KGRI Working Papers
No.1

Quest for Broadly Acceptable Architecture for Data Governance-A Man-Machine Conviviality Approach-Version1.0
November 2019

Jiro KOKURYO(i), Jonathan CAVE(ii), David FARBER(i), Hiroaki MIYATA(i),Jun MURAI(i), Takehiro OHYA(i), and Tatsuhiko YAMAMOTO(i)(i)

Keio University, Cyber Civilization Research Center (CCRC)(ii)

Alan Turing Institute and University of Warwick (CCRC adviser)

Keio University Global Research Institute© Copyright 2019 Jiro KOKURYO, Jonathan CAVE, David FARBER, Hiroaki MIYATA,
Jun MURAI, Takehiro OHYA, and Tatsuhiko YAMAMOTO, Keio University

Quest for Broadly Acceptable Architecture for Data Governance-A Man-Machine Conviviality Approach-Jiro KOKURYO, Jonathan CAVE, David FARBER, Hiroaki MIYATA, Jun MURAI, Takehiro
OHYA, and Tatsuhiko YAMAMOTO,
Keio University, Cyber Civilization Research Center
Abstract:
In order to protect human dignity given the ever-growing power of computers anddata aggregation, we must adopt a new philosophy and architecture for thegovernance of data. We step beyond the conventional assumption of humanmonopoly of intelligence and envision integrated man-machine agents that will
emerge to safeguard personal data on a firm basis of trust. A new "cyber civilization"is dawning, in which humans live with machines in conviviality, and we must develop
governance structures that address this reality. A few guiding principles for thedesign of the architecture are proposed.
1. An Alternative Strategy for the Protection of Human Dignity
The dilemma between beneficial exploitation of data and maintenance of privacy aimed at theprotection of human dignity is deepening. This issue has arisen in step with the growing powerof computers and networks but also our waning ability to know, let alone understand or control
their effects. It would not be an exaggeration to say that policy makers and operators handling
data around the world see themselves confronted with a stark choice between 1) abandoning
human rights in favor of the power of collective data, 2) protecting individual rights even at thecost of falling behind competing countries in the exploitation of data for machine learning andcollective intelligence, or 3) finding new ways to think about and guard human dignity by way ofuse of collective data.
This is an introductory note which explores ways to realize the third option by appropriately
designing the architecture of data governance. The primary argument in this paper is that itshould be possible to design an “architecture” for data governance in which citizens can “entrust”
their data without fear of their misuse1. This idea is actively debated in Japan with a view to1“Misuse” here can take many forms, but here, we broadly assume situations in which people

are unfairly discriminated against, or lose autonomy in thoughts and action, based on datacollected by others.
1substantiate the framework of “Data Free Flow with Trust”(DFFT)(METI, 2019), which theJapanese government advocated at the 2019 G20 Summit as its chair.
Architecture here is defined as institutional/technological artifacts that provide an environment(Matsuo et al. 2017: Lessig, 2006) which nudges (Sunstein, 2014) actors to behave in desirable
ways, where desirability in this paper is assessed by the degree to which human dignity is mutuallyhonored. In the sense that it relies on persuasion rather than enforcement, this approach can be
categorized as a “soft law” approach. It may, as an example, include the adoption of machine
assisted “personal data artificial intelligence (AI) agents,” as considered in IEEE P7006”(Merchant, 2019). Personal data AI agents that are given missions, incentives and controllability(the meaning of which includes visibility and explicability) to represent the interest of individuals
can collaboratively maximize the social benefits of shared information.
One might note that an underlying perception in our proposal is that the dogma of “self-control
of private information“ (Waldman, 2018), without the involvement of machines, e.g. algorithmic
content mediation, is becoming unrealistic given the flood of information individuals face. A
collaborative relation between “trustworthy” systems and individuals is necessary to nurture
harmonious man-machine conviviality.
We come to this perception resigned that humans no longer enjoy a monopoly of intellect. We
now live in a world where automated intellectual capabilities that are detached from humanphysical existence are starting to make decisions that humans cannot catch up to. We know that
this is threatening the philosophical and institutional foundations of modern western societies
which assume human monopoly of intellect and rely on individual (autonomy and) consent as
pillars of social order. As much as we would like to dismiss it, a new reality is setting in. Therefore,
we should somehow recognize and position machine intelligence, as well as new forms of(machine-mediated) connected human intelligence, in the architecture of governance.
Boldness in changing our world view seems required to realize the obvious societal benefits ofmaking use of data. Let’s put aside temporarily questions of legitimacy and agency of commercial
enterprises accumulating and using data in their own interests. Though potentially runningcounter to the interests of consumers and other data subjects, there also seems to be a potential
for “common” good to result from data accumulation and use. For example, sharing personal
health records (PHR) clearly offers great benefits through diagnosing and curing individual
patients, improving medicine more generally and advancing related sciences (World HealthOrganization, 2019).

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Japan, though the pioneer in adopting western individualist and liberal democratic principles in
Asia, has also been grappling with the communal traditions of Asian society. For instance, wemight recognize that a society based on “altruistic” virtue, where people are rewarded forrespecting the dignity of others and for their contribution to society, is in fact well suited to aworld of shared data and co-created value. This is why we cannot simply dismiss state governanceof data as “Digital Leninism” (Heilman, 2016).
In an even longer historical and cultural context, Japan also has an animistic tradition thatconsiders humans as a “part” of nature, rather than regarding them at a “top” or “central” position
in it (Jensen, 2013). This contrasts with the societal hierarchies of western and other civilizations
which regard human intellect as a supreme value. The Japanese are also much more receptive tothe idea of recognizing the “self” in non-human beings or even inanimate matter and thus able
to accommodate changes in nature.
While recognizing such alternative systems, we are also cognizant of the great achievements ofdemocratic systems in delivering stable, open, and fair societies that embrace human dignity.
Even in the East, where collective welfare is emphasized, notions of honor and autonomy ofindividuals are upheld as values to be protected. Clearly, the misuse of private information can
result in grave consequences, most notably discrimination offending personal dignity. Used topoint at others, surveillance can easily lead to oppression. Therefore, while democracy in East
Asia may be seen under threat, personal freedom and dignity must be protected. There must be
a way of maintaining the autonomy of individuals while harvesting the value of shared data. In
accordance with the data platform ”Person-centered Open Platform for wellbeing” originallyintroduced by the Japanese government, our team at Keio University humbly remains humancentric, not rightfully so but because we selfishly desire to be so.
2. Governance in “Cyber Civilization”
We believe that the root of fundamental change currently taking place lies with the network
externalities that underpin the digital economy (Katz and Shapiro, 1985: Schilling, 2017). A force
that was not fully recognized in conventional industrial societies is at work, fundamentallychanging the way societies function. We define network externality in this paper as the tendencyof goods and services used by networked individuals – especially those that help them interact –to become more attractive as others adopt them. This has several consequences, including
undersupply of connectivity (because individual adoption or connection decisions may notconsider benefits to others) and undersupply of competition (because one or a few interoperable
products may tip into dominance regardless of whether they are the ‘best’).
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As the term “network” externality suggests, decisions to join or use a network typically affectother users. For the sake of readers who are not familiar with the term, a simplistic illustration
follows – though it should not be over-generalized. A classic telephone (connecting only two
people by voice at a time) has no value if there is no-one to call. For this illustration, we make achallengeable assumption that the value of a network is proportional to the number ofconnections it enables. A second phone allows one connection. A third phone gives three2
connections; n phones allows 𝑛 ⁄2 possible pairwise conversations. One notices here that the
network value increases more than proportionally with the number of users.
Such more-than-linear increases in value with the growing ‘size’ of the market were rare in the“material” world of industrial value creation, where value (to a competitive seller) is linearly
proportional to the number of units of output sold (the constant of proportionality being theprice). In contrast, the nature of the network has been one of the reasons why monopolies,
whether firms or states, tend to emerge. Another reason is that a firm with a larger number ofusers will be more attractive to new users or those patronizing smaller suppliers, and will tend togrow until it absorbs the whole market. As acronyms representing such dominant firms (e.g.
GAFA or FANG) are synonymous with “power,” platforms that accumulate data are gaining
unprecedented power to control and manipulate society. By offering protocols for connection
between (and among) suppliers and users, these platform giants are now capable of gathering
data and exercising power on both the supply and demand sides of electronic markets for content,
e-services, and so on. (Eisenmann et al, 2006). Users are offered access to products that allow
them to connect to more and more peers and merchants; merchants not only gain access to a vast
installed base of consumers, but also to information concerning their preferences and behavior.
This is not just a matter of quantity; choice among more suppliers on the same platform allows
users to more closely match their preferences and increases incentives for suppliers to innovate
constantly. Suppliers able to use vast data samples can make higher-quality estimates ofconsumer preferences than those limited to small and selective samples. Patently, in more andmore fundamental ways, the governance mechanism that has controlled the “material” world
seems unable to control these new realities adequately.
While we are mindful of the danger of simplistic analogy, we note that similar conclusions apply
to exchanges of data. This reflects the recognition that data only has value (meaning2) in a given
context, i.e., a network of data within a certain structure and in connection with other data. Whilean isolated datum does not generate much value, a collection of data exhibiting certain patterns

2

We perceive “meaning” in the context of data as “information” in this paper.
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does. This is felt with a keen sense of urgency in healthcare, where data tend to be scattered andincomplete. Partial data collection may be useful, but far less than comprehensive and complete
data sets. The whole is clearly greater than the sum of its parts.
A careful analysis of the powers and limitations of network effects should be conducted
separately; We note for instance that not all connections create value; some destroy value, whileothers help one party but hurt others. Moreover, complexity and cost limit value; not all benefits(even potential ones) scale up without limit. At the same time, network effects remains a
powerful concept to explain how digital economies may behave differently from the material
economies of industrial societies – and why their governance may therefore need to change as
well.
We believe that these changes are significant enough to herald the emergence of a new paradigm.
We call it Cyber Civilization. Here we define civilization as the pattern of behavior and a norm
developed by (1) core technology that drives society, (2) core wealth (or source of power)
pursued by society, and (3) institutional structure that governs the way technologies andinstitutions are used. We call it cyber civilization because it consists of a complex of man andmachine interacting to form cybernetic beings. (Wiener, 1950)
From this perspective, we understand that we are in the midst of a shift away from industrial
civilization in which energy systems had been the core technology. In this older civilization,
money (which was the token in exchange for material industrial output) constituted core wealth.
The market-based democratic system provided the institutional foundation, with ownership ofmaterial objects by individuals and the exchange of ownership being its key mechanisms. We
underline here that ownership of property (the unconditional and exclusive access right to theuse and utility of an object) has been sacrosanct in industrial civilization.
Following this line of thought, digital technology forms the core technology in cyber civilization,and data (or more precisely, the flow of data through evolving networks) constitutes its wealth.
Governance structure, however, has not yet emerged with any clarity.
Thus, governance structure, or the architecture of cyber civilization, becomes an urgent central
question. The General Data Protection Regulation (GDPR) can be seen as an attempt to tackle
some of the issues arising in an increasingly data driven society (Haug, 2018). However, its
underlying philosophy seems to remain focused on the protection of individualist modernity. We
would like to see the latter evolve to address the new realities of the connected world.

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We know the required architecture will have to promote the benefit of data sharing beyond
borders, but that it will not arise of its own accord. The recent emergence of sharing and circular
economy notions at the same time as security precautions are increased seems to be indicative ofthis. It reflects the nature of cyber civilization in which the value of data increases whenconnected with other data to form meaning.
At the same time, sharing of data should not encroach on human dignity and free will. Thereinlies the challenge as far as governance of cyber civilization is concerned. Mere protection of old
norms will fail to take advantage of new opportunities offered by this world in which machines
help humans to explore new ways of using data to unlock the value hidden in our interactions.
Governance should go beyond simply protecting the modern industrial norm and squarely
address the nature of the new civilization.
3. Architecture for Trust
What design principles should characterize the data governance architecture in cyber
civilization? Based on the above discussion, we argue the architecture should aim at creating
personal data agents (PDA), that employ the power of systems in ways that people can trust.
Data agents apply their technical competence to maximize the value of data sharing while
protecting the privacy of clients.
The question, then, boils down to the design of an architecture that allows individuals to entrust
their data to the agent. Here we propose the following four principles.
(1) Avoiding Conflicts of Interest
A major flaw with the existing major commercial platforms is that they seem to honor the
economic interests of paying clients (most notably advertisers) more than the interests of thelegitimate holders of control of personal information. The incentive structure involved in “target
marketing” business models seems to disregard the welfare of likely victims of personal
information mishandling. Thus, avoidance of conflict of interest should be a primary design ruleof the architecture.
(2) Transparency
While auditing all machine handling of data may not be possible, the algorithms and data usedshould be auditable by a qualified third party. Here again, we should anticipate that it will bemachines that will be assessing algorithmic biases of other machines. We envision a world in
6which checks and balances are provided by multiple “beings,” i.e., integrations of humans andmachines (i.e., cyborgs). Such renewed forms of transparency may, for example, enable agovernment or a peer to certify data handling organizations as trustworthy fiduciaries of thecitizens.
(3) Substitutability
Predictably, life without personal information agents will become intolerably inconvenient. On
the other hand, monopolies may deprive us of our freedom if there are no substitutes and we nolonger have any reason to strive to further our interests. We must ensure against such undesirable
outcomes. To ensure substitutability, the freedom of individuals to move their data from one
agent to another, i.e., data portability, will have to be included in the design rules.
(4) Sustainability
Whatever architecture we adopt has to be sustainable. We must be cognizant of how theenormous power of target marketing to generate profit and provide free services has had users
give up their privacy unguardedly. Authors of this paper are sympathetic to profit making services
handling personal data, to the extent they provide service purely in the interest of the individuals
that use those services. AI agents that connect consumers with desired services should be able toget their rewards. Such rewards will have to be proportional to the economic benefits that theconsumers receive, rather than to sales gained by the sponsors.
Substantiating these principles will have to be a continuing, evolutionary and forward-looking
exercise, as we can expect technologies to advance very quickly and in ways that reflect current
governance. Their enforcement requires multi-stakeholder participation, from commercial
entities to governments, to be subject to monitoring.
4. In Conclusion
Currently, tests are being conducted in Japan around the notion of “information bank,” to which“fiduciary loans” of information are being made on a technical and institutional trial basis. The
notion of personal data AI agent has also been actively debated in this connection. For thesenotions to take firm root in society, a solid philosophical foundation seems essential. Global
discussion is also important to build systems that at a minimum are compatible across nationalboundaries.

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