This is an updated view on the future value of data. After events in Bangalore and Madrid we have added extra perspectives and these are all now being taken on to forthcoming workshops across Asia, Africa and South America in April and May. Further events across Europe and North America in June and July will then complete this major global project

1. The Future Value of Data
An Emerging View to be Challenged
Singapore | April 2018 The world’s leading open foresight program

2. Context
This is an point of view on the topic of the future value of data. It is a
perspective to be shared, challenged, built upon and enhanced via a series
global discussions that are taking place throughout the first half of 2018.

3. 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.

4. Data is the New…
Data can fulfil different roles in the economy, in society and for individuals.
Simplistic views help us understand some roles, but also mislead and blind us.

5. Data is the New Oil?
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.

6. Data is the New Currency?
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.

7. Data is like Water?
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.

8. 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.

9. 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.

10. Polarized Data Debate
The debate becomes extreme. Protagonists adopt ‘all or nothing’ positions
on issues such as privacy, encryption, security and economic freedom.

11. Open Data
In many contexts, data is increasingly openly shared for free.
The positive social benefit is seen to outweigh any economic loss.

12. 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.

13. Shared Language about Data
A shared language around the definition and use of data emerges
but it is not clear which voices will be seen as credible and authoritative.

14. 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

15. Talking at Cross-purposes
Different stakeholders have very different perspectives on (and understandings
of) what data is. This makes the quest for common ground increasingly difficult.

16. 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.

17. Increasing Public Confidence
The public becomes more informed about the issues that really matter.
There are new approaches around data education, transparency and choice.

18. Joined Up Regulation
Policymakers and regulators undertake a more joined up approach to data
regulation stimulating growth on one hand, and minimising risk on the other.

19. Sustainable Customer Relationships
Organisations build long-term trust-based relationships with the people who
use their services and so create a broader ecosystem based on social value.

20. Data Marketplaces
Ecosystems for trading data are emerging and soon both personal and
machine data are openly brought and sold in new data marketplaces.

21. Ethical Machines
As we approach technology singularity, autonomous robots and
smarter algorithms make ethical judgments that impact life or death.

22. 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.

23. Personally Curated Data
‘Personally curated’ sources of data have higher value because they represent
the wishes of individuals, rather than the presumed wishes from derived data.

24. Digital Shadows
It is difficult to differentiate between the digital truth and the real truth.
There is growing awareness of the importance of managing our digital shadow.

25. 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.

26. 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.

27. 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.

28. Linkability of Open Data
No data will be anonymous: Current practice wrongly assumes that technology
cannot relink it to its source. So, we see different levels of re-identification.

29. 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.

30. 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.

31. Living in Glass Houses
We will allow our personal information to be widely accessible in return for the
understanding that this enables an easier, more ‘streamlined’ life as a result.

32. Informed Consent
Informed consent around data use is increasingly impractical and unworkable.
Alternative models addressing transparency and data rights are developed

33. India Setting Global Standards
India has an innovative data design solutions for large populations.
Many are applied to higher income economies seeking efficiency benefits.

34. The Privacy Illusion
There is a rising belief in the right to data privacy and security. But security is
impossible without increased monitoring - and so true privacy is illusive.

35. Machine Learning Driving Accuracy
As more people use apps as “AI” advisers, more data is collected and machine
learning improves significantly. Devices therefore deliver more accurate advice.

36. 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

37. Individual Custodians
People make more informed personal decisions as they become custodians of
their own health and financial data. They control who can access their data.

38. 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.

39. Conservative Regulators
Legislators desire certainty and are concerned about the consequences of
change. They therefore slow adoption of new technologies and approaches.

40. A Public Good
The broader use of data for public good drives system reliability,
interoperability and consensus around when individual data can be used.

41. 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.

42. Decentralized Secure Data
We decentralize more of our data in an ambition to make it more secure.
However as technology evolves, distributed data is more easily integrated.

43. Data Sovereignty
Sensitivity over ownership of personal data constrains sharing across national
borders. In particular, resistance to a US-based concentration of data builds.

44. Dataism
More place their faith in the power of data to drive efficiencies and solve
problems. This blinds many to the flaws in data-sets and applications.

45. Data Imperialism
Dominant services, built by western engineers, reflecting western values are
increasingly seen as imperialist interlopers, irrelevant in different regions.

46. Artificial Empathy
The race for machines that emulate human emotions leads to unintended
consequences as the unpredictability of driving behaviours takes hold.

47. Fake Data
Poorly collected, deliberately contaminated or fabricated data drive weak
decision-making, inaccurate and biased AI, bad governance or societal unrest.

48. Data from the Child’s Point of View
Rather than designing for adults (whose psychology was formed pre-big data),
we increasingly shape our systems and services for the users of the future.

49. 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

50. Future Agenda
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