How will data be valued in the future and what are the key implications? What will this mean for business, for society and for individuals around the world? Ahead of the final expert workshops in the 2018 future value of data project, this is an interim summary of key insights to date.
This detailed presentation covers 7 areas:
Scope of Project
What is Data?
Areas of Agreement
Issues of Debate
Regionally Specific Topics
Questions on Value
Next Steps
To complete the research, over the next two months we will host more expert workshops across Europe and the Americas plus two more in Asia.
We will then prepare a synthesis of all the different expert views we have heard and, as with all our projects, share a global report for open use by all.
If you would like to be involved in the upcoming events, do let us know.
The Future Value of Data: An Emerging View to be Challenged
1. The Future Value of Data
An Emerging View to be Challenged
Interim Summary | August 2018 The world’s leading open foresight program
2. Contents
This is an interim summary of insights gained from the first 18 workshops
in the 2018 global Future Value of Data project. It covers 7 key areas.
Scope of Project
What is Data?
Areas of Agreement
Issues of Debate
Regionally Specific Topics
Questions on Value
Next Steps
4. The Value of Data
The economic incentive to generate and collect data from multiple
sources is leading to a data “land grab” by many organisations.
5. Aim of Project
Given the growing importance and power of data, as well as increasing
regulatory interest, we are focused on addressing several key questions.
• Is it in the data or in how it is used?
• Is it value for the individual, for business or for society?
Where is the real value of data?
• What is changing, where and why?
• What is the global consensus vs regional variation in this?
What issues are driving this?
• Given the regional variations on issues like privacy can there be a global view?
• What are the implications for future data ownership vs access?
What is a credible future framework?
• How should data be valued in the future, why and by whom?
• What will be the balance between public good vs. private gain?
Who benefits?
6. Approach
This project is engaging with multiple experts via immersive workshops in
important locations to explore the issues and build then share the global view.
Review
existing
research
Share initial
perspective
Explore
views via
global
dialogue
Identify the
key priorities
Prepare
global
synthesis
Support
hosts with
implications
7. Progress To Date
By the end of July we had undertaken 16 workshops across Asia and Africa as
well as the first of the European events. All will be complete by November.
Level of Privacy Regulation:
DLA Piper https://www.dlapiperdataprotection.com
Heavy Robust Moderate Limited
C Top 3 Challenges
Open Data Barometer – https://opendatabarometer.org/
Internet Penetration – https://data.worldbank.org/indicator/IT.NET.USER.ZS
ICT Development Index (2017) – http://www.itu.int/net4/ITU-D/idi/2017/
O Top 3 Opportunities E Top 3 Emerging Issues
Future Value of Data
Key Insights After 50% of Research
January to July 2018
Contact
london@futureagenda.org
Confirmed Events Proposed Locations
Johannesburg 17 MAY 2018
C Digital Literacy/Inclusion
Cyber Security Threats
Fake Data
O Open Data
Data Governance
Public Good/Human Rights
E Data Ethics
Data Sovereignty
Privatisation of Data
Pretoria 21 MAY 2018
C Data Literacy
Fake Data
Regulation
O Data Governance
Digital Taxation
Human Rights and Data
E Data Decolonisation
Government as Custodian
Data Bias
Madrid 22 FEB 2018
C Ulterior Motives
Joined Up Regulation
Democracy and Data
O Data Ownership
Data Ethics
Education and Social Contract
E Data-ism
Data Liability
Data Sovereignty
Dakar 26/27 JUL 2018
C Data Capital
Digital Skills
Fake Data
O Tax for Development
Digital Skills
Digital Education
E Data Imperialism
Human Capital
Latent Regulation
Stockholm 18 JUN 2018
C Digital Literacy
Rising Cyber Security
Data Ethics
O Open Data
Data Marketplaces
Broader Collaboration
E Data and Democracy
Data Liability
Privatisation of Data
Abidjan 29/30 JUL 2018
C Cyber Security
Data Imperialism
Data Ownership
O Data Ethics
AI and Humanity
Skills and Education
E Data Inequality
Regulation and Control
Democracy and Data
Lagos 10 JUL 2018
C Data Collection
Data Ethics
Data Inequality
O Data Regulation
Infrastructure Development
Data Literacy
E Data Ownership
Fake Data
Data Ethics
Nairobi 04 JUL 2018
C Cyber Security
Data Literacy
Identifying Truth
O Monetisation of Data
Understanding of Value
Data for Public Services
E Cultural Diversity
Empowering National Identity
Data Regulation
Abuja 13 JUL 2018
C Cyber Security
Digital Equality
Fake Data
O Digital Literacy
Data for Public Good
Transparency and Democracy
E Data Governance
Digitisation of Culture
Educating Government
Dubai 30 APR 2018
C Data Ethics
Cyber Security Threats
Informed Consent
O Data Ownership
Open Data
Blockchain
E Data Sovereignty
Trust in Data Use
Data Liability
Jakarta 17 MAY 2018
C Fake Data
Data Literacy
Data Imperialism
O Data for Development
Digital Taxation
Access to Data and Analytics
E Data Sovereignty
Data Ethics
Data Bias
Sydney 21 MAY 2018
C Data Ethics
Data Ownership
Rise of AI
O Open Data
Common Approach
Social Impact
E Data Liability/Negligence
Informed Consent
Data Literacy
Bangkok 23 MAY 2018
C Cyber Threats
Data Literacy
Data Politics
O Data Governance
Access Inequality
Open Data
E Data Ownership
Data Ethics
Digital Taxation
Tokyo 23 APR 2018
C Cyber Security Threats
Fake Data
Trust in Data Use
O Open Data
Metadata Value
Digital Skills
E
Bengaluru 10 JAN 2018
C Informed Consent
Privacy Harms
Individual Custodianship
O Machine Learning
India Setting Standards
Social Value of Data
E Data Ethics
Data Sovereignty
Data Liability
Data Liability
Data Marketplaces
Digital Taxation
COUNTRY
ICT
Development
Index
(2017)
Australia 8.24
Cote D’Ivoire 3.14
India 3.03
South Africa 4.96
Indonesia 4.33
Japan 8.43
Kenya 2.91
Nigeria 2.60
Senegal 2.66
Singapore 8.05
Spain
Open
Data
Barometer
(2016)
81
11
43
34
38
75
40
21
9
53
73
Internet
Penetration
%
(2016)
88
27
30
54
25
93
26
26
26
81
81 7.79
Sweden 70 90 8.41
Thailand 28 48 5.67
UAE 26 91 7.21
Singapore 27 APR 2018
C Data Ethics/Principles
Data Sovereignty
Cyber Security Threats
O Democracy and Data
Data Education
Open Data
E Data Marketplaces
Data Liability
Privatisation of Data
9. Metaphors
Whenever something new arrives we often seek to explain it by making a
comparison to something already existing and so use a metaphor.
Cloud (2006)
Highway (1991)Web (1989)
Common Internet Metaphors
Cyberspace (1984)
Virtual communities (1993)
Firewall (1994)
“A faster horse” (1908)
10. Data is the New…
Data can fulfil different roles in the economy and in society. Views on
metaphors may help us understand it. Here are some suggestions to date.
11. Data is the New Oil? (The Economist and others)
Vast hordes of data can make its owners very wealthy and powerful but unlike
oil it is not a finite, exhaustible resource, nor are the costs of extraction high.
12. Data is the New Currency? (WSJ and others)
Data can certainly serve as a medium for exchange and can also be used as a
store of value, but describing it as currency just tells us it sometime has value.
13. Data is like Water? (Bangalore)
Data is like water - abundant and essential. It enables many other things of
greater economic value to grow and develop. But it itself has little or no value.
14. Data is like Sap? (Madrid)
Data is like sap – a conduit for the good and the bad: nutrients to nourish
growth and development but also it an spread disease.
15. Data is like Sunshine? (Tokyo)
Data is like sunshine – free, continuous, everywhere and infinite. It’s exist
independent of human interaction but its power can be harnessed
16. Data is like the Periodic Table? (Singapore)
Data is similar to the elements on the periodic table. They can act
independently but interact with each other to create new combinations.
17. Data is like Air? (Dubai)
Data is like air – it is all around us and lets things live. We would be nothing
without it and yet it is intangible and invisible.
18. Data is like Religion? (Copenhagen)
Data is like a religion – people believe it is the answer to everything
but belief in it can control people – for good and for bad.
20. Areas of Agreement
In the discussions to date, there have been a number of issues related to the
future value of data about which there has been consistent priority.
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Open Data
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Data Literacy
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Clear Data Value
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Rise of the Machines
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Data Ethics
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Trust in Data Use
21. Data Ownership
Traditional legal models of ownership to digital data cause debate. The focus
shifts from ownership to the question of who is benefitting from what data
22. Digital Literacy
There are increasing calls for education to address data and media literacy.
Key to this is the ability to differentiate between fact and fiction.
23. Clear Data Value
Organisations have to be clearer about why they value specific types of data
and on what terms, or they risk losing public trust and their licence to operate
24. Trust in Data Use
Trust increasingly drives success. To gain buy-in from governments and
consumers, trust in data usage becomes a core source of differentiation.
25. Fake Data
Poorly collected, deliberately contaminated or fabricated data drive weak
decision-making, inaccurate and biased AI, bad governance or societal unrest.
26. Informed Consent
Informed consent around data use is increasingly impractical and unworkable.
Alternative models addressing transparency and data rights are developed
27. Data Ethics
We need a universal framework on data use to build trust in the system, create
a more competitive marketplace, maintain order and establish accountability.
28. Rising Cyber Security Threats
In some areas, greater interconnectivity and the IoT create new opportunities
for the unscrupulous who seek to exploit weakness and destroy systems.
29. Open Data
In many contexts, data is increasingly openly shared for free.
The positive social benefit is seen to outweigh any economic loss.
30. Data Liability
Storing some kinds of data could come to be seen as a liability as it erodes user
trust, and the costs of securing it outweighs the costs associated with losing it.
31. The Rise of Machines
AI presents both a threat and an opportunity: Greater AI and automation free
up time, but also threaten jobs - both low skilled and administrative roles.
32. Privatization of Data
In sectors such as healthcare the privatization of public knowledge test
the view that most information should be a ‘public commons’ for all.
34. Issues of Debate
There have also been a number of issues about which there have been
differences of opinion on future impact and relevance across varied locations.
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Declining Significance of Privacy
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China vs the US
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Data Capital
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Block-chain for Trust
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Digital Taxation
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Sharing Secrets
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Too Much Information
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Data Imperialism
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Democracy and Government
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35. Digital Taxation
Governments increasingly seek to tax digitally-driven sectors and introduce
a number of approaches to link this to locations of data generation and use.
36. Data Marketplaces
Ecosystems for trading data are emerging and soon both personal and
machine data are openly brought and sold in new data marketplaces.
37. Data Capital
Integrated Reporting will include data as a ‘capital’ alongside financial, social,
environmental and human capital. Annual reports will reflect this.
38. Democracy and Government
Citizen data is increasingly used and shared by governments as an
instrument of social change. The limitations around its use are challenged.
39. Block-chain for Trust
Distrust drives the adoption of block-chain which offers a universal set of
tools for data integrity, standardized auditing and formalised contracts.
40. China vs. The US
The data battle between US and China will become a major issue.
Tencent vs. Google will be just one of many global competitions.
41. Data Imperialism
Dominant services, built by western engineers, reflecting western values are
increasingly seen as imperialist interlopers, irrelevant in different regions.
42. Sharing Secrets
In exchange for better service or an improved quality of life, we increasingly
recognise exactly what personal information we are prepared to share.
43. Too Much Information
As more data is available, the fear of data overload exceeds the individuals’
capacity to see things in perspective leading platforms to filter what is shared.
44. Data Politics
Data politics enters the mainstream as more people come to understand
impact of its the collection and use of their personal data on their own lives.
45. Declining Significance of Privacy
The concept of privacy is relatively new: most people don’t really care about
it - they are indifferent. In ten years time concerns about privacy will subside.
46. Data Sovereignty
Sensitivity over ownership of personal data constrains sharing across national
borders. In particular, resistance to a US-based concentration of data builds.
48. India Setting Global Standards
India has an innovative data design solutions for large populations.
Many are applied to higher income economies seeking efficiency benefits.
49. GDPR Setting Standards
There needs to be a balance between national and international approaches.
GDPR offers a positive template around the collection and ownership of data.
50. A Commons Approach
Europe is well-positioned to lead a very different kind of data revolution – one
where companies pay for access to our data – that we mostly own in common
51. The Data Burden
Poorer economies shoulder the burden of ‘pollution’ created
by the data consumption habits of wealthier nations.
52. The Risk of No Data
Government control of internet access leads to communication restrictions, the
absence of free speech and the inability to disseminate accurate information.
53. Licencing Culture
A global code of cultural ethics is supported by a global oversight organisation.
Cultural Data is treated as intellectual property which can then be licensed.
54. Low Trust - Poor Data
Low levels of trust in government, institutions and big tech devalues data by
making databases unreliable. Citizens choose not to share accurate information.
55. Global Standards and Institutions
As regional politics and data polarization grows, open standards become
important. So we seek guidance on sharing - maybe from global institutions.
56. Data Localisation
Tired of “Amerification” an informed public calls for regional data centres that
are better equipped to protect individual data than commercial organisations.
57. Regulation Pockets
Governments use tax and regulation to protect consumers and establish state
control of powerful data-sets. This limits innovation and has negative outcomes.
58. Digital Vision
To avoid the ill-considered adoption of the shiny and new, regional governments
construct a ‘Data Vision’ - a strategic template for data-driven technologies.
59. A Public Good
The broader use of data for public good drives system reliability,
interoperability and consensus around when individual data can be used.
60. Global vs. Local
Data does not respect national boundaries. Nation states try to set rules.
Growing tensions drive design for global standards but with localised use.
61. Hidden Environmental Costs
Over 5% of the world’s energy is already used to data centres: In the future
there will be so much data that we may not have the energy to store it.
63. Multiple Views
In defining exactly what is the ‘value’ of data and how it should be valued,
several have highlighted different views that should be considered.
65. Complete Global Discussions
To complete the research, over the next two months we will host more
expert workshops across Europe and the Americas plus two more in Asia.
66. Global Report
We will then prepare a synthesis of all the different expert views we have
heard and, as with all our projects, share a global report for open use by all.
Future of Cities
(2016)
https://www.futureofcities.city
Future of Philanthropy
(2017)
https://www.thefutureofphilanthropy.org
Future of Patient Data
(2018)
https://www.futureofpatientdata.org
The World in 2025
(2015)
https://www.futureagenda.org
67. Future Agenda
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