Article by Stefaan Verhulst and Julia Stamm:”…In the below, we consider 10 reasons why we need to reboot the data conversations and change our approach to data governance…
1. Data is not the new oil: This phrase, sometimes attributed to Clive Humby in 2006, has become a staple of media and other commentaries. In fact, the analogy is flawed in many ways. As Mathias Risse, from the Carr Center for Human Rights Policy at Harvard, points out, oil is scarce, fungible, and rivalrous (can be used and owned by a single entity). Data, by contrast, possesses none of these properties. In particular, as we explain further below, data is shareable (i.e., non-rivalrous); its societal and economic value also greatly increases through sharing. The data-as-oil analogy should thus be discarded, both because it is inaccurate and because it artificially inhibits the potential of data.
2. Not all data is equal: Assessing the value of data can be challenging, leading many organizations to treat (e.g., collect and store) all data equally. The value of data varies widely, however, depending on context, use case, and the underlying properties of the data (the information it contains, its quality, etc.). Establishing metrics or processes to accurately value data is therefore essential. This is particularly true as the amount of data continues to explode, potentially exceeding stakeholders’ ability to store or process all generated data.
3. Weighing Risks and Benefits of data use: Following a string of high-profile privacy violations in recent years, public and regulatory attention has largely focused on the risks associated with data, and steps required to minimize those risks. Such concerns are, of course, valid and important. At the same time, a sole focus on preventing harms has led to artificial limits on maximizing the potential benefits of data — or, put another way, on the risks of not using data. It is time to apply a more balanced approach, one that weighs risks against benefits. By freeing up large amounts of currently siloed and unused data, such a responsible data framework could unleash huge amounts of social innovation and public benefit….
7. From individual consent to a social license: Social license refers to the informal demands or expectations set by society on how data may be used, reused, and shared. The notion, which originates in the field of environmental resource management, recognizes that social license may not overlap perfectly with legal or regulatory license. In some cases, it may exceed formal approvals for how data can be used, and in others, it may be more limited. Either way, public trust is as essential as legal compliance — a thriving data ecology can only exist if data holders and other stakeholders operate within the boundaries of community norms and expectations.
8. From data ownership to data stewardship: Many of the above propositions add up to an implicit recognition that we need to move beyond notions of ownership when it comes to data. As a non-rivalrous public good, data offers massive potential for the public good and social transformation. That potential varies by context and use case; sharing and collaboration are essential to ensuring that the right data is brought to bear on the most relevant social problems. A notion of stewardship — which recognizes that data is held in public trust, available to be shared in a responsible manner — is thus more helpful (and socially beneficial) than outdated notions of ownership. A number of tools and mechanisms exist to encourage stewardship and sharing. As we have elsewhere written, data collaboratives are among the most promising.
9. Data Asymmetries: Data, it was often proclaimed, would be a harbinger of greater societal prosperity and well being. The era of big data was to usher in a new tide of innovation and economic growth that would lift all boats. The reality has been somewhat different. The era of big data has rather been characterized by persistent, and in many ways worsening, asymmetries. These manifest in inequalities in access to data itself, and, more problematically, inequalities in the way the social and economic fruits of data are being distributed. We thus need to reconceptualize our approach to data, ensuring that its benefits are more equitably spread, and that it does not in fact end up exacerbating the widespread and systematic inequalities that characterize our times.
10. Reconceptualizing self-determination…(More)” (First published as Data Reboot: 10 Gründe, warum wir unseren Umgang mit Daten ändern müssen at 1E9).