The current “Ownership Model” does not encourage reuse

In the private sector a large and profitable industry has grown uparound the collection, integration, and monetisation of data for marketing purposes.

This data reuse industry is based on an inherently extractive model, realising value from exclusive ownership. The data is obtained in exchange for “free services” such as email, search, or social media platforms. The same approach is also employed by non-digital services, such as buying shoes at your local shop and using a loyalty card. Digital footprints and fingerprints are traced and tracked as you shop and go about your daily life. The companies doing this want to build up the most complete profile of you that they can. Whoever does this best can realise a financial dividend by on-selling your integrated profile to marketing companies and other commercial interests for a profit.

This is a competitive and commercial approach to building up an integrated behavioural profile of our lives. The trouble is (apart from lack of control and privacy) that at the heart of the model is the fragmentation and siloing of data rather than sharing and integration.

The commercial imperative is to monopolise and own more data. Googleextracts value from data for its shareholders by on-selling integrated pro lesof its users to direct marketing companies. The same is true of Facebook and Loyalty New Zealand, and other integrators of personal data. These companies are competing with each other to monetise your profile, so they don’t integrate their respective data assets (unless they get bought out). E.g. Microsoft bought Linkedin to add to its inventory of social network data.

The service user has little meaningful control over how that data is used and whether and to whom it is on-sold.

The public sector in New Zealand and elsewhere is falling into the same pattern.

Many government agencies have been, and remain, reluctant to share data with each other, partly because they are stewards of data acquired using the coercive powers of the state, but also from a bureaucratic instinct to stick to hierarchical lines and resist lateral collaboration. More recently, in an era of joined-up government and under significant pressure from the centre to work across organisational boundaries, at least some parts of the state sector have a newly developed interest in reuse and integration, particularly of personal data. There is genuine value to society in having a better understanding of life pathways, of what works, of how to invest better socially and economically. But the reuse of data in the public sector comes with risks. While sharing of personal information has to meet the requirements of the Privacy Act, there is still potential for misuse and increased marginalisation of individuals and communities.

For example, in New Zealand, non-governmental organisations (NGOs) are increasingly being caught in crossfire between citizens and the state. Agencies such as the Ministry of Social Development are increasingly demanding that third party providers (who rely on MSD contracts for their survival) hand over identifiable and deeply personal data about the people who use their service. So MSD is meeting its interests in obtaining and integrating data from third parties. But in doing so it may be overriding the interests of those third parties and their relationships with their clients.

The coercive approach to appropriating citizen data may represent high value to government in the short term, but it erodes confidence and trust between NGO providers and their service users who are the source of the data that government agencies value so highly. NGOs are already expressing concern that marginalised and ‘hard to reach’ communities may go further underground because they can no longer expect a confidential and high-trust relationship with the NGOs that were set up to support them.

In education, it is now possible to “tear down the classroom wall” (as one Ministry of Education offcial described it) through the use of an integrated profile of every learner. The information could be used for performance-based pay linked to how well a teacher does for each kind of student. But micro-level indicator-based control of teachers and students from central government is likely to reduce the quality of data and eventually stifle innovation and the quality of outcomes. People removed from engagement are poor decision-makers about data reuse and value since very often their interests do not align with the users of government services or the people who serve them directly. Getting elected or meeting the sector KPIs for career advancement is very different work from improving other people’s lives.

Unfortunately, because of the power that public servants can have over people’s lives, many citizens simply do not trust them to make good decisions for other people about how their data should and should not be used. That decision is best placed back in the hands of the affected people who own their own data who can then share it exclusively with the people they trust. This is called consent – it is a basic principle, for good reasons, in privacy legislation but it can be expanded by embedding it in data management.

The reuse of data by business and government based on an Ownership Model has two fundamental problems that need addressing:

  • You, as the user of the service in which your data is generated, don’t get to use your integrated profile for your own benefit. The company or agency to which you surrendered your personal data has no interest in your realising the value of your own integrated personal profile to help you better manage your wellbeing, your time, or your finances. Somebody else gets all the value from this fine-grained knowledge of your life.

  • Society doesn’t get to realise any benefit from your integrated profile either. People working to solve complex social challenges such as diabetes, homelessness, and child abuse cannot benefit from society’s data about itself. Your data may have become the private property of a technology company and have to be bought back, or it may be locked up in different government sites by officials using it as an asset to further their own careers or by ministers who would rather not have the political risk often attached to transparency.

Whilst these kinds of concern are acute when applied to the reuse of personal data, similar kinds of concern emerge around data reuse for the scientific community, for professional interests, and for commercial interests. Scientific and commercial interests also have trust challenges with the reuse of data they (co)produce. How do I integrate and share my data in an environment of “publish or perish”? How can I be the first to market if everyone can use my hard-earned data?

In a nutshell, the current Ownership Model for data reuse is destroying value and frustrating collaboration. Entrepreneurs, politicians, public servants, community leaders, scientists, and citizens who can see the value in greater data reuse face significant institutional and systemic resistance, or they themselves feel the professional, personal, or commercial risks are too great. “How can I allow reuse without losing control over something I have an ongoing personal, professional, or commercial interest in?”

One of the fundamental barriers to greater reuse is lack of trust or control over reuse.

Should we acknowledge the risks and abandon the effort? Or perhaps further data reuse and integration for greater individual and community benefit is only possible with more private ownership and coercive appropriation? We’re optimistic that the future for use of data for our collective benefit as a society is bright, but it will be based on the development of a new model of data sharing, reuse, and integration.

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