Experimenting With New Models of Data Governance – Data Trusts

This post has been authored by Shashank Mohan

India is in the midst of establishing a robust data governance framework, which will impact the rights and liabilities of all key stakeholders – the government, private entities, and citizens at large. As a parliamentary committee debates its first personal data protection legislation (‘PDPB 2019’), proposals for the regulation of non-personal data and a data empowerment and protection architecture are already underway. 

As data processing capabilities continue to evolve at a feverish pace, basic data protection regulations like the PDPB 2019 might not be sufficient to address new challenges. For example, big data analytics renders traditional notions of consent meaningless as users have no knowledge of how such algorithms behave and what determinations are made about them by such technology. 

Creative data governance models, which are aimed at reversing the power dynamics in the larger data economy are the need of the hour. Recognising these challenges policymakers are driving the conversation on data governance in the right direction. However, they might be missing out on crucial experiments being run in other parts of the world

As users of digital products and services increasingly lose control over data flows, various new models of data governance are being recommended for example, data trusts, data cooperatives, and data commons. Out of these, one of the most promising new models of data governance is – data trusts. 

(For the purposes of this blog post, I’ll be using the phrase data processors as an umbrella term to cover data fiduciaries/controllers and data processors in the legal sense. The word users is meant to include all data principals/subjects.)

What are data trusts?

Though there are various definitions of data trusts, one which is helpful in understanding the concept is – ‘data trusts are intermediaries that aggregate user interests and represent them more effectively vis-à-vis data processors.’ 

To solve the information asymmetries and power imbalances between users and data processors, data trusts will act as facilitators of data flow between the two parties, but on the terms of the users. Data trusts will act in fiduciary duty and in the best interests of its members. They will have the requisite legal and technical knowledge to act on behalf of users. Instead of users making potentially ill-informed decisions over data processing, data trusts will make such decisions on their behalf, based on pre-decided factors like a bar on third-party sharing, and in their best interests. For example, data trusts to users can be what mutual fund managers are to potential investors in capital markets. 

Currently, in a typical transaction in the data economy, if users wish to use a particular digital service, neither do they have the knowledge to understand the possible privacy risks nor the negotiation powers for change. Data trusts with a fiduciary responsibility towards users, specialised knowledge, and multiple members might be successful in tilting back the power dynamics in favour of users. Data trusts might be relevant from the perspective of both the protection and controlled sharing of personal as well as non-personal data. 

(MeitY’s Non-Personal Data Governance Framework introduces the concept of data trustees and data trusts in India’s larger data governance and regulatory framework. But, this applies only to the governance of ‘non-personal data’ and not personal data, as being recommended here. CCG’s comments on MeitY’s Non-Personal Data Governance Framework, can be accessed – here)

Challenges with data trusts

Though creative solutions like data trusts seem promising in theory, they must be thoroughly tested and experimented with before wide-scale implementation. Firstly, such a new form of trusts, where the subject matter of the trust is data, is not envisaged by Indian law (see section 8 of the Indian Trusts Act, 1882, which provides for only property to be the subject matter of a trust). Current and even proposed regulatory structures don’t account for the regulation of institutions like data trusts (the non-personal data governance framework proposes data trusts, but only as data sharing institutions and not as data managers or data stewards, as being suggested here). Thus, data trusts will need to be codified into Indian law to be an operative model. 

Secondly, data processors might not embrace the notion of data trusts, as it may result in loss of market power. Larger tech companies, who have existing stores of data on numerous users may not be sufficiently incentivised to engage with models of data trusts. Structures will need to be built in a way that data processors are incentivised to participate in such novel data governance models. 

Thirdly, the business or operational models for data trusts will need to be aligned to their members i.e. users. Data trusts will require money to operate – for profit entities may not have the best interests of users in mind. Subscription based models, whether for profit or not, might fail as users are habitual to free services. Donation based models might need to be monitored closely for added transparency and accountability. 

Lastly, other issues like creation of technical specifications for data sharing and security, contours of consent, and whether data trusts will help in data sharing with the government, will need to be accounted for. 

Privacy centric data governance models

At this early stage of developing data governance frameworks suited to Indian needs, policymakers are at a crucial juncture of experimenting with different models. These models must be centred around the protection and preservation of privacy rights of Indians, both from private and public entities. Privacy must also be read in its expansive definition as provided by the Supreme Court in Justice K.S. Puttaswamy vs. Union of India. The autonomy, choice, and control over informational privacy are crucial to the Supreme Court’s interpretation of privacy. 

(CCG’s privacy law database that tracks privacy jurisprudence globally and currently contains information from India and Europe, can be accessed – here

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