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A fair data economy requires rethinking and re-distributing data’s value

As a society, we must rethink and re-distribute data’s value in the public interest.

By Thea Anderson and Sushant Kumar, Responsible Technology at Omidyar Network

Over the last few decades, the data economy has developed, largely in the absence of governing norms and regulations. Major companies across all sectors — including banking, finance, energy, healthcare, transportation, and consumer goods — are increasingly becoming data-intensive businesses. And consumer and industrial devices are connected through the Internet at scale and with significance. In fact, 2/3 of the global population (5 of 7 billion) has access to a data-collecting, Internet-connected device.

Every time we explore the Internet or use an app we enter into a lopsided bargain: in exchange for access to services, we agree to the collection of our data. Data about us (our bodies, beliefs, behaviors, and transactions) is collected by businesses and governments — with few limits on how it is used. Because they control the means of data collection, they also control how data is valued and derive all of the resulting power and profits. This paradigm is not only unjust and undemocratic, but it also incentivizes them to collect more data than they need, use it in ways that don’t prioritize the public interest and evade accountability for the associated risks and harms. We need a new paradigm that is not built on opposition (us vs. them) but mutualism.

We’re not alone in this thinking. Many scholars, nonprofit advocates, lawmakers, and technologists have begun to question some of the underlying assumptions and shift mindsets as well as build evidence, new approaches, and a robust movement to design different data future. Omidyar Network is supporting the shift toward a more equitable data economy so that everyone can experience the benefits of the data economy and better outcomes in their digital and “real” lives. A new data “paradigm” or “social contract” would allow for a clearer framework for data rights, a better understanding of value creation and distribution in the data economy, and facilitate value creation in the public interest.

A critical task in front of us as a society is rethinking and re-distributing data’s value in the public interest.

In February 2020, the University of Cambridge’s Bennett Institute of Public Policy, in collaboration with the ODI, published a comprehensive landscape of existing literature and frameworks on the value of data. It concludes that “… most analyses agree that the value of data is not being fully realised or evenly spread. Economies and societies that find ways to unlock this value and distribute it fairly will be at an advantage.”

Data is…not like the others

Our current data economy is run by tech giants and lawyers who treat data like assets, land, or labor, all of which are inherently different from data. Instead, we need a multidisciplinary (e.g. economic, ethical, political, technological, and cultural) framework to better think about why data is unique and how it needs to be governed differently. Understanding how the value of data is created, captured, and distributed is critical to governing the economic rights associated with data.

We also believe it is especially important to understand the social value of data in domains where large positive societal benefits are possible, such as public health and mobility. Today, understanding of the value of data is limited to the private sector’s profits generated from data. Omidyar Network is specifically supporting research and discourse on the value and nature of data with the aim of harnessing greater value creation in the public interest.

For example, we supported research by the Bennett Institute of Public Policy to pilot methods for valuing data commercially and socially. Professor Diane Coyle and Annabel Manley summarized various methods being used in practice to value datasets and how they compare. The study found five main approaches:

  • Cost-based: this approach says data is expected to be valued at least as great as its cost (to generate, collect, store, replace, etc. the dataset).
  • Income-based: this approach is based on the estimated revenue streams being generated by, for example, the sale of data-driven marketing analytics or information services.
  • Market-based: this approach requires looking at data marketplaces and publicly-available pricing; the impact data has on market capitalization (aka the total value of a publicly traded company’s shares), and the volume of global data flows.
  • Impact-based: this approach is based on the outcomes data has, including the value of improving insight, helping entities make better choices, and generating jobs or broader economic growth.
  • Stakeholder-based: this approach says the value of the data goes beyond the firm and its profits, employees, customers, supply chain providers, etc., and extends to the wider public.

The authors noted the importance of valuing data thoughtfully so policymakers can understand how data affects the economy and society, so they can govern the collection and use of data meaningfully, and so they can determine the appropriate level of investment.

Context matters

Once data’s value has been considered, we need practical tools to determine how to equitably generate and shift value toward the public interest and standards to hold people and organizations accountable.

“There are many proposed methods to value data, but no ideal or agreed upon methodology has yet emerged to measure it,” said Robert Fay, managing director of digital economy at Centre for International Governance Innovation (CIGI). “Largely because data’s value depends on its usefulness in a particular context and that context is framed by governance — the rules and regulations that determine how data can — and should be used.”

Fay also stresses that governance must be inclusive and reflect differing voices and values around the collection and applications of data.

Earlier this year, Dr. Patricia Meredith, a senior fellow at CIGI, called for a fresh approach to data valuation by the accounting industry. She argues, “current accounting standards are not suitable for the intangible assets that fuel the data economy.” Further, “without a shift in mindset that recognizes intangible assets and reflects the new economic reality, challenges will arise in making loans and investments and taxing value creation. The accounting profession cannot act alone in making the shift.

Omidyar Network is partnering with CIGI, an independent, Canadian, non-partisan think tank, to put theory into practice on how to value societal and private data. To lead these efforts, CIGI will network scholars and practitioners across industries, including accounting, economics, law, computer science, political science, and ethics. This network will ensure new standards consider sector-specific needs for governance and regulation and how to value data across national, regional, and international borders. It is our hope that the ideas, methodologies, tools, and recommendations they generate will lead to actual shifts in practice and the data paradigm.

Data valuation affects everyone
Today’s mental models about data preference extractors over technology users, limiting data’s full societal value and slowing innovation across the economy. History tells us this is not sustainable. The economy will break when it becomes too lopsided or disproportionately benefits companies and institutions with outsized wealth and power over regular people. Extraction is a losing game for corporations (well, all of us) in the long run.

Greater appreciation of data’s value in the public interest and access to practical tools to channel its value will promote better decision-making by policymakers and ensure fair value for all stakeholders in the data economy.

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