitative data (literally “making sense of it”, and making use
of the data – e.g., predictive analytics, statistics)
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Q: We run digital service for academics; Alex’s examples are a good example of why consent doesn’t work (installing
cookies … mortgage applications – of course stop sending me information on mortgages when I already have one!) – so
there are some things that should be “never do”; some that are “of course do it”; and some that are in the middle. I have
no problem with finding this in proposed or current European legislation – so what we need to do is identify what things fit
into which category – I like the idea of a “mutual” doing this
Response: Do you think there are organisations or services that get it right?
A: Learning analytics (e.g., can a university improve its education to students by identifying students it could help in a
different way?; or providing federated access management – a service provider doesn’t need to know all the details of a
student to grant access to specific applications in specific ways
Q: I campaign in this area. An appeal: be precise about language. The EU legislation is data protection not privacy
legislation. I am concerned about the way we are talking about privacy – it is a fundamental human right and needs to be
respected. In trying to frame how people can come to trust institutions and companies, a balance of consensual, safe and
transparent things must be arrived at – this varies by context. But all three must be addressed – for control and
understanding what that control actually is. Many of us here are tackling very difficult but not intractable problems. To find
mutual benefit we must recognised that this is inherently wrapped up with “privacy” – though definitions of privacy are
subjective and can’t be easily predicted
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Q: You say EU frameworks won’t work – what does this mean? I think it will (EU Directive 95 etc).
A [Alex]: Doing this top down is fundamentally wrong – we need data protection and you can’t have trust if it’s mandated
from the top down; if it’s my data, then I want to say how it’s used. The EU should not say how it can be used. The
principle is wrong and there should be no one-size-fits-all European decision. But there is no alternative being put up
against the EU way
Comment: There is a publication “The Lord of The Things” – when data is “ours”, are we just “stakeholders” in our data?
Q [“Patients Like Me”]: We should think about things at a community level – you can see some really interesting things on
sharing personal data in the health sector. Patients Like Me is one of many similar groups / communities online doing the
“quantified self” – sleep patterns, blood pressure etc …increasingly YouTube channels are created as well “like
embarrassing bodies”! Very useful and informative
A: Lowering the cost and inertia of signing up to things like this is important
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Q: Thinking about the Tesco diabetes thing – what is the appetite from banks etc for sharing of data for social good?
A [Rav]: They know about life events. Typically, if you are going to divorce, the party you are divorcing changes spending
patterns a year before it happens. Financial services organisations, if they choose to, can know more about you than
Tesco because they can match more types of data – and they can link family bank accounts etc; Tesco doesn’t do this.
Banks also have many years’ of data (they have to keep it for legal reasons). They can profile customers to a frightening
degree. Most financial services organisations choose not to do this because their customers don’t want them to. There are
strict guidelines about this … but they could do an awful lot more than they do. For the social good of mining this data –
leveraging a small amount of my data – I don’t think it would be a problem, but it must be driven by the customer, banks
can’t do I themselves
Q: I don’t believe there’s no need for regulation – it’s essential. In Europe we have two fundamental rights – privacy and
data protection – you can’t get away from this. But we are thinking only of personal data here. I live in a multi connected
world: there are types of data all over the place that might impact on my privacy – it’s not enough to think about personal
data alone. So how do we deal with privacy in a context-based way? We need to find a way to help people protect their
privacy. There has been work on “meaningful consent” at Southampton University and elsewhere – how do we get the
work out of the lab into peoples’ hands?
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Point: I have an app that can track my emotional state using my phone. I can’t see a way beyond individuals being
responsible for their own data and privacy – I don’t trust any privacy network – people click to give consent, but they don’t
know where the data goes – they must know this
Point [Patient Opinion]: The language at today’s meeting has been all consumerist. We are treating trust as a black box,
but it varies a lot (there’s a difference between what trust means as a patient and as a consumer) – having a Mercedes is
different to having a heart attack. When you want something for yourself, that’s one thing; wanting something for the public
good is different – can the network address this aspect, and keep the distinction clear? There’s a danger of skewing
everything to the consumer angle.
A: Yes – it’s your network – we can do this if we want to – there is a whole range of interests represented in the room
included medical
Point: I manage Warwick University’s Hub of All Things – we address some of the issues that have emerged: our project
recognises the need for people to own their own personal data and manage its availability in different contexts, where the
value can be understood (e.g., retailers, healthcare, wholesale etc – to get different types of value). We are creating a tool
– we recognise the opportunities and challenges and we are looking to have 1000s of people collecting their data into a
repository
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Q: Loughborough University – speaking as consumer: do we need to be careful in assuming that trust is always good?
Alex’s point about mortgages hit home – anything that improves the process is good. I had to go online, search products,
do some sums, sit with an advisor, and I came out with different, better product. There are benefits of engaging fully like
this – if we trust automated solutions, we might cut out benefits of traditional personal interactions. Do we need a series of
nuanced approaches to trust / scepticism?
A [Alex]: What you describe is horrible – I don’t have time to do what you did. I want to do it quicker online. In my work I
want to do it my way; you can do it your way. There is an opportunity to do something in between too – and turn your trust
up or down
A [Rav]: We are on a journey here – it’s not going to change overnight – and it’s a generational thing
Q: Let’s get the data owner back in the picture. There are billions of data creators facing a handful of big brands. Normally
when you own something, you can sell it for money. How can the individual get a share of the value of their data?
A: Yes – the Data Mutual can only be funded that way – like a Tesco Clubcard
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A [Rav]: But what is the currency? Not everything is monetisable. Data is everything to do with you: it’s not just you, it’s the
wider context – so where does the value get created? It’s not just because of your data, it’s because of the context of that
data (that you don’t own)
Point [Governor Technology (Richard Beaumont)]: We have learned how nuanced the decisions are that websites make
when using personal data. Consent and control plays a lot in trust (as does accountability) – it all needs being lined up to
give strong trust and a strong economy, especially if you want it to be fair
A [Rav]: One of the network’s fundamental challenge is about data literacy: generations are coming through that aren’t
aware of what is data, privacy and trust. So let’s go to the grass roots – e.g., cookie caches – there is a whole subset of
society that is completely data-unaware. If we can address this, that would be a big step forward, I suggest
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Group 1: Sharing best practice
• Best practice must be user-centric – user control; instead of
common standards, it can involve certification and
verification
• Best practice looks at objective models of risk; risk is very
hard to quantify for individuals, and for people doing risk
assessment, but there are commonalities across
organisations
• Common risk models could be identified, with common
mitigations – this can be a good way of sharing best
practice
• Along with this we propose voluntary certification
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Group 2: Digital social innovation [1]
• What are the principles you need to operate by to
generate trust? Here’s out trust pyramid: we are
trying to get to being trustworthy (not trusted)
• The building blocks are user empowerment in the
process: transparency, and accountability or
power to remove data – this is a remedy
• There are operational principles that companies
must adhere to: ‘security by design’, ‘privacy by
default’, and other things: open business model
(be clear about how money is going to be made)
and data minimisation (important in the big data
era) …
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Group 2: Digital social innovation [2]
• … we know we can’t keep data secure, so we must work to minimise the data that we keep; and be
clear that there is no covert tracking or profiling going on
• The most interesting discussions we had on our trust pyramid were those to do with “remedy” – is
removal of data really empowering? And ultimately how ‘validatable’ is all this?
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Group 3: Dealing with (EU) regulation
• The bad stuff in the regulations will hit us anyway, so
how do we make the best of the good stuff?
• Two things are “privacy by design” and “privacy
impact assessments” – they could be positive tools to
encourage people to trust us. We could present these
in citizen-friendly ways
• Also, if you think that consent doesn’t fit your
application, there are five other things allowed
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Group 4: Consent in pervasive environments [1]
• Informed consent problems: it’s not informed; and it’s not consent
• The consumer doesn’t know what’s going on or understand risk,
costs or benefits of giving consent
• What we should do is “surprise minimization” – nothing that
happens should surprise the consumer
• You can’t consent if you don’t understand, so you must “empower”
users. It’s a dynamic process. People are willing to be fluid in data
exchange if feedback exists – something needs to support this
dynamic process, such as trust agents
• The main thing is to enable a “supported user” – with
visualisations
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Group 4: Consent in pervasive environments [2]
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Group 5: Who owns the rights to use the data [1]
• You own the rights to your data (enshrined by Magna Carta). The
individual is a creator of data, so the individual should own it
• But data must be interpreted in some cases – e.g., by a doctor.
Sometimes you might not trust your GP, and you want access to your
own data not mediated by the GP
• Data is linked to community groups – data is collected within a
context. Using the data is not like consuming it; you need to protect
the access rights – and enforce this
• You must work out how enforcement can be managed – it’s complex.
Content protection? Authorities need rules, and the issues extends to
secondary and tertiary use of data – it’s easy to lose control. How can
you constrain the inheritance of the data and access rights across
multiple users? This could be controlled and enforced through
technology and enshrined in law
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Group 5: Who owns the rights to use the data [2]
• You might want “authorised witness” – a notary –
certifying the data as yours. In the medical domain it’s
often a committee that certifies who can do what.
• There are differences of opinion about this, though – the
goals of research are evolving
• There is some more complexity – co-ownership of some
data. For example, consider a delivery driver who might
have stayed for hours at a pub. His car belongs to a fleet.
It might be a Ford (Ford might have rights). The payload
owner has rights / interests in what’s happening to the car
too
• We talked about taxonomy and ontology and instantiation
(because we are computer scientists)
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Annex: Notes from presentations,
slides presented, and plenary discussions Slides 30-122

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Notes from Andy Green’s opening talk
Andy Green stressed the significance of the personal data and trust issue – along with security, he said these were the two most
important issues facing the development of the digital economy
He said there was a spectrum of opinion on the issue of personal data and privacy – but the consensus is that only one or two bad
events would change the balance
He said the biggest brands understand the significance of dealing properly with private data – they are extraordinarily careful with this
data – it’s not a legal issue, it’s a consumer moral boundary issue. It’s complex issue, and there has been work on codes of practice –
but what we need is for the innovators in the room to come together and contribute new ideas and new ways to think about the issue.
The other side of the issue is about value - I get great value from people knowing about me; but I can see the importance of
protection too
Andy added that for the long term, the issue will lead to a big evolution of the Internet – we will have to rethink rights management. It’s
not easy – but we need to think about it… and work out some policies for it all
He concluded by saying that this network is a collaborative venture – and the area is important to lots of us here. He hoped that
people would find other to talk to, find customers and so on, and gain insight from each other by talking about, and understanding the
issues
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Notes from Matt Stroud’s talk
Matt explained why the network had been set up, by drawing a parallel with the development of the railways in Victorian times – the
real value generated then arose because of its enablement of other services; the Internet was very similar – and the data carried by
the Internet had already generated huge economic benefits
Private data was harder to unlock value from, though, because of the complexity around the different aspects of that data – personal
trust and legal and political, for instance
It was important for people with an interest in this area to get together and work out how we could look at the central challenges
around trust in the use of personal data. There are practical issues here – but also ethical issues (the data affects people)
The network created today draws together the academic community, SMEs and corporate enterprises: all have different, valuable
perspectives. The network is a physical and virtual environment for these groups to work together
Some issues are open innovation and collaboration (useful for corporates); SMEs can meet potential customers and research the
thought leadership from universities; academia can learn what the commercial world’s challenges are and find opportunities to
commercialise their work
He encouraged people to register as a member of the network
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Purpose of the network
Dr Matt Stroud
Head of Personal Data & Trust, Digital Catapult

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Personal Data and Trust Innovators Network:
The rationale
• The next growth of the Internet is likely to rely on the successful generation
and management of personal data. High levels of trust and confidence in
these data are a pre-requisite for successful new services, which have both
huge economic and social potential.
• The Personal Data and Trust Network, building on world-class research and
business insight, will help organisations to develop the next-generation of
personal data management, giving the UK clear advantages for consumers
and citizens.

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Personal Data and Trust Network:
The Community
SME’s
Universities Corporates

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Benefits of membership….
Corporate benefits:
• Access to potential innovation partners
• Supports corporate open innovation programmes
• Gain insight to evolving market trends, capabilities and opportunities
• Visibility of academic research & innovation
SME benefits:
• Opportunity to meet and work with potential customers
• Opportunities to meet other innovation partners to further differentiate your product
• Visibility of and contribution to, cutting edge thinking
• Identification of commercially important problems
Academic benefits:
• Problem definition of commercially important problems
• Build research roadmap
• Partners to commercialise capabilities
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Membership of the network is free.
So that we can best organize events, could you register @:
http://www.PDTN.org or
http://www.digitalcatapultcentre.org.uk (in the “Get involved” section)
Personal Data and Trust Innovators Network:
Registering

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Notes from Alex Craven’s presentation [1]
Alex runs an advertising agency and has trust issues – he spoke about his professional and personal issues
His agency uses individuals’ Twitter and other data, from advertisers and elsewhere as part of its work for ITV – there was a huge
amount of data. Twitter was a very large source of useful data – e.g., about the conversation that happens when the X Factor is
broadcast. There is real value and his clients and he makes money from it
Alex is a member of the Open Data Institute, and is thinking about how data can be used for good; for instance, analysis of Tesco
Clubcard data can identify potential diabetes sufferers two years before they present themselves – saving treatment costs worth a
huge mount of health service money; McKinsey reckons big data can save an enormous amount of healthcare money
But as a consumer he is less interested in the technology, and more interested in the trust issue
He sees lots of technology innovation, but where is the trust? He is trying to launch “Our Data Mutual” – and he presented briefly
about it. He made the point that banks protecting you from identity theft is for their own benefit, not yours
Ipsos Mori reported last year on public attitudes to trust (seen this) – Bloom has won a contract to do some research in this area; he
picked out some highlights from the Ipsos Mori report – including where trust was low (large companies) and that people could not
see the benefit of the use of much personal data by companies (or the state, or academia…)
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Notes from Alex Craven’s presentation [2]
So how do we get trust into private organisations?
There are contradictions here: He made the point about people’s stated attitudes to trust and privacy, and their practice (e.g., with
how they use social media)
Alex said he felt we are at a crossroads – and this forum today is critical and must arrive at a consensus. Prohibition will not work. We
can’t go back. We can’t do nothing (it’s the wild west, and the only people benefiting are a few corporates) – society can benefit, and
we can do better
Privacy is dead – it never existed. We must move on, and we must do something. We need a trust framework that enables a market
to exist while giving individuals some control over the use of their data
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WHERE IS THE TRUST?
@ALEXCRAVEN
@BLOOMAGENCY

Tesco clubcard can identify type 2 diabetes 2 years before you present
yourself to your doctors with symptoms – the rise of diabetes could bankrupt
the NHS within a generation
50% of global advertising spend is wasted - $250bn
Data can save 8% on US health care - $300bn *McKinsey
Our data opportunity

Keep me private
£low
Don’t care £high
Only for good Don’t care
We can earn you £947

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Version 1 | Public© Ipsos MORI
Version 1 | PUBLIC
Public attitudes to the use and sharing of their
data
Research for the Royal Statistical Society by Ipsos MORI
July 2014
23/07/14

Royal Statistical Society Ipsos MORI report finds ‘data trust deficit’
http://www.statslife.org.uk/news/1672-new-rss-research-finds-data-
trust-deficit-with-lessons-for-policymakers
‘In particular, there may be big benefits to be had from data
sharing within government, but to get a public mandate
policymakers must be clear about the benefits and show how they
will safeguard individual privacy’
The Problem

48
Version 1 | Public© Ipsos MORI
University researchers
Government-funded – 50%
Company-funded – 45%
Charities
Who provide public services –
42%
For themselves – 36%
Companies
Who provide public services –
36%
For themselves
Mentioning controls – 27%
No mention of controls –
26%
A hierarchy of support for data sharing?
By whom For whom
But at this level
controls make no
difference?

If we are asked whether we are worried about privacy we are, yet we repeatedly
ignore this in our every day lives.
We want to receive the benefit of our data but we cant really be bothered to do
anything about it.
We assume we are being protected from abuse of our data but actually we are not.
We contradict ourselves

PRIVACY MUTUAL BENEFIT
GO BACK WILD WEST

There is no going back – privacy is dead, in fact it never existed, move on..
EU regulation wont work
Wild west abuses the citizen and will eventually ‘eat itself whole’ fuelling the privacy
hawks
There is a huge opportunity but we wont realise it until we can establish trust
There is clear evidence for a requirement for new institutions to establish a trusted
environment
Who’s data is it anyway?

Where is the trust?
Any questions? Please
contact:
Alex Craven
alex.craven@bloomagency.co.uk
@alexcraven
@bloomagency

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Notes from Rav Bain’s talk [1]
Rav advises banks on “conduct risk” – helping them conduct themselves better, and to reduce operational risks. Banks must comply
with lots of new regulation – an eyewatering amount. They spend billions on compliance, and there is a lot of data involved. Senior
executives will be held personally responsible for breaches of trust – so they must rely on their companies’ strong policies and
frameworks and systems; they have to trust their colleagues to do the right thing – and measure those colleagues!
There must be microscopic tracking and surveillance of trading-floor activity and branch activity. Rav mentioned MIFID and MIFID 2
regulations (governing the certain types of financial products) and having transparency of a trade before and after it happens. He said
to achieve this you need to rearchitect systems. It is a multi-dimensional prolem for banks
Organisations like the Personal Data and Trust Network will create a body of work that can be used by corporates – and not just
banks; telcos and other corporates that manage personal data or large amounts of data all have similar issues
Rav said that if you are made to do something about this you need to work out what you are going to do? We all agree that there
should be an appropriate level of regulation (and compliance with it)
He gave an example: think about data entering the banking system with a transaction (e.g., applying for a loan). Do you want this
data held forever? So how do you decide how to get rid of data at the right time? He said he was not sure how the market is turning –
it feels like kids’ football – we’re all chasing the ball wherever it goes
54

www.pdtn.org
#PDT
Notes from Rav Bain’s talk [2]
In defence of big corporates, Rav said they are pretty good at managing your data (though there are exceptions). A typical UK high
street bank has 8-15m customers – and they look after a lot of data. But we need to crack down on the exceptions. And we should
think in fresh ways about the issues
Big banks and other financial services companies and consultancies don’t have all the bright ideas – there are many ideas “out
there”. A network like this will not just build consensus but will build a critical mass of thinking. If we find Europe is more heavily
regulated on privacy, and we are quicker and more agile, then can we make this work for the UK?
55

www.rcuk.ac.uk/digitaleconomy
Personal data and trust research
Personal Data and Trust Network Inaugural Event
Digital Catapult, London, Wednesday 11 March 2015
Jerome Ma
RCUK Digital Economy Theme
jerome.ma@epsrc.ac.uk
@RCUK_DE #PDT

RCUK Digital Economy Theme
• >£150M since 2008; 400 user partners
• Co-creation approach (users, society, business and/or
government)
• Interdisciplinarity is key
Rapidly realise the transformational impact
of digital technologies on the UK

DE Theme priorities:
2015 onwards
Trust, identity, privacy & security
What are the urgent challenges/questions?
Research roadmap

University Expertise
Aberdeen computational models of norms & trust
Birmingham applied criminology
Buckinghamshire
information security management; cybercrime;
compliance
Cambridge systems for privacy preservation
Cardiff
politics and social issues of the creative & digital
economies
City cloud security and trust; identity management
Edinburgh design informatics; big data ethics
Imperial
defence and security; language-based computer
security and data analytics.
KCL computational models of trust & reputation
Lancaster
privacy; identity management, access control
models; reputation
Leeds digital identity
Leicester
online trust, privacy, security & surveillance
issues; cyber-ethics.
Loughborough empathy and trust in online communication
Newcastle
user experience; cybersecurity, defence, critical
infrastructure protection
Nottingham personal data in media, services & products
Northumbria identity, trust & security in new social media
Oxford big data ethics; cyber security centre
Queens Belfast
trust, e-commerce; online buying behaviour
Southampton AI; autonomous systems; meaningful consent
Strathclyde internet law
UCL mobile systems; cybersecurity
Warwick
novel service business models; attitudes
towards data security, trust & privacy
Wolverhampton online behaviour
Edinburgh
Aberdeen
Newcastle &
Northumbria
Southampton
Oxford
Nottingha
m
UCL
Imperial
Birmingham
Cardiff
Strathclyde
Lancaster
CambridgeWarwick
Wolverhampton Loughborough
Leicester
Belfast
Leeds
KCL
City
UK PD&T research:
expertise & location

£12M each (£2M partnership funding)
dot.rural, Aberdeen
SocialInclusionDE, Newcastle &Dundee
Horizon, Nottingham
3 Digital Economy Research Hubs

www.pdtn.org
#PDT
Notes from Derek McAuley’s presentation [1]
Mac spoke about the work of Horizon, and the lifelong contextual footprint of a person – the digital traces created explicitly and
implicitly. He said there were opportunities and challenges in personal data and Horizon was exploring these through lots of projects
(of 9-12 months each). Topics are refined, but work is done in short bursts. He gave the example of “smart meters”– the data
collected and the privacy implications of knowing, per second, people’s energy usage and the implied knowledge that is created from
this (e.g., “I know you didn’t have a shower this morning …”)
Condition monitoring of domestic appliances would be good (and enabled by smart meters), but the privacy issue raises its head.
What will actually get deployed in the UK? Only once a day reading (or opt out to a minimum frequency of once a month, or opt into
once every half hour). But has the privacy issue been solved? No. And we’ve lost the ability to do some great applications.
In my view this is simple to resolve: it’s small data and it should be processed in isolation. The reason we have lost this great
opportunity is because of the privacy and the lack of value recognition. We need distributed computing to do this properly. Distribute
the code and the computation instead of doing “big data”. There is academic work that proves you can do distributed processing to
extract value without sending personal data to a single point
We also did work to evaluate the simplicity or otherwise of terms and conditions of usage, to examine what counts as “consent”. We
published work in 2013; bettingexpert.com analysed all the betting sites’ T&Cs and found you have to be 23 years old to understand
the English, let alone the legal position. This work was widely cited
61

www.pdtn.org
#PDT
Notes from Derek McAuley’s presentation [2]
Should we come up with T&C templates? Possibly. Government responded positively with the British Standards Institute.
Let’s see where that goes from here.
Final example – we have to teach people how to design these privacy and trust conditions into the products and services
they are designing. Ideation Cards (not a new idea) can be used here. In most design processes, data protection and
privacy isn’t high on the list of priorities – it is usually retrofitted at the end of the process. So we use ideation cards – a
location-based truancy tracker was an example design we thought about. There are lots of murky issues around that
service concept. Using the cards really helps people to think about them
What is “Legitimate Interest” – is it good enough that it’s “it’s legal”? Possibly not. There’s a Catch 22 about having to track
people to check that they don’t want to be tracked, for instance
62

TL; DR
Derek McAuley
11th March 2015

• What is/has Horizon been doing
• Three examples
– Technology
– Policy
– Design
• Topic de jour
The talk
64

The lifelong contextual footprint
• The footprint – the digital traces we create explicitly and implicitly as we go about
our everyday lives at home, at work and at leisure.
• The contextual – these digital traces enable personal technologies to infer our
activities and provide appropriate services.
• The lifelong – an inclusive digital society must consider how these digital
footprints are handled throughout our lives, literally from cradle to grave.
The opportunity
65

Broad range of applications, core topic:
“Lifelong Contextual Footprint”
Eye test - the current projects
66

Rollout across
UK by 2020
..but…
Readings once a
day, or opt in to
30 mins or opt
out to 1 month.
Privacy and smart meters

The way of small data: analyze at edge and then aggregate
• Privacy & performance & scalability
Data on the edge
68
Cloud
Edge
Analyze
Aggregate
Mainstream thinking: aggregate into cloud then analyze

Solve for voltages…
Examples…
69
DAR [1]
[1] “Teletraffic Science”, ITC12. Elsevier,
1989.

Policy impact
71
May 2013
Luger, E., Moran, S., and Rodden, T. Consent for all: Revealing the
hidden complexity of terms and conditions. Proceedings of ACM
CHI2013: Human Factors in Computing Systems (pp. 2687-2696).
ACM.

Policy impact
72
May 2013
www.bettingexpert.com uses it
to rank T&Cs for betting sites!

Policy impact
73
March 2014
Written evidence to Social Media
Inquiry by Select Committee

Policy impact
74
June 2014
Verbal evidence to
Select Committee

Policy impact
75
Nov 2014
Report with strong
links to our input

Policy impact
76 Nov 2014
Widespread
coverage

& The University of Nottingham
The design process

• Define/constrain design problems within broader problem space (Golembewski &
Selby, 2010)
• To surface human values (Friedman & Hendry, 2012)
• Support intra/inter-familial communication (Mackay, 2004)
• Encourage thought around security threats (Security Cards, Washington)
• Support use of creative methods within design process (IDEO)
• Support exploration of issues around online privacy (Privacy Game)
Ideation Cards in Use

Tracking Truancy
Truancy is a key problem in
urban deprived areas and is
costly to the state. The
commissioning body (govt
department) wants a
location-based social
'tracking' system that will
allow parents and teachers to'
track' truants. This system
makes use of location data.

Limited Connection
The system should be
able to operate with
limited/sporadic
connectivity

Children
Children and
adolescents

Explicit Consent
Data should only be collected where a user
has been given information about the
nature of collection, and then specifically
and explicitly agreed to it.
The form of that information or how it is to
be delivered is not defined. Highlighting
risks to users and enabling
negotiation/withdrawal with the system
over data collection is a challenge.
Consent is also not a static concept either
(e.g. given once, does not mean forever).

http://www.horizon.ac.uk
Questions?
derek.mcauley@nottingham.ac.uk

www.pdtn.org
#PDT
Notes from Paul Watson’s presentation [1]
We focus in our hub on those who are socially excluded – it could be up to 20% of the population, including the old, those
with disability, those without skills or jobs…
We felt that there was potential for digital technology to make a difference to the socially excluded. We have run many
projects over five years – and many of them have had a security or trust issue. I will pick three examples to show you that
illustrate things I have found:
Digital technologies can give insights as well as solutions: you get a view into people’s lives that you can use to solve
their problems. Trust of older people in technology is lower than it is for younger people, and this is an issue for
government as it moves services online. We explored, using clickstream analysis, how people navigate around websites; it
varies by age. We researched the nature of trust and how it relates to the Web. Older people’s trust is often based on
brand – we were able to test this through research. Eye-tracking technology was used to better design web pages that you
want people to trust. “Certification” of the brand on the web page is really difficult to do; web page design aesthetics were
more important than brand
Target socially excluded people: example of victims of domestic violence are often subject to abusers seeing what they
do online. Deleting search history etc is only partially successful because it arouses suspicion. You need to be much more
subtle than that – routines that selectively clear search history or weblogs etc.
85

www.pdtn.org
#PDT
Notes from Paul Watson’s presentation [2]
Design for scalability: this generates security issues. Example of healthcare and wearables; IT systems choice (the
cloud for no risk; internal IT for anything with risk – this inhibits cheap, fast, scalable service development). So partition
applications to make use of cloud resources – e.g., only send anonymous data to the cloud; keep attributed data internally
Create multidisciplinary teams – security, domain and systems experts, coproducing
86

Paul Watson
Newcastle University

The result of related factors
that prevent individuals or groups
from participating fully in the
economic, social & political life
of society
Social Exclusion

How can
Digital Technologies transform the
lives of excluded people &
communities?

Lesson 1: Digital technologies can give insights, as
well as solutions

Ex. Older people’s trust of the Web

Lesson 2. Target socially excluded people &
communities

Ex. Victims of Domestic Violence

Lesson 3: Design for scalability

Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write Results
(s3)
A. Smith
378456729
p = 30%
q = 27.4
r = 34

Options
Application
Public
Cloud
Interna
l IT
Risk
?
Yes No

Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write
Results
(s3)
A. Smith
378456729
p = 30%
q = 27.4
r = 34
Public
Cloud
Private
Cloud
?
Or Can we Partition Applications?

Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write
Results
(s3)
Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write
Results
(s3)
Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write
Results
(s3)
Read Patient
Data
(s0)
Anonymize
(s1)
Analyze
(s2)
Write
Results
(s3)
1
4
2
3
New Method Generates secure
Partitioning options:

Lessons we’ve learnt
L1: Digital technologies can give insights, as well as solutions
L2: Target socially excluded people & communities
L3: Design for scalability
L4: Create multidisciplinary teams:
• security, domain & systems experts … and users
www.side.ac.u

www.pdtn.org
#PDT
Notes from Pete Edward’s presentation [1]
We are focused on rural challenges – not just rural broadband coverage, but much wider. In almost all our projects, there
have been issues that emerged relating to personal data and trust
I will talk about the themes that emerged across our projects that are relevant to this debate. Others were also looking at
specific relevant things (Facebook data, CareData fiasco, selling of personal data by individuals to the highest bidder…)
• Keep it user-centric – attitudes vary by demography, the kind of data, the context of the data usage … so we look at the
issues through an attitudinal lens – trust, risk, transparency and control (I think risk is sometimes forgotten)
• Example of work using smartphone data for rural bus planning – this raises anonymity issues because in rural areas,
individuals could be traced
• Mobile devices and wearables to support people with chronic disease in rural areas – attitudes to personal health data
sharing. We looked at different categories of personal health data (e.g., exercise regime, diet, mood). There is a
massive variation based on age, health etc…. Exercise data is not considered private; mood data is considered very
sensitive. Also looked at who people would be happy to share with – e.g., people don’t trust government, universities,
companies; they do trust their GP
102

www.pdtn.org
#PDT
Notes from Pete Edward’s presentation [2]
• “Conducting privacy impact assessments code of practice” (ICO’s office); identifying privacy-related risk – individuals
don’t understand risk, and especially risk in the digital world. This is a huge problem we all face. “Trusted Zone” idea for
personal health data – what about leaking the data outside the zone – even if it’s good and valid to do so; how can we
build a model that is flexible enough to cope with this and what controls need to be in place to mitigate perceived risk?
• Managing inferential risk – people generally don’t think about this. Social networks have data flying around – way
beyond where people expect it to go; also, sharing can result in unexpected risk – e.g., releasing two or three pieces of
data to different people that can be put together
• Control – how to allow users a measure of control over their data. How do you represent controls? Make them simple
and effective and understandable (like informed consent issue). Too much control can introduce new risks – in the event
of an accident, say, do you want your health data shared in a way that’s outside your normal “policy”?
103

myData with Attitude
Peter Edwards
dot.rural Digital Economy Hub
University of Aberdeen

Personal Data Landscape
Trust Transparency
Control
Risk
Influenced by the
foundational principles
of Privacy by Design.
“Keep it User-Centric”
Attitudes

Attitudes to Data Sharing
Your primary mental health
Your adherence and compliance
Your alcohol intake
Your contact information
Your criminal record
Your exercise level
Your medical history
Your medication
Your mood
Your personal characteristics
Your reproductive health
Your specialist mental health
Your substance abuse
Your test results
0 25 50 75 100
% respondents
Card
Sensitivity
Not sensitive
Quite sensitive
Highly sensitive
335 NHS users surveyed
Recruited though market
research (Research Now)
Online card-sort exercise to
identify sensitivity attitudes and
sharing preferences of health-
related information
Opinions about sensitivity of
personal data items vary
dramatically

Risk
Trusted Zone
A
B C
owner
requester recipient
data
How to protect information
when sharing is desirable,
but policies are incomplete?
Trusted individuals may need
to share our data with
unknown third parties
What’s the perceived risk for A, in allowing B to share with C?
How does A’s trust in B, and the sensitivity of the data, influence this risk
factor?
How can controls (such as payments, monitoring or reputation) mitigate
some of this perceived risk?
Identifying privacy related
risks key part of PIA process
Considerable body of
evidence that individuals do
not understand / appreciate
personal data risk

Managing Inferential Risk
What is the probability that users'
data become available to others in a
networked context?
How may data owners manage
unsafe inferences that others may
draw whilst sharing data?
How to assess the benefits of
sharing (utility) vs possible
risks?

Controls
• Allowing users a degree of control over their data
– helping users specify their wishes
– monitoring behaviour of data accessors
• Controls can mitigate perceived risk of sharing data
– Simple and effective controls? Must be clear to data owners and accessors
– Right level of controls? Too much control may introduce new risk of data being unavailable in
critical situations.

Transparency
Who controls a device and has
access to the data generated?
For what purpose are the data
collected?
Assurance of behaviour?
Making IoT device capabilities and
behaviours (data provenance)
transparent to users.

Thanks
Acknowledgements: Stanislav Beran, Chris Burnett, Liang Chen,
David Corsar, Paul Gault, Tim Norman, Edoardo Pignotti, Karen Salt
…

www.pdtn.org
#PDT
114
www.pdtn.org
#PDT
The future of the network
Dr Matt Stroud
Head of Personal Data & Trust, Digital Catapult

www.pdtn.org
#PDT
Where next? 115
• Future regular meetings
• Build digital presence
• Form community interest groups
• Create research roadmap
• Grow membership base

www.pdtn.org
#PDT
Future regular meetings 116
• We intend to hold regular (quarterly?) meetings, physically bring together
practitioners and researchers in Personal Data & Trust
• In addition there will be thematic meetings around the country
• We may use the “National Virtual Incubator” teleconferencing system to
make the London accessible from around the country
• Would your institution like to host a physical or virtual gathering?

www.pdtn.org
#PDT
Build digital presence 117
• Our new website:
PDTN.org
• Will be complimented by a quarterly PDTN Review journal
• Covering the Networks activities
• Features on members activities
• Expert articles

www.pdtn.org
#PDT
Form community interest groups 118
Some will be sector specific “verticals” such as banking and others will be
“horizontal” such as security or psychology. By way of illustration, two early
groups are:
• Privacy Working Group
Working to define a “best practice” privacy standard that companies can be certified against
• PIMS provider forum
Collective challenges and opportunities faced by providers of personal information management services
These are the first of many. If there’s a personal data and trust related topic which
you feel would benefit from an open working group and would like to establish,
please let us know.

www.pdtn.org
#PDT
Create research roadmap 119
• Bring together Industry and the Research Councils to create a
research roadmap which drives economic and social growth
• Spearheaded by a number of events run by the KTN and the Digital
Economy Hubs around the country
• SME’s and Corporates will be invited to contribute views and work to
identify key challenges
• Output will be fed into the Research Councils and IUK to guide future
research and calls.

www.pdtn.org
#PDT
Grow membership base 120
• We will grow the network by reaching out to our networks & social media and
working with media brands:
• We are writing white papers and working with the media to drive interest
• We are informing the organisations who have worked with us, IUK, Catapult,
KTN, Research Councils and Digital Economy Hubs
• We are Posting, Blogging & Tweeting
• Your colleagues, customers and collaborators will derive value too...
…let them know!

www.pdtn.org
#PDT
Your community, be part of it! 121
• Want to do a blog for the web site
• Want to write an article for the PDTN review journal
• Got an idea for a “community interest group”
• Want to join or lead a group
• Want to host an event
• Got an idea for the research roadmap
Then e-mail us: Matt.Stroud@cde.catapult.org.uk
jon.kingsbury@ktn-uk.org

www.pdtn.org
#PDT
Thank You
Personal Data & Trust Network
www.pdtn.org
#PDT

Personal Data and Trust Network inaugural Event 11 march 2015 - record

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