Something is happening in the world of data. Yes, more data is being collected, analyzed, used, and reused at practically every juncture between life and the internet. At the same time, concerns over personal privacy and the surveillance economy are increasing, too. As new realms of possibility open up for use of data, including for artificial intelligence (AI), are we approaching a time where fundamental critiques of data extraction also begin to sprout new innovations for how we collect, share, and generate purposeful value from data?
The short answer is: yes. But if the dominant paradigm is one where companies like Facebook offer free services to gather data about every facet of human activity to sell ads against, what are the actual emerging alternatives? Who could even compete with such a market share advantage to empower the individuals, communities, and societies from which so much data stems? Over a decade of scholarly writing and research into data governance law and theory show that different pathways for ‘stewarding’ data within trusts, commons, collectives, collaboratives, fiduciaries, and more, are indeed opening up. These various approaches each have their imperfections, but, at least in theory, there is hope for alternatives to help redefine how we conceive of data to address imbalances of power between data holders and data subjects.
Download the full report: "Shifting power through data governance"
The fluid and overlapping definitions of data stewardship evident in literature and theory, inevitably carry over into how we consider examples of them in real life. In practice, innovators of all kinds and in different contexts, are still at the beginning of figuring out what works, for whom, and with what data governance approach. Do the many initiatives we see today for rethinking data in agriculture or health or mobility constitute a credible challenge to the entire surveillance economy? No. Does technology to manage personal data or to distribute benefits from datasets more evenly offer a glimpse of the future? Perhaps. What we do see is a clear rise in the creativity and ingenuity on display to solve real world challenges helped by data in different ways. In the past year alone, countless responses to the COVID-19 global pandemic, show just how far we have come in considering data as a key to solving big problems, for better or worse.
By collaboratively studying and eventually supporting attempts to reimagine, reconstitute, and rebalance data governance, we believe we may help influence a paradigm shift in a positive direction. The values that guide us are embedded in our frameworks for internet health, Trustworthy AI, and the Mozilla Manifesto. We are critical of tech monopolies, critical of tech solutionism, and deeply concerned with privacy, transparency, and accountability. And we are just as concerned when it comes to surveillance and (ab)use of data by the public sector. The learnings we wish to summarize for you are sandwiched between theory and practice. Our goal is to better understand what it takes to build bridges from conceptual frameworks into actual innovations that offer better prospects for humanity in all its diversity of race, gender, geography, ability, and more. We believe in unlocking opportunities for people to gain greater insight and meaningful agency over the different kinds of data that are generated about them.
With external researchers Ana Brandusescu and Jonathan van Geuns we have assembled a literature catalog of more than 250 resources that discuss different facets of data stewardship and alternative forms of data governance. From here, we have siphoned a list of the most commonly discussed data stewardship approaches and defined them. What you will encounter is a general overview accompanied by a few examples and a link to relevant literature. This is not a detailed topography nor legal analysis. It will serve as a foundation from which to proceed with more research and conversations with allies and builders, including many experts who helped review this work. We consider ‘stewardship’ to imply guidance toward a societal goal, while ‘governance’ refers to a process for making decisions and exercising power (we look to Aapti Institute and Ada Lovelace Institute for more refined scrutiny of the term ‘stewardship’).
In the absence of broad consensus around definitions and categories, especially in different languages and across different legal, political, and economic realities, we have worked with a team of regional researchers from Africa, Central and Eastern Europe, South East Asia, and Latin America to assess what types of initiatives, companies, and organizations exist around the world that employ exemplary, new approaches to data governance. Together, we have compiled a non-exhaustive database of more than 110 initiatives that we plan to continue expanding. Public input is welcome! We hoped to uncover global interest in data stewardship, but our analysis concludes that there is a pronounced geographic imbalance as to where alternative models (as described below) are hatched and to what extent they are currently on the radar of even seasoned open data and digital rights professionals and scholars worldwide.
Beyond a handful of countries in Europe, Canada, and the United States we did not find evidence that these theories hold high currency in other regions, or in other major languages than English. There are exceptions, and indeed many interesting ones. But as we continue to consider how new data governance approaches may offer true relief from the myriad of harms people do (and will) experience from highly centralized and discriminatory data power worldwide, we can only emphasize that far more diverse input, co-creation and research is necessary for the evolution of this field. For our part we will continue an open minded but critical interrogation of data stewardship (in theory and in practice) throughout the next several months. We’ll also be examining the sprouting ‘ecosystem’ of organizations, companies, and software developers that support innovation in this field. If you wish to be in touch with us, let us know.
As Mozilla, we have a particular interest in understanding how software and technology can be developed to benefit consumers while upholding values of equality and human rights. In better understanding stewardship, we wish to think strategically and collaboratively about our own role in the technology ecosystem to support bright ideas and real alternatives to the status quo.
- We see genuine potential in different contexts for data stewardship to help open new paths away from the dominant approaches employed by big tech.
- This is an emerging field. There are relatively few examples of scalable initiatives for more than a handful of data governance approaches that are frequently repeated.
- Different data stewardship and governance approaches are all mutually exclusive. They can be mixed and matched to accomplish a variety of goals.
- We see clear geographic and linguistic imbalances in the discourse surrounding data stewardship, alternative data governance approaches, and related legislation.
- There is a budding ecosystem of thought leadership and support for inspiring, incubating and testing new data governance approaches in practice.
Of the 7 data stewardship and governance approaches described below, the first six are the most commonly mentioned in more than 250 literature resources reviewed. The final one is a honourable mention, but each exemplify an interesting aspect of data governance. For each, we examine how they can be vehicles of empowerment for data subjects, like you and me.
Before you dive into this list of definitions, please know that the different approaches are not mutually exclusive and often seek to address entirely different objectives. In other words, if you were to create a new data stewardship initiative yourself, you might employ a number of different approaches in combination with one another. Alternatively, it’s possible you may have trouble discerning the difference between some approaches with very similar purposes. This is an emerging field and these descriptions are based on theoretical explorations, rather than clear cut models with definitions everyone adheres to.
What you will find here is a simple overview of each approach, including at least one initiative, organization or company that exemplifies it. Our aim is to make it easier to navigate the field and recognize key terms used by scholars and technologists. For each, we also link to a list of literary references on which our understanding is based. In sum, you can browse our catalog of literature, see what definitions we logged by others on this board, review our database of projects, and submit your own examples to participate.
Click on the numbers to read a description of the approach.