Governance of Data Value

By Maria Savona
Professor of Innovation and Evolutionary Economics 

At exceptional times of public health emergency such as the present Covid-19 pandemic, Taiwan seems to have contained the spread of contagion better than other countries. The country has managed to digitally track individuals with symptoms and their contacts to contain the spread, with a mix of community based app, releasing data on symptoms and positions, and a fast reaction by the digital minister who has coordinated the government’s response. This seems to be an interesting synergy of decentralised and centralised governance of data for a relevant public purpose.

However, such initiatives also raise as many challenges as they overcome around personal data collection and storage, user consent, and surveillance and the extent to which individual data tracking is reversible once the emergence is over.

Interest in personal data has been growing unprecedentedly, with issues of privacy and power at the forefront of policy debates. Over the last decade the scale of data generation has reached a dimension that its management and control might have already gone well beyond the capacity of the very tech giants we are all feeding. Concerns around data governance, data rights, data privacy, and a sense of imminent impingement of our democracies, have been raised, though they might be too little and too late to lead to effective and timely action. One of the reasons why it is so, is that they seem to overlook the issue of concentration of equity value that underpins the current structure of big tech power, and the need to unpack their business models.

Economists have missed the opportunity to predict the massive concentration of data value in the hands of large platforms and underestimated the complexity of the political economy of data value concentration. Professor Savona proposes a novel data rights approach, that redistributes data value to achieve economic justice whilst not undermining the range of ethical, legal and governance challenges that this poses.

Key Findings

  • Personal data is closest to a club good. Data is an intangible yet durable asset as it does not become obsolete. Its value is in its scale.
  • The business models of big tech rely on a complex (and opaque) integration of layers.
  • Different governance models depend on what rights data require and for which purposes.
  • Governance of data value includes not only enforcing data taxation systems but also recognizing and protecting authorship’s right to data generators
  • The approach requires designing a novel institutional architecture for data value governance, that creates synergies between decentralized and centralized systems and maximizes the public use and value of data.

To find out more about this project, see the policy briefing “ Governance of Data Value ”.

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