Advancing Digital Agency:
The Power of Data
Intermediaries
INSIGHT REPORTFEBRUARY 2022

Images: Getty Images

Contents
Preface3

Executive summary

4

1 The challenge: Human–technology interaction
and the data value chain

5

1.1 Introduction: The trust gap in data sharing

6

1.2 Introducing data intermediaries

9

1.3 Exploring data value chains

11

2 The opportunity: Trustworthy human-centric data intermediaries

13

2.1 Data intermediary organizational models

14

2.2 The policy environment

17

2.3 Human-centricity and fiduciary duty

18

3 Moving towards trusted digital agency

20

3.1 The role of digital identity in supporting human agency

21

3.2 Automated decision-making

25

3.3 A potential trusted digital agency model26

4 Reshaping human–technology interaction

28

4.1 How the use of data intermediaries shapes human–		
technology interaction29

4.2 User experience design consequences of using a third-		party digital agent

30

5 Levers of action

31

5.1 For governments: Future-proof regulatory support

32

5.2 For businesses: A policy leadership role

36

Conclusion

37

Glossary

39

Contributors

41

Acknowledgements

42

Endnotes

43

Disclaimer
This document is published by theWorld Economic Forum as a contribution to a project,insight area or interaction. The findings, interpretations andconclusions expressed herein are a result of a collaborative
process facilitated and endorsed by the World Economic
Forum but whose results do not necessarily represent theviews of the World Economic Forum, nor the entirety of its
Members, Partners or other stakeholders.
© 2022 World Economic Forum. All rights reserved.
No part of this publication may be reproduced
or transmitted in any form or by any means,including photocopying and recording, or by any
information storage and retrieval system.

Advancing towards Digital Agency: The Role of Trusted Data Intermediaries

2

February 2022

Advancing Digital Agency:
The Power of Data Intermediaries

Preface
The power of the data ecosystem has neverbeen greater but the system itself is becoming
more difficult to navigate.
Navigating the data ecosystem

Anne Josephine
Flanagan
Data Policy andGovernance Lead, World
Economic ForumThe power of the data ecosystem has neverbeen greater but the system itself is becoming
more difficult to navigate due to increasing
complexity. We share and receive data every day
to interact with the technologies that serve us,
whether in a personal or commercial context.
Data value chains then funnel, use and reuse thatdata, usually for commercial or public interest
purposes. These value chains, often involving
personal data, are at best complicated to follow;
at worst they can lead to mistrust in data sharing
and can potentially give cover to bad actors.

Contrasted with this complexity is our relianceon data sharing both as our way of life andas the backbone of the global data economy
and the key to technological innovation.
If mistrust in the data ecosystem acts as a pointof failure leading to suboptimal outcomes for
us all, what can be done? What if there was abetter way whereby data could be more easily
traced, more easily permissioned, more easily
controlled by data rights holders (including
people) across the data ecosystem?

Data intermediaries as a lever of action

Sheila Warren
Deputy Head, Centre
for the Fourth Industrial
Revolution Network,
World Economic ForumIn this report, the World Economic Forum’s
Task Force on Data Intermediaries, composedof business, academic and civil society actors
worldwide, explores these questions and more.
Building on the Forum’s Redesigning Data Privacy:
Reimagining Notice & Consent for Humantechnology Interaction1 report, the task force
examines data value chain scenarios as they
already exist today – and may exist in the future –with a view to improving both human–technology
interaction and data sharing more broadly.

In an era that has policy-makers moving beyond
just privacy laws and to grapple with developing
policy levers designed to support data-sharing forcommon purposes, the task force shares what it
has learned to support responsible policies. The
value-added use of data intermediaries as a key
to unlocking complexity and building trust holds
the promise of protecting the interests of data
sharers and data subjects alike – and ultimatelythat of society.

Towards trusted digital agency
Taking lessons from global business, the researchcommunity and cutting-edge technology design,
we explore best practices in the use of dataintermediaries. We identify various models,
including the organizational data intermediary,
such as the data trust, that assumes a fiduciary
duty. We explore the automated gateway that
predetermines standard rules. And we look to the
future, to the artificially intelligent agent that allows
for autonomous third-party decision-making on
our behalf, with its associated promises and perils.

Finally, although any views expressed do not
represent the views of any individual taskforce
member or their organizations, we invite you
to join us on this journey of exploration as we
unearth and build a picture of where consensus
may or may not lie in unleashing the power of dataintermediaries leading to trusted digital agency –and where and when these types of policies could
potentially be deployed.

Advancing Digital Agency: The Power of Data Intermediaries

3

Executive summary
Data intermediaries represent a new policy
lever to navigate the challenges of thegrowing data ecosystem.

The challenge
Everyone is familiar with the paradigm of going
online and clicking on terms and conditions they
don’t understand (or take time to read). No one
knows (nor follows) what happens to their data.
This status quo creates a reliance on companies tobe responsible but can lead to mistrust in the data
ecosystem as a whole. Further, mistrust between
people and technology becomes amplified themore complex the data ecosystem becomes overtime. Where once people had screens to navigate,
new ambient data collection methods with their
many benefits create nervousness and resignation
when people don’t have the full picture. In somecases, individuals may opt out of interacting withtechnologies that would be of huge benefit to theirlives. But what if it were possible to outsource thesedecision points to a trusted agent acting on an
individual’s or even a group’s behalf?

The opportunity
Now that screenless technology is a part of everyday
life, there is an opportunity to rethink the human–
technology interaction paradigm and reposition
the debate to focus on roles and responsibilities
beyond the person. How can the use of dataintermediaries help people navigate technologies
and data ecosystem models without losing sight ofwhat it means to be human, in terms of agency andexpectations? How can people think beyond thatgiven that, as they move towards the complexity ofscreenless metaverse issues, their understanding of“humanness” is transforming? Data intermediaries–
especially digital agents – represent a new policy

lever through and around which individuals canpotentially navigate the challenges of the growing
data ecosystem. This report seeks to shed lighton an alternative method of mediated human–
technology interaction whereby data appears totravel seamlessly from people to technology in ahuman-centric and, crucially, trusted manner. By
communicating shared incentives, establishing
reputation or receiving third-party verification, as
well as having assurance structures to mitigate risk
to both the intermediary and the rights holders,data intermediaries can increase trust between
people and the technology they interact with.

The solution
This report explores the opportunities and risks ofdata intermediaries and, specifically, third-party digitalagents. From data trusts to trusted digital agency,
the report paints a picture of a world that is more
empathetic to people and to companies, providing
greater certainty for data sharing as a foundation for

innovation through the introduction of a trusted third
party. Crucially, it suggests levers of action for boththe public and private sector to ensure a futureproof digital policy environment that allows for theseamless and trusted movement of data between
people and the technology that serves them.

Advancing Digital Agency: The Power of Data Intermediaries

41

The challenge:
Human–technology
interaction and thedata value chain
Trust between parties who seek
to share data is not a default state.

Advancing Digital Agency: The Power of Data Intermediaries

51.1 Introduction: The trust gap in data sharing
People mistrusteven the most
responsible andethical companies
because thesystem – the data
ecosystem – isso confusing tonavigate.

“Our days are filled with myriad discrete datacollection moments. Even when we have genuine
intent to affirmatively consent to each moment ofdata collection, it is practically impossible to do so:
No individual has the time to provide affirmative
consent on a near constant basis. This reality
arguably undermines our individual agency.”2
The world is experiencing something of a mistrust
pandemic when it comes to people’s engagementwith the data ecosystem. This global “trust gap” or“trust deficit” is a barrier to economic growth, digital
innovation and social cohesion. The technology
ecosystem is ultimately powered by the collection,
sharing and processing of data, often personalin nature. Data sharing is a driver of innovationin technology and of the digitization of matureeconomic models.
But trust between parties who seek to share or
exchange data is not a default state; it is somethingthat needs to be earned or built, often as a resultof great effort over time. This includes building trust
between people and technology. It is all the more

important when considering that people share data
every time they interact with the technologies
in their lives.
As Bill McDermott, former Chief Executive Officer
of SAP, has noted: “When trust is there, we can take
giant strides, turning our greatest challenges into
our biggest opportunities. When it’s not, the needle
gets stuck. Small hurdles become insurmountable.
Division overwhelms unity.”3
As defined by Russell Hardin,4 trust is a belief
that an actor will perform a specific action withina specific context, whereas trustworthinessis a property of an actor. The goal of dataintermediaries and the infrastructure that
supports them is to enable data rights holders
to trust trustworthy data intermediaries.
That is not to say that without trust andtrustworthiness there is no sharing of data; butwith trust and trustworthiness there will be greater
participation and in turn an increase in the volume andindeed the veracity of data made available as a result.

Advancing towards Digital Agency: The Role of Trusted Data Intermediaries

6

The problem of notice & consent
When presented
with privacy
notices, it isnecessary to takethe time to consider
the implicationsof terms andconditions andto overcome thebarrier presented
by the attention
required to think
explicitly about
preferences.

The challenges of meaningfully consenting topersonal data sharing, meaning the collection
and processing of personal data, are wellknown.5 Much of people’s interaction withtechnology relies on giving consent for datacollection and processing via a medium such asa screen. When presented with privacy notices,
it is necessary to take the time to consider the
implications of terms and conditions and to
overcome the barrier presented by the attention
required to think explicitly about preferences.
People need to think about what they reallycare about and foresee what their data might
be used for – if they can imagine it. The term
“decision fatigue”6 reflects something real: Lorrie
Cranor and Aleecia MacDonald of Carnegie
Mellon University researched7 the unfathomableburden of reading privacy notices that people
typically experience and the resulting difficulty
in being afforded the time to meaningfully react,
understand and consent to them. People aresimply too busy to take the time to read every
consent notice on websites. And even if they did,

could they truly anticipate how their data would
be used?
And what if there is no screen? Ambient datacollection, through for example closed circuit
television and connected devices, is increasingly
common. Getting to an acceptable default stateis more urgent than ever as the world moves
towards the creation of the metaverse where
the metaphysical state of human–technology
interaction becomes ever more seamless.
Other lawful bases for data collection andprocessing do exist in some jurisdictions, such as
legitimate interest or performance of a contract
under the European Union (EU) General Data
Protection Regulation, but they have their own
limitations. Courts the world over have been clearthat notice and consent is the preferred lawfulbasis in certain scenarios. In situations where
notice and consent has been deemed to be theonly existing acceptable standard, that constraint
can have limitations as described earlier.

Resultant mistrust
Today’s default state is not healthy. On the
one hand, people are sometimes accepting
and often left feeling disempowered; on theother hand, organizations struggle to accessand process data that can meaningfully
improve lives, health and even the planet.
People mistrust even the most responsible andethical companies because the system – thedata ecosystem – is so confusing to navigate.

As for the law, it struggles to keep up. Heavily
weighted in favour of principles that lack thenuance of specific scenarios, regulation’s
favourite tool is simply to ask: Can thisentity collect your data? And individuals say“yes” without meaningfully understanding
the benefits as well as the costs, and so on
and so forth as they continue to “consent”
without always meaningfully consenting.

A new approach
What if there was a better way? What if you
could outsource the decision-making fatigue
to a trustworthy third party? What if you could
pre-consent to your preferences so that you
did not need to continuously opt-in? Whatif technology allowed you to outsource yourdecision-making even further – to a digitally
automated agent, potentially using artificial
intelligence (AI), which could actively makethose decisions for you? All such scenarios
require the enlisting of an intermediary.
Is the world ready for such a radical and humancentred approach to managing data relationships

via a third-party data intermediary? Elementsof such a sophisticated and nuanced data
ecosystem already exist but the appropriate
policy frameworks are far from being in place tomake such a scenario viable at a systemic level.
In addition to asking this question, thisreport also explores the secondary effectsof such a scenario through the examinationof relevant use cases and asks what
actions public and private sector actors
can take when probing such issues for the
benefit of building a more robust, humancentric and sustainable data ecosystem.

Advancing Digital Agency: The Power of Data Intermediaries

7

Assumptions
For the purposes of this paper, several
assumptions are made.
The first assumption is that whatever the data
sharing relationship, data rights holders will
inherently mistrust each other without appropriate
safeguards, positing that a data intermediarycan potentially become that missing safeguard,
depending on the data-sharing scenario and thecharacteristics of that intermediary. The assumption
in all cases is that data rights holders have aninterest in their data rights: for example, people
care about information about them and companies
care about the value of proprietary information.
Secondly, when exploring data intermediarypossibilities, the relationships may be binary
or multi-party in nature. An example of thisis where data collected about people in asmart city environment can be used for the
purposes of urban planning; while the people
whose data was collected are themselves
rights holders, the sharing takes place several
times throughout a data value chain.8
Thirdly, it is worth nothing that data is contextual,
which means that non-personal data may become
personal in nature depending on the context,

for example, if combined with other datasets.
This includes business-to-consumer (B2C) andbusiness-to-business (B2B) relationships involving
someone’s personal data, but business-togovernment (B2G) scenarios are also relevant.
If data intermediaries anonymize personal data
and/or handle non-personal data, it may berecommended that they should have a process inplace to test the robustness of their anonymization
methodology. Nevertheless, given the difficultyof disassociating personal data from data setsthat contain otherwise non-personal data, andthe higher regulatory bar placed on the handlingof personal data, personal data will be used as aproxy for all data.
And finally, there is no silver bullet approach:policy responses are as nuanced as the scenarios
they respond to. It is assumed that the findingsof this work as they pertain to personal data may
be adjusted as relevant to apply to the treatment
of different scenarios, including exclusively nonpersonal data-sharing scenarios, such as B2B
sharing of proprietary data generated from nonpersonal data sources or unknown future use
cases. Indeed, it is intended that this paper bemade available to contribute to future work byothers in this space.

Advancing Digital Agency: The Power of Data Intermediaries81.2 Introducing data intermediaries
The possibilities of a mediated approach todata sharing by a third party are as limitlessas the possibilities of data sharing itself. Dataintermediaries can empower people to control
and even automate the flow of data about
themselves, improve cross-border data flows,
and allow for the leveraging of personal data forsocial impact, to name just a few use cases.

(such as people or businesses), depending on theparties’ relationships, intentions and resources.
They do so by encapsulating, communicating andenacting the shared interests of the relevant parties
and safeguarding their interests. At their most basic
level they facilitate the exchange of information; attheir most sophisticated they can assume decisionmaking, including on behalf of people.

Data intermediaries can take many forms; but what
they share is a primary purpose of facilitating andmanaging data relations between data rights holders

By definition, it is assumed that data intermediaries
are always third party in nature, as witnesses
to the primary data sharing transaction.

How specific data rights holders
may benefit from data intermediaries
To facilitate trust between data rights holders, at the most basic level data intermediaries may
communicate shared incentives, establish reputation or receive third-party verification; and haveassurance structures in place to mitigate risk to both the intermediary and the rights holders.
In addition, they can take on different roles for different kinds of data rights holders.

BOX 1

The role of data intermediaries for different data rights holders

People & society
A data intermediary can play a significant role in enabling people
to be more in control of their personal data, determining what
personal data is shared with which participants and for what
purposes. They can vet parties that would receive the data
to determine if they are “trusted” based on a set of externallypublished standards and criteria, thereby removing the obligationfrom the individual and thus removing the deficiency of the noticeand consent mechanism common in data protection regimes. A
data intermediary can leverage economies of scale to implement
technologies to enable greater protection of personal data
through real-time anonymization, pseudonymization9 or otherprivacy enhancing technologies and services. Conversely, thedata intermediary could also verify and confirm the identity of
the individual, thereby providing additional guarantees that the
information being shared belongs to the individual and has notbeen misappropriated or obtained by other means.
Data intermediaries could also provide a variety of services,
including that of matchmaker between supply and demand fordata. They could engage in security, authentication and fraud
prevention activities, such as performing verification serviceson the participants and the data being introduced based on a
range of parameters, from potential copyright infringement to
information security scanning of malicious code.
Businesses & private sector organizations
A data intermediary can act as a conduit to gain greater
access to permissioned personal data. It can also enable
greater sharing of that data between private corporations
and organizations. Private entities could benefit from the useof a data intermediary as a method of third-party verificationthat complies with a set of base standards, such as those as
determined by a sector or industry: this is already the case inrelation to information security and the tracking of illegal activity
online. A data intermediary can also help participants navigate
laws, regulations and other complex data privacy requirements,
thereby effectively outsourcing some of these services to theintermediary. It is for this reason that there has been a boom
in so-called “regtech” whereby third-party processes manage
information compliance. Such third parties could be classified
as private data intermediaries.
In a similar vein, scientific research institutions have been
proponents of data trust models for a number of years, giventhat the data trust can act as a trustworthy conduit to manage
access to data that otherwise would be inaccessible forpurposes other than research.10 This paper examines data trusts
in more detail later.
Government & public sector bodies
Although there is growing momentum to enable greater sharingof public data by government bodies, this remains sporadic and,
where personal data is involved, complex and limited. Opendata policies seek to streamline access to publicly held data but
often fall short. The World Economic Forum’s recent work on
empowered data societies,11 sheds light on this topic throughthe example of improving access to publicly held data in the Cityof Helsinki. One finding of that work is that citizen-held data canbe a rich source of relevant information for government service
provision and can enhance people’s lives by delivering value
for societies if conducted in a human-centric manner. A dataintermediary can help ensure trust in such a scenario.

Advancing Digital Agency: The Power of Data Intermediaries

9Advanced competencies of data intermediaries
The above are just a few main examples of theusefulness of data intermediaries. Some of themore advanced competencies of data intermediaries
may include:–

Storing individuals’ personal data within apersonal data space or a vault so that dataprocessing can happen within that space
without the transmission of personal data to any
parties outside the space; rather the insightsfrom the data are transmitted in a manner similar
to federated data learning models. Echoes ofthis idea appear in a proposal for Common
European Data Spaces.12–

Advising individuals on uses of their data,
including tracking who is uses their data andfor what purpose.

–

Strengthening individuals’ negotiation power
when influencing the terms of the data use(s),negotiating a “fee” for the data exchange, or
solving disputes.

–

Leverage individuals’ personal data for social
impact, such as to contribute to academic orscientific research.

–

Providing added-value services to participating
members, such as data anonymization and/or
aggregation, benchmarking services, security
and fraud prevention.

–

Acting as a data aggregation and/or
pseudonymization and/or anonymization layer.

–

Acting as a proxy for consent to offer individual
control to the data subject.

If data intermediaries can add so much value, why
are they not used more often? One possible answer
is the complexity of the data value chain within
which date intermediaries operate by definition andthe policy environment surrounding both it and thedata ecosystem as a whole.

Advancing Digital Agency: The Power of Data Intermediaries

101.3 Exploring data value chains
The data ecosystem versus the data value chain
In describing the difference between the data
ecosystem and a data value chain, the former
might be termed as all data, all transactions andthe global space within which data exists and isprocessed, whereas the latter is a value chain ofsorts. Data exists in the data ecosystem by default,
but once data is collected and processed it enters adata value chain and that value chain is as long andas infinite as the life of the data.
Open Data Watch’s data value chain model below
describes the four major stages of the life cycle ofdata: collection, publication, uptake and impact. In
addition, as data is an infinite resource and (absent
external constraints) can be reused infinite times in

FIGURE 1

infinite ways, the model also contains a feedback
loop. This feedback loop is something everyone
is familiar with: it is the means by which functional
data sharing takes place and how technology
knows what to serve back. It has implications
for online advertising, profiling and, taken to theextreme, is key to dark patterns (which combine
heretofore disparate data sets for purposes ofmanipulating the user in a non-transparent manner).
But importantly, without this feedback loop it would
be impossible for people to interact with today’s
technologies in any meaningful fashion. In otherwords, the feedback loop is a neutral feature of thedata value chain but may be open to manipulation.
Disposing of data closes the feedback loop.13

Open Data Watch’s Data Value Chain14

Identify

AnalyseConnect

Use

Collect

ReleaseIncentivize

ChangeProcess

Disseminate

Influence

Reuse

Feedback

Production use – increasing value of data

Collection

Publication

UptakeImpactFeedback

Advancing Digital Agency: The Power of Data Intermediaries

11Beyond notice & consent: How a data intermediary
alters the flow of data in a data value chain
Once automateddecision-making
starts to occur, atype of synthetic
data precedentarises. This meansthat a data-use
pattern emergesthat infers further
use cases.

Introducing a data intermediary into the data value
chain can fundamentally alter the flow of data inthe transaction by disrupting at least one pointin the chain.

digital identity interacted with relevant scenarios
those preferences and permissioning could betaken forward by a data intermediary to conduct
brand new transactions. The value of this is thatthe person does not need to be asked morethan once what their preferences are; but anobvious downside is that the use cases may
be very different from each other and consent
is being inferred, which may reduce individual
agency and lead to unintended outcomes.

Under the notice and consent model, a person
consents to the collection and processing of theirdata at the very beginning of the data value chain.
The data then flows through the data value chain,guided by the permissions set before the data
entered the chain.

4. Automated decision-making by a digital agent:In this scenario a data intermediary digital agent
takes on the role of decision-maker. Consent is
automated as before but this time using AI thedata intermediary agent decides autonomously
what kind of data permissioning a person might
like. This opens the door to even more possible
uses of that data. This type of scenario disrupts
the normal flow of data in the data value chain
at all stages and again can carry both wonderful
opportunities and considerable risks. The key tosuccess here lies in the quality of the automateddecision-making and the underlying algorithm.

A data intermediary could alter this process inseveral fundamental ways. If the purpose of a dataintermediary is to effectively accompany personal
data by adding a layer of permissioning onto theaccompanying metadata (or use metadata as aproxy), that permissioning effectively follows thedata (technically it acts to determine the use of
the data) throughout the entirety of the data value
chain and will trigger changes on a case-by-casebasis depending on what the permissioning allows
for. A similar model is in use in permissioned andpermissionless blockchains.
Below are some different variations ofpermissioning scenarios in the data value
chain using data intermediaries:
1. Notice & consent: This is the default state
whereby people consent to the collection
and processing of personal data. There arealternative lawful bases for data collection andprocessing but in all cases a pre-determination
is made that the data can lawfully enter thedata value chain.
2. Transferred permissioning: The dataintermediary could take the data into abrand-new data value chain by relying on thepermissions from previous unrelated incidents
of data collection and processing by the same
person. This alters the collection phase of thedata value chain (identify, collect, process) byleapfrogging past specific notice and consent.
3. Pre-permissioning using digital identity:
This mimics transferred permissioning above,
except now the power of digital identity is
introduced. For example, if someone’s digital
identity stored their general preferences for datacollection and processing, then any time that

5. Replenishing and automating across multiple
data value chains: Once automated decisionmaking starts to occur, a type of synthetic data
precedent arises. This means that a pattern ofdata use emerges that infers further use cases. If
this could be harnessed at a systemic level withappropriate policy safeguards, the data and its
associated permissions could be recycled over
and over and look slightly different every time
but should reflect the preferences of the user.
The move is towards a fully automated systemof personal data collection and processing toovercome notice and consent limitations. Thisis a scary and amazing space and arguably
not so different from a world absent of any
data protection and privacy requirements: thedifference here is that there is a system, ideallywith backstops, designed in a human-centricmanner and therefore retains the preferencesof the user and exerts limits accordingly. In
fact, there is no reason AI agents could not be
programmed to be conservative if that is what isreflective of the user’s preferences. In addition,such a system would require clear rules to avoid aconflict of interest on the part of the digital agent.

Important note on best practice
When it comes to personal data, most dataprotection and privacy regimes do not currently
allow for many of the above scenarios. In mostjurisdictions that use the notice and consent model,
consent needs to be specific and meaningfulin order for the data to be considered to havebeen lawfully obtained. Best practice for now istherefore to avoid inferring consent where it is

not explicitly and meaningfully given, regardlessof the jurisdiction. Notwithstanding that otherlawful grounds for the processing of personal data
already exist beyond notice and consent, this paper
looks at what the appropriate data intermediary
backstops would need to be in order to make theabove a reality. Inherent in this is the use of bothpublic and private policy levers.

Advancing Digital Agency: The Power of Data Intermediaries

122

The opportunity:
Trustworthy
human-centric
data intermediaries
Some common features emerge that start
to build out conditions for the third-party
intermediary being independent, having a set ofduties in their performance, being a dedicatedasset and with clear rules of the game.

Advancing Digital Agency: The Power of Data Intermediaries

132.1 Data intermediary organizational models
For human-computer interaction, researchers havedeveloped a definition of online trust as an evolutionof its offline counterpart. In the real world, “trust is
the social capital that can create cooperation andcoordination.”15 In the cyberworld, trust becomes“an attitude of confident expectation in an online
situation of risk that one’s vulnerabilities will not be
exploited.”16 This is at the core of the confusion ofcurrent human–technology interaction, where datacollection is so ubiquitous as to make people feel atrisk of being vulnerable. To solve this, intermediary
third parties can be helpful.

manner to a data steward and other related
fiduciaries. Much as a doctor is charged withtaking care of patient health or a lawyer withlegal affairs, the digital fiduciary is responsible
for assisting individual clients in managing theirdigital selves. At a minimum, this means thata digital fiduciary upholds its duty of care bydoing no harm to its clients and upholds its
duty of loyalty by not having any conflicts ofinterest. Under a more expansive definition,a digital fiduciary upholds its duty of care byprotecting and enhancing the individual’s digital
experiences and upholds its duty of loyalty byactively promoting the individual’s interest.20 The
digital fiduciary can be an individual or an entity,a private or public (governmental) body and, if
private, a for-profit or not-for-profit enterprise.

Much can be learned from data intermediarymodels that are already in use in commercial
and academic spheres today, whether theyshare personal data or not. The section below
examines some of the most relevant and trusted
data intermediary models already in existenceat the B2B level.
–

Data stewards
Organizational leaders such as the chief data
officer may hold a designated data steward role,or teams may be empowered to ensure thatdata is leveraged in a responsible way. The data
steward’s role is to manage data rights and datareuse, identifying opportunities for productive
cross-sector collaboration and responding
proactively to external requests for functional
access to data, insights or expertise. Stewards
are active in both the public and private
sector, promoting trust within and outside theirorganization on how data is being used. In
some cases, the data steward can be an entitywith duties to carry out the interests of a groupof data rights holders, a community,17 or theentity holding the data.

The data steward
can both lead
responsible data
management within
their organizationand increase
the trustworthy
perception of theirsector and facilitate
new relationships.

To establish and demonstrate theirtrustworthiness, data stewards may takeon a professional role, including verifiableethics obligations or certification.18,19 Outsideorganizations must always perceive thedata steward as trustworthy. In the case ofB2G data sharing, the data steward could
even facilitate relationships between theprivate and public sector. Thus, the data
steward can both lead responsible data
management within their organization andincrease the trustworthy perception of theirsector and facilitate new relationships.
–

Fiduciary duties can be defined, implemented
and enforced in a variety of ways, including
via: a new legal framework, existing contract
law, voluntary certification, or a professional
association with licensing and related assurance
infrastructure (like for physicians or lawyers).

Digital fiduciary
A digital fiduciary takes on the mantle of duties
of care and loyalty but in a somewhat different–

Data trust
A data trust is a repeatable framework ofagreements based on trust or contract law,allowing data rights holders to delegate controlof their data to a trustee.
If the data trust employs trust law, the trustee isbound by fiduciary duties of loyalty and care toact in the interest of the beneficiary. The trust
pools individuals’ power and provides an agent
to negotiate their interests, suited to managing
individuals’ asymmetric relationships withcompanies in a complex technical environment.
Upholding duties of loyalty requires the datatrust to be independent and may preclude thedata trust from being a for-profit company.
Although trust law does not exist in all countries,
fiduciary duties are more common globally.21
A data trust can be designed for different
levels of beneficiary participation, delegating
various degrees of decision-making power tothe trustee.22 A data trust contract then is “acontract among one or more controllers of data(the ‘entrusters’) and a third party under which
the entrusters empower the third party (the‘data trustee’) to make certain decisions about
use or onward supply of data (the ‘entrusted
data’) on their behalf, in the furtherance ofstated purposes that may benefit the entrusters
or a wider group of stakeholders (suchentrusters or stakeholders being referred to as
the ‘beneficiaries’).”23

Advancing Digital Agency: The Power of Data Intermediaries

14

–

–

Data collaborative
A data collaborative is a data sharing relationshipthat can take multiple forms, including public
interfaces, a trusted intermediary, data pooling,
research and analysis partnerships, prizes andchallenges, and intelligence generation. In a
relationship between organizations of different
sectors, the data collaborative allows for one ormore parties’ data, insights, models or expertiseto be shared.24 A data collaborative encourages
data sharing by enabling public interest use ofpreviously siloed data. While the sharing could be
multidirectional between multiple varying parties,
data collaboratives most often refer to private
sector entities sharing data with the public sector
or with public interest groups. Incentives forcorporations to share data include reciprocity
in data access, research insights, reputation,
revenue through data collaborative agreements,
regulatory compliance or philanthropy andcorporate social responsibility (CSR), or
environmental social and governance (ESG).

–

Data commons
A data commons is a network of relationships
between data rights holders who have equal
rights to a common, indivisible data resource.
The structure follows Elinor Ostrom’s eight
principles for governing commons,27 as follows:
1. Boundaries of users and resource are clear
2. Congruence between benefits and costs
3. Users had procedures for making own rules
4. Regular monitoring of users andresource conditions
5. Graduated sanctions
6. Conflict resolution mechanisms
7. Minimal recognition of rights by government

Data cooperative
A data cooperative is a network of agreements
between peers with mutual interests, allowing
data resources to be pooled.25 Members bringin data and are responsible for stewarding thedata. Data is brought and removed as members
join and leave.26

8. Nested enterprises
The data is an undivided resource and members
have equal rights to the data; thus, the dataremains unchanged despite members joining
and leaving.28

Advancing Digital Agency: The Power of Data Intermediaries

15

Public versus private models
Can a dataintermediary be
truly independent,
especially in
relation to theservices it may
offer and thefinancial incentive
to perform?

Some common features emerge that start to buildout conditions for the third-party intermediary
being independent, having a set of duties intheir performance, being a dedicated asset andwith clear rules of the game. Considering thedifference also in various duties of care from model
to model, does it make a difference whether theintermediary is public or private in nature? Can adata intermediary be truly independent, especially in
relation to the services it may offer and the financial
incentive to perform? The following section explores
some further characteristic options, especially as
they relate to human–technology interaction and thecollection and processing of personal data.
–

data architecture and data standards for which
all organizations would be required to comply.
This will require deep expertise in privacy, data
and technology, and therefore upskilling of thestaff and/or hiring of a “data steward” with therequired skillsets.
However, whether a public body can be said
to be “trusted” will be dependent on the roleof government in any given country, its levelof control, access and use of surveillancelaws and related technologies. Although asuper-intermediary may enable vast sharingof data between multiple participants,
enabling economies of scale and a consistentinteroperable approach even across borders,
if there is no trust in the system, in thegovernment and its underlying intentions, there
may not be active use, unless under the force oflaw. This would then impact the veracity of data
being shared and could in turn stifle innovation.

Public data intermediaries
A public body or government agency could
take on the role of an intermediary, especiallyas it relates to data coming from public bodies.
Therefore, it can also act as an aggregatoror gateway for such information. Such anintermediary could play an even greater rolein making the data more easily accessible,
identifiable, searchable and usable, including
coordinating interoperable systems, especiallyacross the public sector at least. Therefore, therole of a public body is arguably greater if it is anaggregator of multiple sources of public data.
Another role it could play is to act as a superintermediary, setting the national standard,–

Private for-profit data intermediaries
Whether and how a for-profit commercial
entity can successfully serve its clientele undervoluntary fiduciary duties of care and loyalty
remain open to debate among stakeholders.29
A key driver of the success of this model is how
the intermediary derives economic value to beable to perform and make this service available.

Advancing Digital Agency: The Power of Data Intermediaries

16Without strict controls on the access, use andtransfer of the underlying data provided bydata ecosystem participants, this model could
incentivize the intermediary to examine ways
to profit from the data itself, unless prohibitedby law or contractual arrangements. Where aparticipation fee may not generate sufficientprofit, the provision of additional services
could satisfy the economic argument without
requiring any service that involves or enables
the intermediary to profit from the data itself,
directly or indirectly. A hybrid of this approachand variation of cost models could bridge thisissue. Various models could also co-exist, witha certification or trust mark for those that abide
by certain agreed standards. On the other hand,

however, is an immense opportunity for themost responsible organizations that could be
incentivized to create or pay a trusted third-party
intermediary to increase their independence andtransparency with respect to their user base andthus commercial appeal with respect to offering
services to their users.
–

Non-profit data intermediaries
A non-profit data intermediary will need tobe economically viable to exist and coverongoing costs. An independent nonprofit intermediary may be preferable asa third-party neutral body, with the usual
caveats of a successful non-profit.

2.2 The policy environment
Governments are starting to pay attention to theidea of trusted intermediary bodies to support data
sharing. The new European Union Data GovernanceAct “aims to foster the availability of data foruse by increasing trust in data intermediaries
and by strengthening data-sharing mechanisms
across the EU.”30 The Government of the United
Kingdom also recently commissioned a report31
on data intermediaries that has determined theycan empower both people and businesses in data
sharing activity. As governments seek to regulate
data sharing, agile, innovative and positive solutions
will be needed.

Governments
are starting to pay
attention to theidea of trusted
intermediarybodies to support
data sharing.

A key question in more broadly actualizing dataintermediaries that can eventually act as digitalagents for people will be the role of assurance
structures in facilitating trustworthiness. Legalframeworks, whether statutory or contractual,
can act as assurances to limit harm to data rights
holders and provide a safer ecosystem for building
trust but are insufficient on their own. Thus, otherforms of assurance, such as professional codes ofconduct, licensing and adherence to social norms,
may be necessary to establish trustworthinessamong intermediaries.
In the area of human–technology interaction, amajority of governments worldwide have alreadyestablished baseline data protection and privacy
requirements, even if there are differences between
jurisdictions. Some governments are now also
regulating automated decision-making via AI
legislation. There is also much to be learned fromparallel policy areas beyond data protection
and privacy:–

Human rights law – Data intermediaries in
Europe must comply with human rights law(e.g. European Union Charter of Fundamental
Rights), for example by ensuring dataintermediary services do not result in unfair
bias and discrimination–

Antitrust and competition law – The dataintermediary could not be used as a vehicle toshare or disclose materially sensitive information
between competitors. On the other hand, dataintermediaries could serve as effective antitrust
remedies to address market failures andincumbent platform companies.

–

Intellectual property law – The dataintermediary could protect the trade
secrets and intellectual property rightsof data sharing participants–

Data localization requirements – The dataintermediary may need to process/store certain
types of data “on soil”, meaning within acountry/region (e.g. Russia, China)

Driven by the recognition of the importance of thedata economy, it is clear that many governments
understand the significance of making data available
for innovation; at the same time, policy ambitions topromote data sharing are coming to light. However,
because that often involves the sharing of personaldata, data protection and privacy issues continue tobe important. But data protection and privacy arehighly evolved areas of policy-making, so it will beinteresting to see how policy in the area of trusted dataintermediaries evolves to take account of this tension.

Advancing Digital Agency: The Power of Data Intermediaries

172.3 Human-centricity and fiduciary duty
What might creating safeguards for data intermediaries
look like in reality? Two complementary concepts cometo the fore: human-centricity and fiduciary duty.

Human-centricity“Human-centricity means focussing on
something variously called (self-)sovereignty, selfdetermination, self-governance, autonomy, agency
or the like, in terms of the people involved with thegeneration of data. These concepts derive fromthe internationally-recognized concepts of humanrights. A human-centric approach is one thatmakes central the following: that people have theright to determine, without any kind of coercion orcompulsion, what happens to them.”32

Autonomy and agency are core tenets of humancentricity and fit in with the aims of restoring
trust to human–technology interaction. Humancentric design is a well-researched and used
space but human-centricity has typically takena backseat to a rights-based approach when it
comes to data protection and privacy norms,
especially when it comes to regulation.

Fiduciary duty
A more highly developed area of consideration
is fiduciary duty. A fiduciary typically abides by
two basic types of duties: care and loyalty.
In turn, these can be further subdivided into four
specific duties:–

The fiduciary duty of care = act prudently
towards the entrustor–

The “thin” fiduciary duty of loyalty = have noconflicts of interest between duties and clients––

The “thick” fiduciary duty of loyalty = promote
the entrustor’s best interests.

The general tort-like duty of care = do no harm
to others

Advancing Digital Agency: The Power of Data Intermediaries

18

Importantly, because fiduciary duties are
considered relational, they run not with property
but with the person and their entrusted confidence.
While those are primary duties, others also havebeen recognized.33 These include confidentiality(keeping confidences shared during the courseof the fiduciary relationship) and good faith (acatch-all for having the right intentions).34 Unlike
a contract, a fiduciary duty could foreseeably be
perpetual in nature, as in the case of lawyers anddoctors whose fiduciary duty continues even after
the contract ends.

BOX 2

The law of fiduciaries does not exhaust thecommon law as a rich source of rights andresponsibilities. Other potential common lawbased sources of intermediary duties/rights
include torts, bailment and misappropriation.
Indeed, a policy framework that matches
the duties to the specific digital concern
being addressed can be envisioned.
One approach is to conceive of the responsible
and trustworthy data intermediaries desired in thedata ecosystem – or at least the person at thedata intermediary responsible for trustworthy dataprocessing – as having the role of “data stewards”.

Liability: A tricky question
By managing collectively massive amounts ofdata originating from many data sources, datatrusts are not in a position to assess the legalityof all the uses of the data that are made. They areconsequently exposed to liability risks in a waythat can be compared to the liability of other online
platforms for the illegal content that they contributeto sharing.
The risk of liability of data trusts could further
be managed by designing appropriate dispute
resolution mechanisms that shall apply in case oflegal disputes affecting data trusts. It is essential toensure that the complex disputes that may arise inconnection with the use of data in the context ofdata trusts (e.g. misappropriation of data, loss ofdata, access to data vs protection of confidentiality)
and that may involve multiple parties (data holders,data trusts and data users) shall be solved in a
cost-efficient and coordinated manner. This could

be done by creating dedicated global alternative
dispute resolution mechanisms (including arbitral
tribunals) that would be better equipped –compared to national courts or national regulatory
bodies35 – to solve “data disputes” (i.e., disputes
about the use of data).36 Multi-territorial alternative
dispute resolution systems would make it possible
to avoid the geographic fragmentation that would
result from (parallel) national court litigation/national regulatory proceedings. Alternative
dispute resolution mechanisms consequently offera most convenient and attractive tool to address
the challenges of what has been called “massive
online micro-justice”37 (i.e. the challenges resulting
from the need to manage a multitude of small(micro) disputes, as is done in the digital online
environment with respect to content moderation
on digital platforms).38 Proposals have been madeto set up specific dispute settlement mechanisms,
including dispute review boards.39

Advancing towards Digital Agency: The Role of Trusted Data Intermediaries

193

Moving towards
trusted digital agency
Digital agents may negotiate access todata above and beyond a simple binary
gated function.

Advancing Digital Agency: The Power of Data Intermediaries203.1 The role of digital identity
in supporting human agency
Can the use of data intermediaries establish anotion of sort of “digital self-determination40” by
helping people navigate technologies and data
ecosystem models without losing sight of what
it means to be human, in terms of agency andexpectations? Our digital identities
may hold the key to allowing us todetermine how we can start to navigate
the data ecosystem around us in a moresophisticated manner.

Digital identity
A digital ID is the electronic equivalent of anindividual’s identity card. It is a way to provide
verified personally identifying information of anindividual for a software to read and process. Bothonline and offline environments can adopt digital
identity. And it can also act as a key by storing anddeploying permission.

specific purpose. Some of the biometric based
digital ID systems have already been adopted infinancial transactions and for a cash-free shopping
experience. Such authentication and authorization
processes can be completed in real time and freeof hassle.

Carefully designed and properly managed, digital ID
can also enhance privacy protection and reduce therise of identity fraud since each time only minimum
information is needed for authentication for theGood digital identity has five key components as
defined by a multistakeholder group curated by theWorld Economic Forum: useful, inclusive, secure,offers choice, fit for purpose.41 Figure 2 shows theimportance of Identity in everyday lives.

Advancing Digital Agency: The Power of Data Intermediaries

21

FIGURE 2

Identity in everyday lives

Healthcare
For users to access insurance, treatment; tomonitor health devices, wearables; for careproviders to demonstrate their qualifications

Telecommunications
Financial services

To monitor devices andsensors transmitting data suchas energy usage, air quality,
traffic congestion

To open bank accounts, carryout online financial transactions

Food and sustainability

Telecommunications

For farmers and consumers
to verify provenance of
produce, to enhance value andtraceability in supply chains

For users to own and use
devices; for service providers
to monitor devices and data on
the network

Digitalidentity
Entities

PeopleDevicesThingsTravel and mobility

E-government
For citizens to access and use
services – file taxes, vote,collect benefits

To book trips, to go throughborder control between
countries or regions

Social platforms

Humanitarian response

For social interactions; toaccess third-party services that
rely on social media logins

To access services, todemonstrate qualifications
to work in a foreign country

E-commerce
To shop; to conduct business
transactions and secure payments
Source: World Economic Forum, 2018, Identity in a Digital World A new chapter in the social contract.

BOX 3

Digital identity has an evolving scope42
Authentication: Processes that determine if
authenticators used (e.g. fingerprints, passwords)
to claim an identity are valid. Sometimes
digital identity goes beyond authentication.
Authentication is a security process thatcompares attributes to confirm a claim. In
principle, there is no need to know who theperson is. In digital identity, there may be aneed to link the person to their identity and that
may require identity verification technologies.

Profile: May include inherent data attributes (suchas biometrics) or assigned attributes (such as
names or national identifier numbers).
History: Credit or medical histories, online
purchasing behaviours.
Inferences: Judgements or decisions made basedon authentication processes, profiles and histories(e.g. a bank decides the attractiveness of anindividual for a loan).

Advancing Digital Agency: The Power of Data Intermediaries

22

Individuals can already use decentralized
identity solutions, for example, personal dataservers to import their personal data andon-device data storage, from banking andhealthcare information to social media data,

TA B L E 1

Digital ID

Characteristics

Evolutions in digital identity solutions and how they can help

Now

Evolution

FutureConsent

Shift control to user

AgencyTraditional intermediaries
and user consent (e.g. webbrowsers, apps, mobile devices)

Personal data stores, ondevice data storage and moreadvanced data intermediaries(e.g. smart devices, agents)

Next level of data intermediaries(embedded in body, devices,
homes, cities, etc.)–

Focus on Verified Attributes(address, age, health status)

–

–

–

Governance: centralized,
distributed, federated

A fundamental level of
ID proofing and verified
attributes remains (I am
really who I say I am)–

Looser data stores (e.g.
profile built by larger techcompanies, by browsers)–

Focus shifts from only
verified attributes andcredentials to profiles andinferences about a person–

Fluid boundaries between
data stores, agentsand data managed on
individual’s behalf–

Evolving definitionof control/agency–

Needs scalable user
agency concepts––

Self-declared attributes (e.g.
social media login)–

Policyconsiderations

and use them directly for identity authenticationand data access authorization with apps andwebsites.43 This technology can empowerusers to take control of their personal
information, increasing data portability.

–

Data protection and privacy–

Security requirements–

Data minimization–

Certification ofissuers, verifiersMore collaborative digital
ID approaches (within
sectors, e.g. health,banking; at national levels,
e.g. across borders; orat regional levels, e.g.
travel corridors, trust):
Personal data stores(e.g. Digi.Me) focusing on
consumer to business (C2B)
and user control, reducing
need for business-tobusiness (B2B) interactions
User-driven web (e.g. Solid
project) and embedding
digital ID into the web
experience–

Query-based ID (e.g.
Demos UK), avoiding dataexchange, just answer
queries “are you over 18?”,“are you vaccinated”, etc.?

–

Credential interoperability(technical, legal levels)–

Legal acceptanceof digital ID––

Trust frameworks linked
to attributes, exchangeof credentials
Recourse and liability

Create definitions andthresholds of ownership,delegation, liability
Prescribe transparency,
auditability, predictability
Allow for scalable (rulebased vs granular per
data items) approaches toscope of data agency
Create sandboxes
for experimentation

Advancing Digital Agency: The Power of Data Intermediaries

23How digital identity helps solve decision fatigue and improvedata sharing potential in human–technology interaction
Digital identity can allow for the selection ofpreferences and the making of certain choices inadvance, such as “pre-consent”, avoiding doublingof efforts. This already happens in device usage:
when setting up a new phone, for example, users
can predetermine privacy settings before using any
app. Their identity is usually inherently connected totheir devices. Similarly, through the use of cookies,
browsers can remember which user is which
through a set of identifiers.

BOX 4

Digital identity then can be the key to unlocking
a less ethically concerning but arguably equally
impactful scenario as an AI-enabled digital agent.
Digital identity allows the digital agent to recognizethat the data belongs to a specific user and consult
the permissions that that user has authorized(effectively data processing scenarios that the user
has pre-consented to) and act accordingly in linewith the user’s wishes. Crucially, consent can begiven in advance for a myriad of use cases and thatconsent can be attached to the user’s digital ID.

Vaccine passports
The COVID 19 pandemic has led to a heightened
focus on the power of medical data, specificallyso-called vaccine passports. These passports
by nature serve as a form of digital identity.
Commercial entities serve as a type of centralized
data intermediary in several jurisdictions. Given
the sensitivity of this type of health data, in manycases governments have procured third-party
contractors to administer and manage such
systems. Unsurprisingly, strict security and privacy
criteria are central to such systems in most cases,
not least because a public policy health concern
relies on increasing trust in the system.
Such vaccine passports are used when travelling
between jurisdictions and at a local level, suchas when entering dining establishments orother places where proof of vaccination status
is necessary. Importantly, these intermediaries
provide a means of verifying status without sharing

health data with the establishment per se, in asort of zero-knowledge proof scenario whereby
the trusted data intermediary verifies that thedata subject is vaccinated but does not shareany other information. This avoids unwanted
secondary effects of the establishment sharing
the data any further.
However, at a collective level, vaccine data is anincredible public health asset. The United Kingdom
Government in particular has acknowledged
this44 and has suggested that anonymization,
pseudonymization and data shielding techniques
could be harnessed in a controlled environment toallow for the reuse of that highly sensitive data. In
such cases, notice and consent is not required per
se for the reuse of the data but the intermediary
processes the data undergoes must be done in acontrolled environment so that the findings of thedata set are made available rather than the data itself.

Advancing Digital Agency: The Power of Data Intermediaries243.2 Automated decision-making
Machine decisions vs human decisions
To automate the data intermediary process there
are some additional concerns about machine
decision-making that people may inherently distrust
due to the machine’s lack of empathy.45 In addition,
as well as perceived harm, as the Future of Privacy
Forum points out, harms associated with automaticalgorithmic decision-making can vary.46
So how to instil trust? It comes down to backstopsof governance including provisions for recourse andmechanisms for redress. The rules of a banking
transaction – the execution of standardized andconsistent behaviour throughout the transaction –acts as a de facto data intermediary because
the data is handled through a specific processwith rigorous backstops. This example plays out
especially in the payments industry, where people
rely on trusted third-party technology to handle

BOX 5

money and the data that represents the value ofthat money. Nowhere is this truer than in blockchain
technology and cryptocurrency, where the value of
assets is intangible and inherently and inextricably
fully dependent on trusted data.
Many different technologies could potentially servea role as an intermediary; but some of the mostinteresting and relevant are those acting as software
agents. A software agent is defined by four key
hallmarks: autonomy, social ability, responsivenessand proactiveness.47
Excitingly, digital agents may negotiate accessto data above and beyond a simple binary gatedfunction. Using sophisticated algorithms may allow for
decisions that emulate agency and autonomy in as
close a way to human decision-making as possible.

The four key hallmarks of a software agent48
Autonomy: Agents should be able to perform the
majority of their problem-solving tasks without
the direct intervention of humans or other agents;
and they should have a degree of control overtheir own actions and their own internal state.

Responsiveness: Agents should perceive theirenvironment (which may be the physical world,a user, a collection of agents, the internet, etc.)
and respond in a timely fashion to changes that
occur in it.

Social ability: Agents should be able to interact,when they deem appropriate, with other software
agents and humans in order to complete theirown problem solving and to help others with theiractivities where appropriate.

Proactiveness: Agents should not simply act
in response to their environment; they shouldbe able to exhibit opportunistic, goal-directedbehaviour and take the initiative where appropriate.

Advancing Digital Agency: The Power of Data Intermediaries25

3.3 A potential trusted digital agency model
In order to be truly at the service of the individual,
a trusted digital agent (TDA) that automates
permissions for people and effectively manages

CASE STUDY

their data across different services needs to respecta certain number of rules. Below is an outline of a
prototype concept of how such a TDA might work.

Meet Valexander, a TDA
Rules of the game for Valexander, a friendly,
trustworthy TDA–

The TDA should therefore be able toperform a basic check that complianceexists before any data sharing occurs, withthe caveat that a verifiable third party likely
conducted the compliance itself.

–

Such checks could be traced using smart
contracts on the chain, for instance.

–

TDAs should have contracts with people
guaranteeing it serves their best interests.

The TDA will base its decisions mostly upon:–

Previous consents and preferences of theperson, as well as the full context of suchconsents (who, what, when, why, etc.).

–

Previous consents and preferences of the large
amount of people that agent serves.

–

Information about the person (age, gender,
objectives, etc.).

–

Information about the services it exchanges
data to and from:–Nature of the service–

Type of organization–

Business model–

What data is needed by the service when
and why.

–

Such a TDA needs to guarantee:––

Neutrality on the services it recommends––

The TDA needs to be able to explain why
it shared data with one service and notwith another.

–It needs to be able to list the criteria it
based its decisions on.

–

While this is not always entirely possible
with machine learning/deep learning (ML/DL) technologies, inputs need to be clear
and explainable and there needs to beaccountability of the TDA.

Human interaction for some data sharing–

The business model of the TDA should notdepend on the services it shares data to
and from in order to guarantee its neutrality.
––

Auditability, explainability of its processes

On some sensitive or crucial data sharing(regarding the type of data or type ofprocessing that will occur), the person
needs to validate the data sharing.

Accuracy of the data shared

Compliance for data sharing–

Data sharing needs to be compliant withregulation, sectoral rules, contracts andgovernance frameworks.

–

While the TDA may perform basic
compliance checks, it is unlikely to be able
to conduct full-fledged compliance reviews.
For instance, for personal data to be sharedlawfully under the General Data Protection
Regulation (GDPR), the data must havebeen collected lawfully in the first place (bythe data provider) and the data may not
be used for incompatible purposes (by thedata user). This is a complex area and mustbe nuanced, so the TDA is best seen as
supplementary to compliance itself.

––

Since, for instance, the TDA will allow
people to easily keep their profiles up todate, it needs to make sure data shared isalways accurate and up to date or provide
some grade on the accuracy of the data.

–

This will be possible when the data provider
is the data holder/subject but less so when
the data provider is an organization.

Interoperability with other TDAs–

People need to be able to easily change
TDAs without losing their preferences,
just as it is possible to change telecom
providers without losing the number.

Advancing Digital Agency: The Power of Data Intermediaries

26

To enable this, governance is needed. This
governance is larger than the TDA or theorganization that develops it. It includes the person
and the public and private organizations that forma legitimate and representative alliance to makesuch decisions (public-private-people partnership).

–Governance rules, standard contracts andagreements for TDAs–

How consents and preferences are stored–

Interoperability standards of the TDAs

Possible suggestions to ensure good governanceof TDAs:–

Certifications for TDAs–

Business models of TDAs guaranteeing
neutrality of TDAs for the digital services–

The public information about the digital
services the TDA will share data to and from:–

What data is needed, when it is needed,
why does each service need it and what isthe business model?

–

TDAs could be registered at the appropriate
authority and precise requirements
should be installed, as well as audits
and certifications.

–

TDAs could be interoperable and rely on
open standards. Non-compliance should be
fined and prosecuted. Liabilities should beclear for the organization developing the TDA.

–

TDAs should be neutral and independent
in regard to the digital services that will use
the person’s data, in order to prevent any
conflict of interest and ensure the TDAs only
serve the interests of the person.

–

How is that information described andprovided? For instance, for the healthsector there should be a registry so that
health services (public and private) registerthat information.

–

The person can manage and decide its
preferences on the data, reset any profile
the TDA is supposed to use, and needs tobe able to reverse an automatic decision
made by the TDA or made in consequenceof the TDA’s decision.

–

This will guarantee fair access to data about
the services needed by TDAs, explainabilityof the TDA’s decision and foster competition
among TDAs.

––

Governance structures (public-privatepeople partnerships) need to be mandated
or created to decide and standardize:

It is essential to ensure a person can change their
TDA and that there is competition among TDAs:––

When human interaction is necessary–

The automatic decisions that can bereversed and how

People can easily switch from one TDA
to another without losing their preferences
or profile. TDAs can differentiate on thequality of their AI but not on the data
they access about the person or about
the services.

In the case of a sophisticated approach like the one
above, TDA interoperability must be mandatory inorder for this system to function. But Valexander
is just one example: this paper’s role is to unearth

the opportunities and risks of TDAs as the world
moves towards trusted digital agency that is not justinteresting from a technical and policy perspective
but may become essential in one form or another.

Advancing Digital Agency: The Power of Data Intermediaries

27

4

Reshaping humantechnology interaction
The use of a data intermediary to
overcome the limitations of notice andconsent does not do away with the corecomponents of notice and consent but
merely displaces them.

Advancing Digital Agency: The Power of Data Intermediaries28

4.1 How the use of data intermediaries
shapes human–technology interaction
The systemshould beaccessible,
interrogable,
intelligible andcontrollable.

Designing for online interfaces and interactions
relies upon existing heuristics. Such heuristics
have remained largely unchallenged despite
developments in both the underpinning businessmodels of online platforms and data protection
law. Even when designing to support user consent,
the rule of minimal distraction (that a designer
should seek to ensure the user is not distracted or
noticeably redirected from their principal activity/goal) remains a tenet.49 However, when the locus
of consent is distributed or redirected, as in thecase of data intermediaries, this then requires
substantial rethinking of how to approach thedesign of such interactions. At its most basic, apriori consent requires that the user be cognizantof the transaction, informed of its implications,and capable of agreeing to the terms.

intended to reduce the overarching issues into
three principles: agency, legibility and negotiability.51
HDI pushes individuals beyond user awarenessand control, extending this to include questions
over how a user might interrogate the system inorder to support their understanding and then how
the user might allow the system to exert control
over how their data is used. Arguably, even if adata intermediary distributes consent, the user
should still be unsurprised by what happens, beable to interrogate the model, and have the tools
available that allow them to act, if they so choose.
So, the system should be accessible, interrogable,
intelligible and controllable.

One might assume that if a data intermediaryis sought, then this is a voluntary choice (andultimately revocable); therefore, the moral role ofinteraction designers is not to replicate consent
but simply to scaffold understanding and promoteagency,50 so as to ensure that any signal of assent
is sufficiently supported. This notion of informationalsufficiency is highly contextual but broadly includes:(a) how much a user should understand and thepresentation of this information; (b) what aspectsof the system or the data transfers should behighlighted/brought to the surface and how/when
this might occur; and (c) when and how to alert
users to changes in system state. Another way toconsider this is to first ask: “How much do I needto know to ensure I am neither surprised nor upset
by the use of my data?” The second question to
ask is: “How soon, and in what way, would I wish toknow this?”Another way to look at this issue is through humandata interaction (HDI), a normative framework

Finally, the use of a data intermediary, to overcome
the limitations of notice and consent, does not
do away with the core components of notice andconsent but merely displaces them. Informing,
agency and revocation (awareness and control)
are still central to the functioning of an effective
intermediary. Equally, agreeing to trust such asystem with data requires a priori assent but withthe additional burden of informational sufficiency,
as with any software product. However, given
the normative nature of such a system, it isalso necessary to consider how to design the
onboarding/assent process to be one more akin toan engagement with any offline intermediary. While
such relationships are notoriously difficult to modelthrough systems design, one interesting concept
is that of building in latency, or the affordance ofdelay, in the law and the design of computational
systems.52And the “ongoing pursuit of seamlessuser experiences forecloses opportunities forengagement with the text, meaningful reflection,
suspicion and interrogation, thereby limiting
agency and autonomy,”53 raising the importanceof building moments of latency into interaction
design, particularly in the build-up to assent.

Advancing Digital Agency: The Power of Data Intermediaries29

4.2 User experience design consequencesof using a third-party digital agent
The design for which a digital agent framework
becomes universally accessible and desirable
must follow a traditional approach to achievingease of use. To a greater degree when dealing
with digital identity and personal data, there exists
a challenge of trust and participation, whichmakes it vital to achieve a low rate of attrition.

Inclusive: A universal, non-discriminatory andaccessible tool that allows ease of use and inhibits
exclusion, and whose design prevents surveillance.

Beginning with the user, there must be a highdegree of individual control and open knowledge
developed into the framework to ease concerns ofsurveillance, misuse and security vulnerabilities.

Choice: A user-centric and usermanaged design where alternatives areprovided through informed consent.

Secure: A trusted and open framework that is
auditable and designed with a dashboard thatprovides notifications of all data access points.

Purpose: The accuracy and sustainability of designthat encourage use across services over time, withpredictable outcomes.

To the first point of surveillance, a data intermediary
could be designed as a pass-through mechanism
without knowledge of the data exchanged, where
no access to the data is required for the service.
Producers of data will be sceptical of each point ofinteraction between producer and consumer, thus
creating a need for open design.
With a blurred reality of liability and consequences fordata misuse, a decentralized exchange system suchas blockchain must be incorporated to enhance
security and limit siloed control. The responsibility ofintermediaries to act on behalf of both parties createsa need to establish well-checked decentralized
transaction and decision-making processes
throughout the entire exchange. Whether government,
enterprise, private company or individual, trust mustbe earned and security proven through the design of aframework that includes the following attributes:
Useful: A portable and responsive design thatfunctions across platforms and is acceptable to lesstech-savvy users.

The EU’s Data Governance Act proposesa framework for the governance of dataintermediaries, including the obligation to haveneutral and independent data intermediaries,
interoperability of data intermediaries, registrationand specific governance organizations.
Initiatives are emerging to unite data intermediaries
and public and private service providers toform such governance organizations and startbuilding those rules for automatic human-centric
data sharing. For example, in the European
Union, aNewGovernance unites leaders of such
TDAs and organizations in the skills (education,
employment, etc.) and mobility sectors. In India,
Sahamati does the same for the banking and thehealthcare sector. Both are producing governancerules and are working on concrete use cases tohelp build such human-centric data networks.

Advancing Digital Agency: The Power of Data Intermediaries

30

5

Levers of action
Having a clear regulatory environment
will serve the users of data intermediaryservices, as they are safeguarded fromrisks associated with them.

Advancing Digital Agency: The Power of Data Intermediaries31

5.1 For governments: Future-proof regulatory support
For entities to use and invest in data intermediaries,
legal certainty is key. But this area is complex.
Having a clear regulatory environment will serve
the users of data intermediary services, as they
are safeguarded from risks associated with them,and the flourishing of the market as a whole,as liability risks will be easier to navigate andcompetition will be rooted in a level playing field.

BOX 6

sharing, although as mentioned earlier, this isshifting quickly.

The demand is there: irrespective of regulatory
gaps, more and more data trust initiatives are
emerging because of their usefulness.54

In contrast, however, there usually is immensepressure on legislators to act in areas where existingdata protection and privacy policy fails as a system,
as in the case of high-profile data breaches. An
example of this is AdTech and the constant opting
in and out via cookie banners, where the European
Parliament now calls for a complete ban of targeted
advertisement in the European Union Digital
Services Act.55

The consensual sharing of data rests on thebalance of incentives (such as for innovation,
profit or philanthropy) and disincentives (suchas privacy concerns and proprietary interests orother disincentives such as external regulatoryintervention). In many cases, regulation intervenes
to bridge this trust gap by demanding a level ofdata protection and privacy be adhered to. Whilethat may tackle disincentives, in most markets
there remains a lack of regulatory support for data

Effective trustworthy data intermediaries, which
opt in or out on behalf of people, might ease thesubjective need for strict legislation in specificindustries and for specific use cases and insteadallow for a more harmonized and holistic approachwith multiple applications. The appeal of TDAs
is that they are similarly simplistic and complex:
when a TDA can navigate any data sharing
scenario, the sky is the limit for the opportunity –and the risk.

Relevant existing and upcoming legislation
Prominent examples of existing or upcoming
legislation concerning data intermediaries:–

European Union GDPR
The European Union General Data
Protection Regulation (GDPR)56 lays down
horizontally applicable rules on the handlingof personal data in the European Union. It
does not have explicit provisions on dataintermediaries and could be amended
to implement a clear and legally secureframework for them.

–

US ACCESS Act
In the United States, the ACCESS Act
of 2019 is the first proposed federal
legislation expressly allowing for end-users
to delegate their data rights to trusted“third party custodians”.57 The proposed billincorporates a general “duty of care” owed

Due to the risks that data intermediaries can poseto fundamental rights – next to their benefits if
implemented correctly – it seems consequent
to explore having certain provisions for dataintermediaries enshrined in law.
–to the custodian’s clients. Importantly, theproposal also requires that large platform
companies provide these custodians withinterconnection and data portability via
transparent and accessible interfaces.58
Such interoperability provisions will be key iftrustworthy data intermediaries are to havea reasonable opportunity to fully represent
the delegated interests of their clients andthereby compete successfully with large
platform companies.

Transparency and neutrality
Transparent data trusts may be more neutralthan others. One way this can be achieved is–European Union Data Governance Act
Chapters 3 and 4 of the European Union
Data Governance Act59 discuss for-profit
and not-for-profit data intermediaries at
length. They comprise obligations suchas that of neutrality of intermediaries andregistration schemes, and establish theconcept of data altruism and standardized
consent forms.

by guaranteeing that the monetization of theservice mainly derives from the managementof the data and possibly the provision ofadded value services and not from using thedata itself. The EU’s Data Governance Act
contains provisions of this nature and echoes
the ePrivacy Directive60 where providers ofelectronic communications services may
transport data but may not harness it for theirown purposes, including commercial use.

Advancing Digital Agency: The Power of Data Intermediaries

32

–

Already provided for under data protection andprivacy legislation, data portability is seldom
supported in reality. To move to a world of trusted
digital agency, data portability must be explicitly
supported in operational terms. One way tomanage data portability is via a data intermediary.
–

To move to aworld of trusted
digital agency,
data portability
must be explicitly
supported inoperational terms.

Human-centricity is a more nuanced concept
based on taking into account the interests ofthe person, their autonomy and their agency.
Human-centric policies will help develop ahuman-centric data ecosystem within whichhuman-centric data intermediaries can survive.

Data portability–

In instances where data is held directlyby the data trust – and not decentralized
and only managed centrally – provisions
in cases of the entity’s insolvency or
liquidation seem advisable.62 This echoes
well-understood security protocols andthe decentralization of servers, as well
as being the premise of decentralized
autonomous organizations (DAOs).

Fiduciary duty vs human-centricity
While imperfect, the fiduciary duties that are
owed to the data subject could be definedin legislation, in particular in markets with noprivacy and data protection law. An example
of such a definition can again be found in theEuropean Union Data Governance Act, whichstates that “the provider offering services todata subjects shall act in the data subjects’ bestinterest when facilitating the exercise of theirrights, in particular by advising data subjects
on potential data uses and standard terms
and conditions attached to such uses”.61 Moregenerally, most privacy and data protection
laws, such as the European Union GDPR,
impose strict obligations on entities handlingpersonal data, whether they act as a data
controller or data processor. However, this may
not be appropriate in all cases, especially where
rights and interests collide or are unknown.

Insolvency–

Access rights of public authorities
Which and to what extent public authorities
such as law enforcement and intelligence
services shall have access to data managed
by data intermediaries is naturally an area ofconflict. This holds particularly true in crossborder cases, as can currently be observedin the ongoing US-European Union conflictover the Privacy Shield, which was recently
struck down by the European Court ofAdvancing Digital Agency: The Power of Data Intermediaries

33

It may be
preferable
to promote
decentralized
models (such as
those in Web 3.0)
that do not rely
on a centralized
database, or data
sharing enabled by
secure application
programming
interfaces that
rely on strong
authentication
methodologies.

Justice because it deemed personal data
not well enough protected from accessfrom US intelligence.63 Data retention andsurveillance are usually matters of national
security and defence; nevertheless, increasedtransparency increases trustworthiness inthe data ecosystem.64 For this reason it may
be suggested that the intermediary enjoy
a carve out requiring a warrant, much like
telephone data in many jurisdictions.
–protection regulator, for example, to deal
with data protection issues in relation tointermediaries, which increases the rightsof the individual. But the business outcome
argument to do this is more persuasive, as astronger regulator, more trust in more sharingof data, and individual rights also increase. In
addition, close collaboration among regulators– across countries and across sectors – would
contribute to more effective enforcement andtherefore further enhance trust in data sharing.

Oversight
Recommendations for the development ofstandardized policies for data intermediaries:

As the inevitable counterpart of every legislative
obligation, appropriate opportunities foroversight need to be guaranteed. This seems
particularly reasonable in relation to data trusts,
where certain risks such as unintended biases
or discrimination would be hard to catch fromthe outside. Under current circumstances,that is likely to be a national regulator or dataprotection authority; but a new model could
emerge, especially if fiduciary duty is required.
Any regulatory framework with a weak regulator
will not incentivize compliance, regardlessof the intensity of the regulation. In addition,
where a regulator also plays a more proactiverole in publishing guidelines, best practice andstandard templates, this will create additional
trust in the knowledge that participants havea verified benchmarked to judge compliance.
There is a balancing act to be struck and it
could be that in those jurisdictions that havea weak regulator, the intermediary model will
follow that same approach. The argument
against this would be strengthening a data–

Sandboxes – It may be worth exploring
how regulatory sandboxes cancontribute to building trust in the data
sharing economy. These sandboxes
would enable data intermediaries andother participants to test new data
sharing projects and technologies ina safe and controlled environment,
while receiving privacy guidance.

–

Security – Where data intermediaries
get access to credentials (e.g. username
and password) or amass vast amounts ofpersonal data or confidential information,
this raises potential security concerns.
It may be preferable to promote
decentralized models (such as those in
Web 3.0) that do not rely on a centralized
database, or data sharing enabled
by secure application programming
interfaces (APIs) that rely on strong
authentication methodologies.

Advancing Digital Agency: The Power of Data Intermediaries

34

–

BOX 7

Liability: Under certain limited
circumstances it may be appropriate toestablish a special regime for reduced
liability for those entities that voluntarily
accept the fiduciary duties of care, loyalty
and confidentiality vis-à-vis their customers
or patrons, and adhere to strict humancentric criteria. These entities would
by design be required to go above andbeyond current legal data protection andprivacy requirements. Recognition ofsuch a status could be geared to sector
co- or self-regulatory measures, such asprofessional codes of conduct or bestpractices, which include robust enforcement
measures to ensure compliance with thespecified fiduciary duties. Such a regime
would need to be tightly controlled to avoid
the circumnavigation of the spirit of dataprotection and privacy laws and avoid
unintended consequences.

–

Delegation: Policy-makers may wish toconsider developing a “right to delegate”
provision in future data protection andprivacy legislation. Such a provision iscontained in the ACCESS Act legislation
currently pending in the US Congress.
To the extent that individuals are granted
certain rights, such as data portability andinteroperability, they also may also be
granted express permission to delegate
those rights to a trusted third party – adata intermediary. This mechanism
would, among other things, prevent
delay or interference with the ability of
individual data subjects to exercise theirrights with the assistance of trustworthy
third parties. Such a provision could be
limited to those entities that can satisfy
specified pre-determined standards andwould also need to be carefully monitored
to avoid unintended consequences.

Cross-border data flows and data transfers
As a consequence of the GDPR’s focus on theprotection of the European Union’s fundamental
right to privacy, it contains a strict purpose
limitation for granting consent, which currently
hinders many use cases of data altruism. Anotherarea with potential is that of cross-border datatransfers: With the right amendments to the law,
could an adequacy decision (Art. 45 GDPR) be
issued in favour of a data trust?
Data intermediaries will need to consider where
they are located, their place of legal establishment,

corporate structure, and independence. They will
also need to consider the impacts of legislative
movements to localize the residency of dataintermediaries and require representatives incountry, among other similar requirements, which
could prejudice those use cases, even whenostensibly motivated to protect personal data.
Finally, it is critical to emphasize the need to enable
and facilitate global data flows while maintaining highstandards for privacy and security, as the free flow ofdata is the backbone of any data sharing economy.

Advancing Digital Agency: The Power of Data Intermediaries35

5.2 For businesses: A policy leadership role
Meanwhile, as useful as regulation is, businesses
also have a role to play in developing responsible
data intermediaries. While some aspects of
how business will ultimately drive the designof digital agents have already been discussed,
responsible businesses may wish to explicitly
consider the following:–

requests for data presents a host of challenges
and implications, especially in light of threetrends: (i) law enforcement and intelligencecommunity responsibilities to safeguard
national interests against domestic andtransnational threats; (ii) increasing restrictions
on cross-border data flows based in part on
concerns with those lawful access/surveillance
responsibilities and authorities; and (iii)increasing desire to localize and tap into data
to develop revolutionary technologies like AI.

Standards
Widespread standards are a precondition for
efficient and well-functioning data intermediarysystems. Standardized machine-readable
formats and communication protocols
allow for the automation of the execution ofservices offered by data intermediaries andthus allow them to scale. The private sector
has a crucial role to play in the adoption ofstandards: what industry as a whole uses
ultimately becomes endorsed at a systemiclevel. A government, in turn, may endorse it
later, either explicitly or implicitly; at the very
least standards are passively tolerated.

–

In addition, the fact that daily lives are
increasingly lived online leads to requests
between private parties to access data via
mechanisms like a subpoena.
Businesses using data intermediaries will
therefore need to consider:
Whether to encrypt data in a way that only
the authorized recipients can access thedata – such that not even the intermediary
itself can access the data in an intelligible
fashion (which may, however, preventthe data intermediary from offering some
services that require access to the datain the clear);–

Whether to seek legislative relief fromand protection against lawful accessrequests; or–Whether to create policies and proceduresto handle such requests (which is a legal
obligation under GDPR and other privacy
laws globally).

Certification/licensing schemes
Certification, or licensing schemes, such as
certificates of conformity are a well-establishedco-regulatory measure and an acknowledged
option for the regulation of data intermediaries.65
A certification could work as follows: thelegislation would define a set of core criteriathat all certified intermediaries should meetin order to demonstrate their neutrality; thisset of core criteria could be the absence of
conflict of interest, no competition with data
users (e.g. no development of own data apps
in competition with others, so as to avoid any
risks of self-preferencing) and the commitment
to not discriminate between companies thatwould like to offer data services (openness
obligation).66 Certification under these criteria
could then either be voluntary or compulsory.

––

Law enforcement and access requests
This inevitable pressure to either resist orcomply with lawful access or intelligence–

Collaboration
Finally, businesses may wish to consider
learning from non-traditional allies, such as
peers with different business models but who
could benefit from the use of TDAs. Peer-topeer learning can provide opportunities forthe application of TDAs. Those applications
in turn inform the broader policy andgovernance debate.

Advancing Digital Agency: The Power of Data Intermediaries

36

Conclusion
Opportunities abound to create and adopt novel
solutions to the challenge of enabling users tomake durable decisions for how data about
them is used and to make sure their wishes areabided by – and to be able to share that data.
Since it is not possible for every business todo this, the solution is to give them a service
provider: a data intermediary. The idea of placing
a trusted data intermediary inside the data value
chain can also be a form of standardization.
In order to fully harness the data ecosystem
in a responsible, cohesive and interoperable

manner, people, businesses and governments
require trusted safeguards that respect humancentricity and proprietary rights alike when
designing alternatives to notice and consent.
Businesses meanwhile are already using dataintermediaries in instances of delegated agency,such as in the payments industry. Businesses are
more empowered than they may believe giventhat digital agency policy is in its infancy; but it will
become established in a way that endorses norms,
including the identification and prevention of harms.

What could go wrong? What could go right?
In many ways, a lot of things are already goingwrong. Users are carved up as products and theirdata used in ways they are uninformed about – orfeel uninformed about; in ways that their data might
be used, which could be inconsistent with theusers’ values or preferences; or in unexpected waysthat the application did not disclose. In worst casescenarios, digital agents could lead to the nontransparent use of data, including in ways that harmthe data subject.
At the system level, without efficient diversity,
people may find the opposite – that they have or
perceive to have reduced spectrum of choices oragency. This is due to the echo chamber effectof group think.
On the flip slide, a lot could go right:–

A balance of control for any user to understandthe decision they are making as to voluntarily
providing their data or withholding it, thanks
to their understanding of the policy of theapplication and the accountability of thehost company OR the scaling of the user’s
permission sets according to skill set onunderstanding technology.

Advancing Digital Agency: The Power of Data Intermediaries

37

–

–

–

Granularity to provide options as to what data
the user will volunteer (for example, if I am a dog
owner, I might be happy to volunteer that data,
so I get dog food ads; but I do not want myhealthcare data shared).
Improved data provenance as a result of
increased legal certainty. It is essential toconsider data provenance when working on
things like blockchain and machine learning

present choices to the user but the choices
would already be created by the application.
–

Some decision automation without interrupting
the user’s current task, without worrying aboutrisky use of the data.

Trusted digital agency that harnesses the powerof data intermediaries holds so much promise; but
it is clear that a one-size-fits-all solution does notexist. Instead, it is necessary to look at lessons
from industry and academia to observe what canbe learned and the meaningful actions to take tosuccessfully rewrite notice and consent where it isless relevant.

A user would have the ability to choose theirpreferred application, which might align with
their personal values and the values of theapplication or company. An application may

A multistakeholder call to action
In developing the rules of the game for trusted dataintermediaries giving rise to a potentially automatedregime of personal data sharing at a system level ina manner that overcomes the limitations of noticeand consent regimes, it is the voice and presenceof people that matter most. This presence can beamplified by taking a human-centric approach tothe issue and placing people at the centre of such a
step change in data policies.
But it also requires a multistakeholder approachto get right. It is only by listening – to people
to understand their experience and desires,to businesses to understand their innovations
and constraints, to scholars who can isolate
commonalities between models, and of course togovernments who aim for evidence-based policy-

making from a unique vantage point – that it ispossible to start to understand the rich tapestry of
the implications of data intermediaries, especiallytrusted digital agents, in different scenarios.
The concept of trusted digital agency is effectively
in policy “beta67 mode and therefore requires testingfrom all stakeholders. Only when the concept istested will it be possible to unearth the solutions
that society will demand to advance towards
trusted digital agency. That will be the key toholistic, systemic policy-making that leverages
technological advancement for human-centric, proinnovation purposes in areas such as international
data transfers, healthcare research and diagnostics,
innovation itself and a safer and more inclusive
online world.

Advancing Digital Agency: The Power of Data Intermediaries

38

Glossary
Cross-border data flows
The movement of data across international borders,
usually at the business-to-business level.
Data controller
As defined in the GDPR (Article 4), the natural or
legal person, public authority, agency or otherbody which, alone or jointly with others, determines
the purposes and means of the processing of
personal data.
Data ecosystem
The ecosystem within which data exists andoperates, either locally or at a global level. Thiscan include the data itself and the applications
and infrastructure that support its storage, access,processing, use and reuse.
Data portability
The ability to port data from one system to another.
Data processing
As defined in the GDPR (Article 4), any operationor set of operations that is performed on personal
data or on sets of personal data, whether or
not by automated means, such as collection,
recording, organization, structuring, storage,
adaptation or alteration, retrieval, consultation,use, disclosure by transmission, disseminationor otherwise making available, alignment or
combination, restriction, erasure or destruction.

Decentralized autonomous organizations(DAOs)
Independent, self-governed and self-funded
decentralized organizations based on a foundationof smart contracts.
ePrivacy Directive
Directive 2002/58/EC of the European
Parliament and of the Council of 12 July
2002 concerning the processing of personal
data and the protection of privacy in theelectronic communications sector (Directive
on privacy and electronic communications).

Human-centricity
Putting people’s wants and needs at the forefrontof process and systemic decision-making.

Data protection and privacy laws
Laws that govern the collection and processingof personal data and personally identifiable
information and that vary from territory to territory.
These differences can act as both a hard and softbarrier to the movement of data across borders
and can cover personal and/or non-personal data.

Data subject
As defined in the GDPR (Article 4), an identified or
identifiable natural person; an identifiable natural
person is one who can be identified, directly or
indirectly, in particular by reference to an identifier
such as a name, an identification number, location
data, an online identifier or to one or more factors
specific to the physical, physiological, genetic,
mental, economic, cultural or social identity of thatnatural person.

Dataspace
A common space designated to use data fora specific purpose or purposes.

General Data Protection Regulation 2018
(GDPR)
Regulation (EU) 2016/679 of the European
Parliament and of the Council of 27 April 2016
on the protection of natural persons with regard
to the processing of personal data and on thefree movement of such data, and repealing
Directive 95/46/EC.

Data processor
As defined in the GDPR (Article 4), a natural or
legal person, public authority, agency or otherbody that processes personal data on behalf ofthe controller.

Data provenance
Identifies the origin of the data processor and data
owner and documents a record of the history ofthe data since collection.

Data trust
An entity or group of entities that is entrusted
to manage a specific data ecosystem or data
value chain.

IoT (internet of things)
A network of items – each embedded withsensors – that are connected to the internet.
Metaverse
A virtual reality space in which users can interact
with a computer-generated environment andother users.
Open Data Watch’s Data Value Chain
The Data Value Chain framework68 helps technicalpractitioners understand how interoperability adds
value to data on the data value chain. The data
value chain describes four major stages: collection,
publication, uptake and impact. It is essential toreference interoperability at each stage, startingfrom when the handshake happens between
systems, to either consume or deliver data in thevalue chain. For example, it will define classifications
and standards to be followed while collecting
and storing the data. Importantly, it describes
how downstream systems should use the data.
The interoperability checklist must also reflect theorganizational practices and data management
plans that cover the entire data value chain.

Advancing Digital Agency: The Power of Data Intermediaries

39

Open data
Data that is made available for anyone to accessand usePersonal data
As defined in the GDPR (Article 4), any information
relating to a data subject. It is important to notethat information that relates to a data subject, even
without a name, can qualify as personal data under
the GDPR.
RegtechFirst coined by the United Kingdom’s Financial
Conduct Authority (FCA) in 2015, which called ita “subset of fintech that focuses on technologies
that may facilitate the delivery of regulatory
requirements more efficiently and effectively
than existing capabilities.” In simple terms, it
refers to any technology that ensures companies
comply with their regulatory requirements.69

Software as a service (SaaS)
Software solutions that reside in the cloud but, due
to high-speed connectivity, can be used in real time
as if they resided locally.
User experience (UX) design
The design process through which people
experience the technology they interact with.
Web 3.0 or Web 3
The third generation of the internet, which isdecentralized in nature and enabled by distributed
ledger technologies.
Zero-knowledge proof (ZKP)
A concept in cryptography whereby one party can
prove the existence of something to another party
without revealing the properties of that something.

Advancing Digital Agency: The Power of Data Intermediaries

40

Contributors
Lead author
Anne Josephine Flanagan
Data Policy and Governance Lead,
World Economic ForumTask Force on Data Intermediaries (Co-authors)
Michael Bahar
Partner, Co-Lead, Global Cybersecurity andData Privacy, Eversheds Sutherland
Paula Barrett
Partner, Co-Lead, Global Cybersecurity andData Privacy, Eversheds Sutherland
Laura Brandimarte
Assistant Professor of Management Information
Systems, University of Arizona
Matthias De Bievre
Chief Executive Officer, VISIONS
Megan Doerr
Principal Scientist, Sage Bionetworks
Edwin Doyle
Global Security Strategist, Check Point Software
Cristian I. Duda
Managing Partner, Chief Digital Officer,
Haefeli & Schroeder Financial Lines
Richard Gomer
Research Fellow, Trust & Digital Agency,
University of Southampton
Jana Gooth
Legal Policy Adviser, European Parliament
Jennifer King
Privacy and Data Policy Fellow, Stanford Institutefor Human-Centered Artificial Intelligence

Caroline Louveaux
Chief Privacy Officer, Mastercard
Ewa Luger
Chancellor’s Fellow, The Alan Turing Institute,
Edinburgh University
Bijan Madhani
Privacy and Data Policy Lead, Meta
Allan Millington
Director, Data Office, EY
Teresa Patraquim da Conceição
Head Privacy Team, International, Novartis
Steven Tiell
Lead, Responsible Innovation + Data Ethics,
Accenture
Aleksandr Tiulkanov
Special Adviser on Digital Development,
Council of Europe
Joe Toscano
Founder, BEACON
Stefaan Verhulst
Co-Founder and Chief Research and Development
Officer, Governance Lab @ NYU
Jacques de Werra
Professor of Law; Director, Digital Law Center,
University of Geneva

Gary LaFever
Chief Executive Officer, Anonos

Richard Whitt
President, GLIA Foundation; Founder andChief Executive Officer, Deeper Edge

Xiao Liu
Assistant Professor, McGill University

Christian Wickert
Head, New Technologies Policy, USA, Merck

Advancing Digital Agency: The Power of Data Intermediaries

41

Acknowledgements
Suzie Albizzati
Head, Corporate Marketing, AlixPartners
Donald Bullers
Global Technical Lead, Elastos Foundation
Jan Huizeling
Vice-President, Digital Labs, Yara International
Robert Kain
Chief Executive Officer and Co-Founder, LunaPBC
Richard Kibble
Global Head, Data Privacy, Alcon
Morgan Livingston
Science Policy Fellow, IDA Science and Technology
Policy InstituteWorld Economic Forum
Kimmy Bettinger
Project Specialist, Data PolicyEvîn Cheikosman
Policy Analyst, Crypto Impact and Sustainability
Accelerator
Tenzin Chomphel
Project Coordinator, Data Policy
Sheila Warren
Deputy Head, Centre for the Fourth Industrial
Revolution Network
Danielle Carpenter
EditorLaurence Denmark
DesignAdvancing Digital Agency: The Power of Data Intermediaries

42

Endnotes
1.

World Economic Forum, 2020, Redesigning Data Privacy: Reimagining Notice & Consent for human-technology interaction,
https://www.weforum.org/reports/redesigning-data-privacy-reimagining-notice-consent-for-humantechnology-interaction.

2.

Ibid.

3.

McDermott, B., 2019, “Mind The Gap: The Trust/Experience Paradox”, Forbes, https://www.forbes.com/sites/
sap/2019/01/15/mind-the-gap-the-trustexperience-paradox/?sh=4df2fd4e6275.

4.

Hardin, R., 2002, Trust and Trustworthiness, Russell Sage Foundation.

5.

World Economic Forum, 2020, Redesigning Data Privacy: Reimagining Notice & Consent for human-technology interaction,
https://www.weforum.org/reports/redesigning-data-privacy-reimagining-notice-consent-for-humantechnology-interaction.

6.

Tierney, J., 2011, “Do you suffer from decision fatigue?”, New York Times, https://www.nytimes.com/2011/08/21/
magazine/do-you-suffer-from-decision-fatigue.html.

7.

McDonald, A.M and Cranor, L.F., 2008, “The Cost of Reading Privacy Policies”, I/S: A Journal of Law and Policy for the
Information Society, 2008 Privacy Year in Review issue.

8.

Data2X and Open Data Watch, n.d., The Data Value Chain: Moving from Production to Impact, https://opendatawatch.
com/wp-content/uploads/2018/03/Data_Value_Chain-WR-1803126.pdf.

9.

GDPR Article 4 requires heightened requirements for pseudonymisation beyond merely replacing direct identifierswith tokens for individual fields within a single data set. Such heightened requirements for pseudonymization include
protecting all data elements, protecting against singling out attacks, dynamism, non-algorithmic lookup tables andcontrolled re-linkability,

10.

World Economic Forum, 2019, Federated Data Systems: Balancing Innovation and Trust in the Use of Sensitive Data,
https://www3.weforum.org/docs/WEF_Federated_Data_Systems_2019.pdf.

11.

World Economic Forum, 2021, Empowered Data Societies: A Human-Centric Approach to Data Relationships,
https://www3.weforum.org/docs/WEF_Empowered_Data_Societies_2021.pdf.

12.

European Commission, 2020, Data sharing in the EU – common European data spaces (new rules), https://ec.europa.eu/
info/law/better-regulation/have-your-say/initiatives/12491-Data-sharing-in-the-EU-common-European-data-spaces-newrules-_en\.

13.

Tiel, Steven, 2020, “AI Ethics vs Data Ethics”, Ethics of Data, https://ethicsofdata.com/ai-ethics-vs-data-ethics.

14.

Data2X and Open Data Watch, n.d., The Data Value Chain: Moving from Production to Impact, https://opendatawatch.
com/wp-content/uploads/2018/03/Data_Value_Chain-WR-1803126.pdf.

15.

Corritore, C. L., Kracher, B., & Wiedenbeck, S., 2003, “On-line trust: concepts, evolving themes, a model”, International
Journal of Human-Computer Studies, 58(6):737–758, 2003.

16.

Ibid.

17.

Kapoor, A. & Whitt, R.S. 2021, Nudging Towards Data Equity: The Role of Stewardship and Fiduciaries in the
Digital Economy.

18.

Ibid.

19.

Verhulst, S.G., 2021, “Reimagining Data Responsibility: 10 new approaches toward a culture of trust in in re-using data toaddress critical public needs”, Data & Policy, 3, 2021.

20.

Whitt, Richard S., 2020, “Old School Goes Online: Exploring Fiduciary Obligations of Loyalty and Care in the Digital
Platforms Era”, 36 Santa Clara High Tech. L.J. 75, https://digitalcommons.law.scu.edu/chtlj/vol36/iss1/3.

21.

Brandusescu, A. & van Geuns, J., 2020, Shifting Power through Data Governance 2020, https://assets.mofoprod.net/
network/documents/ShiftingPower.pdf.

22.

Delacroix, S. & Lawrence, N.D., 2019, “Bottom-up data Trusts: disturbing the ‘one size fits all’ approach to data
governance”, International Data Privacy Law, vol. 9, issue 4, November 2019.

23.

Cohen, C. and Wendehorst, C., 2021, ALI-ELI Principles for a Data Economy, Data Transactions and Data Rights, ELI
Final Council Draft, https://www.principlesforadataeconomy.org/.

24.

Young, A. & Verhulst, S.G., 2020, “Data collaboratives”. In: Harris, P, Bitonti, A, Fleisher, C, Skorkjær, BA (eds)
The Palgrave Encyclopedia of Interest Groups, Lobbying and Public Affairs. Cham: Palgrave Macmillan. https://doi.
org/10.1007/978-3-030-13895-0_92-1.Google Scholar

25.

Ada Lovelace Institute, 2021, Exploring Legal Mechanisms for Data Stewardship, https://www.adalovelaceinstitute.org/
report/legal-mechanisms-data-stewardship/.

26.

Ibid.

Advancing Digital Agency: The Power of Data Intermediaries

43

27.

Ostrom, E., 2015, Governing the Commons: The Evolution of Institutions for Collective Action, Cambridge University Press.

28.

Ada Lovelace Institute, 2021, Exploring Legal Mechanisms for Data Stewardship, https://www.adalovelaceinstitute.org/
report/legal-mechanisms-data-stewardship/.

29.

Some entities are experimenting with various real-world proof of concept exercises to determine, among other factors,
the potential viability and scalability of the commercial digital fiduciary model. See Whitt, R., 2021, Gaining Real-World
Validation of the Digital Fiduciary Model, Aapti Institute, The Data Economy Lab, White Paper Series, November 2021,
https://www.linkedin.com/feed/update/urn:li:activity:6874905018835849216/.

30.

European Parliament, 2020, Regulation of the European Parliament and of the Council on European data governanceCOM(2020) 767 final.

31.

H.M. Government, 2021, Unlocking the value of data: Exploring the role of data intermediaries, https://www.gov.uk/
government/publications/unlocking-the-value-of-data-exploring-the-role-of-data-intermediaries/unlocking-the-value-ofdata-exploring-the-role-of-data-intermediaries.

32.

Lähteenoja, V., Flanagan, A. J., & Warren, S., 2021, “On the importance of human-centricity and data”, World Economic
Forum, https://www3.weforum.org/docs/WEF_On_the_Importance_of_Human_Centricity_2021.pdf.

33.

Other fiduciary duties include good faith and confidentiality, as per Black’s Law Dictionary, 2019, 11th ed. which defines
other fiduciary duties as “good faith, trust, special confidence, and candor”.

34.

Lähteenoja, V., Flanagan, A. J., & Warren, S., 2021, “On the importance of human-centricity and data”, World Economic
Forum, https://www3.weforum.org/docs/WEF_On_the_Importance_of_Human_Centricity_2021.pdf.

35.

See Open Data Institute, 2019, Data trusts: legal and governance considerations, https://theodi.org/wp-content/
uploads/2019/04/General-legal-report-on-data-trust.pdf, p. 8: “court action is expensive and likely to be too slow for
the needs of a data trust, which include maintaining confidence that its rules provide appropriate protections for all the
stakeholders in data. Thus, the report suggests that alternative dispute resolution mechanisms need to be incorporated
into the data trust’s rules”.

36.

On the emergence of data disputes and of data arbitration, see de Werra, J., 2019, “Using Arbitration and ADR for
Disputes about Personal and Non-Personal Data: What Lessons from Recent Developments in Europe?”, American
Review of International Arbitration, vol. 30, n° 2, p. 195-217, available at: https://archive-ouverte.unige.ch/unige:134313;
de Werra, J., 2018, “From Intellectual Property (Data-Related) Disputes to Data Disputes: Towards the Creation of a
Global Dispute Resolution Ecosystem for Data Disputes in the Digital Era”, in: Resolving IP Disputes (Graz: NWV Verlag),2018, p. 87-109, available at: https://archive-ouverte.unige.ch/unige:113027.

37.

de Werra, J., 2016, “ADR in Cyberspace: The Need to Adopt Global Alternative Dispute Resolution Mechanisms for
Addressing the Challenges of Massive Online Micro-Justice”, Swiss Review of International & European Law 2016, 289306, https://ssrn.com/abstract=2783213.

38.

See the report Data trusts: legal and governance considerations by BPE Solicitors, Pinsent Masons and Chris Reed at
Queen Mary University of London, 2019, https://theodi.org/wp-content/uploads/2019/04/General-legal-report-ondata-trust.pdf, p. 8: “[…] court action is expensive and likely to be too slow for the needs of a data trust, which include
maintaining confidence that its rules provide appropriate protections for all the stakeholders in data. Thus the reportsuggests that alternative dispute resolution mechanisms need to be incorporated into the data trust’s rules.”See also de Werra, J., 2016, “ADR in Cyberspace: The Need to Adopt Global Alternative Dispute Resolution Mechanisms
for Addressing the Challenges of Massive Online Micro-Justice”, Swiss Review of International & European Law 2016,289-306, https://ssrn.com/abstract=2783213.

39.

See the report Data trusts: legal and governance considerations by BPE Solicitors, Pinsent Masons and Chris Reed at
Queen Mary University of London, 2019, https://theodi.org/wp-content/uploads/2019/04/General-legal-report-ondata-trust.pdf, p. 41: “[…] dispute review boards (“DRB”), are ordinarily seen under construction contracts and exist for
the length of a particular project. These are put in place by contractual arrangement and governed by the International
Chamber of Commerce Board Rules. The model however could equally be applicable to disputes arising out of a datatrust if similar DRB provisions were to be put into the terms of use for the providing or licensing of data.”

40.

International Network on Digital Self-Determination, https://idsd.network/.

41.

Source: World Economic Forum, 2018, Identity in a Digital World: A new chapter in the social contract,
https://www.weforum.org/reports/identity-in-a-digital-world-a-new-chapter-in-the-social-contract.

42.

World Economic Forum, 2018, Identity in a Digital World: A new chapter in the social contract, https://www.weforum.org/
reports/identity-in-a-digital-world-a-new-chapter-in-the-social-contract.

43.

Kinston, J. & Ng, I., 2021, “Personal Data Servers will help take back digital ID from big tech”, Wired, https://www.wired.
co.uk/article/personal-data-servers.

44.

Centre for Data Ethics and Innovation, 2021, Unlocking the value of data: Exploring the role of data intermediaries – An
exploration of the role intermediaries could play in supporting responsible data sharing, https://assets.publishing.service.
gov.uk/government/uploads/system/uploads/attachment_data/file/1004925/Data_intermediaries_-_accessible_version.
pdf.

45.

Turner, C., David, S., Ahuja, A. & Wulfsohn, G., 2016, Accenture Labs Ethical algorithms for “sense and respond” systems,
Accenture, https://www.academia.edu/31436602/Accenture_Labs_Ethical_algorithms_for_sense_and_respond_systems.
Advancing Digital Agency: The Power of Data Intermediaries

44

46.

Future of Privacy Forum, 2017, Unfairness By Algorithm: Distilling the Harms of Automated Decision-Making,https://fpf.org/wp-content/uploads/2017/12/FPF-Automated-Decision-Making-Harms-and-Mitigation-Charts.pdf.

47.

For example, see Jennings, N. & Wooldridge, W., 1996, “Software Agents”, IEE Review, January 1996, pp 17-20, http://
www.cs.ox.ac.uk/people/michael.wooldridge/pubs/iee-review96.pdf.

48.

Ibid.

49.

Friedman, B., Smith, I., Kahn, P., Consolvo, S., Selawski, J., 2006, “Development of a Privacy Addendum for OpenSource Licenses: Value Sensitive Design in Industry”, Proc. UBICOMP, ACM Press (2006) 194—211.

50.

Luger, E. & Rodden, T., 2013, “An Informed View on Consent for Ubicomp”. UbiComp ‘13: Proceedings of the 2013 ACM
international joint conference on Pervasive and ubiquitous computing, September 2013, pp. 529–538,
https://doi.org/10.1145/2493432.2493446.

51.

Human Data Interaction, n.d., What is Human-Data Interaction?, https://hdi-network.org/intro_to_hdi/.

52.

Diver, L., 2020, “Computational Legalism and the Affordance of Delay in Law”, Journal of Cross-Disciplinary Research in
Computational Law 1 (1), https://journalcrcl.org/crcl/article/view/3.

53.

Luger, E. & Rodden, T., 2013, “An Informed View on Consent for Ubicomp”. UbiComp ‘13: Proceedings of the 2013 ACM
international joint conference on Pervasive and ubiquitous computing, September 2013, pp. 529–538,
https://doi.org/10.1145/2493432.2493446.

54.

See for example:–

MyData Operators, which is empower individuals by improving their right to self-determination regarding theirpersonal data, at https://mydata.org/;–

Decode, a consortium of 15 organizations from across the European Union, at https://www.decodeproject.eu/;–

The Solid project at the Massachusetts Institute of Technology, at https://solid.mit.edu/;–

RadicalxChange (RxC), a global movement for next-generation political economies, at https://radicalxchange.org/.

55.

European Parliament resolution of 20 October 2020 with recommendations to the Commission on a Digital Services Act:
adapting commercial and civil law rules for commercial entities operating online (2020/2019(INL)), Art. 17,
https://www.europarl.europa.eu/doceo/document/TA-9-2020-0273_EN.html.

56.

Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural
persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive
95/46/EC (General Data Protection Regulation), https://eur-lex.europa.eu/eli/reg/2016/679/oj.

57.

See Whitt, R., 2021, “Hacking the SEAMs: Elevating Digital Autonomy and Agency for Humans”, Colorado Technology
Law Journal, Vol. 19, Issue 1, 137, 202 (2021).

58.

Ibid.

59.

European Parliament, 2020, Regulation of the European Parliament and of the Council on European data governance
COM (2020) 767.

60.

European Parliament and European Council, 2002, Directive 2002/58/EC of the European Parliament and of the Council
concerning the processing of personal data and the protection of privacy in the electronic communications sector(Directive on privacy and electronic communications) as amended, https://eur-lex.europa.eu/eli/dir/2002/58/oj.

61.

European Parliament, 2020, Regulation of the European Parliament and of the Council on European data governance
COM (2020) 767 final.

62.

Cf. Data Ethics Commission of the Federal Government of Germany, 2019, Opinion of the Data Ethics Commission,p. 134, https://www.bmjv.de/SharedDocs/Downloads/DE/Themen/Fokusthemen/Gutachten_DEK_EN_lang.pdf?__
blob=publicationFile&v=3.

63.

InfoCuria, n.d., Case-law, https://curia.europa.eu/juris/documents.jsf?num=C-311/18.

64.

World Economic Forum, 2021, A Roadmap for Cross-Border Data Flows: Future-Proofing Readiness and Cooperation in
the New Data Economy, https://www.weforum.org/whitepapers/a-roadmap-for-crossborder-data-flows-future-proofingreadiness-and-cooperation-in-the-new-data-economy.

65.

European Parliament, 2020, Regulation of the European Parliament and of the Council on European data governance
COM (2020) 767.

66.

European Commission, 2020, EU Commission impact assessment accompanying the proposal for a Regulation on
data governance (Data Governance Act) from 25 November 2020, SWD (2020) 295 final, p. 26, https://ec.europa.eu/
newsroom/dae/document.cfm?doc_id=71225.

67.

Beta mode is the test and trial period for a new piece of software when rapid learning and experimentation occur.

68.

Open Data Watch, 2018, “The Data Value Chain: Moving from Production to Impact”, https://opendatawatch.com/
publications/the-data-value-chain-moving-from-production-to-impact/.

69.

EQS Group, 2021, “What Is RegTech?”, https://www.eqs.com/en-us/compliance-knowledge/blog/what-is-regtech/.

Advancing Digital Agency: The Power of Data Intermediaries

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