Who should govern our data?

• The Internet and its data lie in the hands of very large tech companies and ownership of data have become the currency of the future.
• Public agencies have an ‘authority access’ to the raw non-personal data and aggregate non-personal data held by other private players.

About

• When the Internet was evolving, techno-enthusiasts ushered in hopes of a world where knowledge and information would be abundant and free from the hands of the elite.
• The Internet would be democratic, giving everyone open and equitable access.
• Yet almost two decades later, this dream is barely alive.
• Many governments and inter-regional entities have been trying to undo this indiscriminate accumulation of data as well as protect data privacy by conceptualizing different forms of data governance systems.
• The authors of the paper, “Governing the Resource of Data: To what end and for Whom?”, analyze the different approaches to data governance.
• They argue that data needs to be fundamentally understood as a form of social commons and that there should be thorough re-structuring of the data economy.
• They propose a semi-common approach as the most pragmatic way to govern data in order to foster innovation and ensure equitable access.

Platform capitalists

• A handful of ‘platform capitalists’ now control the Internet.
• Platform capitalists are those who take advantage of their first-mover privilege by rapidly expanding across the digital landscape.
• They then offer themselves as a platform for third-party players for a price (Meta, Amazon, Microsoft, etc.).
• These companies retain and expand their control through data accumulation and extraction.
• The importance of data accumulation in the digital economy cannot be overstated. With the advent of the Internet of Things (IoT), ‘smart’ devices and related technologies, the possibility of data goes beyond that of the virtual to even the physical and social.
• Platform capitalists have unbridled control over the data economy leading to exclusion and under-optimization of the data for common good.
• It forestalls the prospects of smaller businesses and data communities.
• Additionally, since most of these companies are based in the West, it leaves developing countries to fend for themselves, left out of their own data’s immense possibilities and uses.
• The commodification of data has led to a finders-keepers logic that undermines human rights and encourages illegal data mining and profiling.

Efforts to govern Data

• State regulators have been trying to find a solution to better re-distribute and govern data structures.
• EU’s individualist policy: In this, individuals have ownership rights of their own personal data (for concerns on privacy) but their non-personal data (data that does not have any personal identifiers) is seen as the property of the data processors/collectors.
  • There are multiple issues with this approach.
  • Assuming that there is no privacy risk with non-personal data is flawed.
  • It also does not offer an answer to how data can be equally redistributed.
• Data stewardship: It refers to any institutional arrangement where a group of people come together to pool their data and put in place a collective governance process for determining who has access to this data, under what conditions, and to whose benefit.
  • It can also take the model of a public-private partnership where private data can be used for governance issues and policies.
  • The EU’s proposal for “data altruism organizations” which will enable the pooling of non-personal data for non-profit, “general interest” purposes and the World Economic Forum’s ‘Data for Common Purpose’ initiative are plausible examples of such an arrangement.
  • The goal is to increase data-based value creation for optimum use.
  • It remains to be seen whether these collectives can really unlock data’s potential.
• Such initiatives would need proper state-of-the-art infrastructure.
• Most countries in the Global South would be at a huge disadvantage as they do not have adequate equipment or resources.
• Data stewardship remains, therefore, an ideal solution while not exactly pragmatic.

The semi-commons approach

• Data has three layers.
  • Semantic layer: has the encoded information.
  • Syntactic layer: represents the information as machine-readable datasets
  • Physical layer: infrastructure through which one extracts data.
• An ideal data governance structure should prevent the possessors of the syntactic and physical layers from having exclusive rights over the semantic layer.
• A semi-common approach to data governance seeks to balance public and private claims to data.
• It recognizes data as social commons where first movers do not get exclusive rights.

How semi-common approach can help?

• Data holders can only have non-exclusive rights over the base layer of data (raw non-processed data).
• They can use and generate profit through it but are required to share data as other data seekers are entitled to accessibility in a semi-common approach.
• Data seekers can have access to raw non-personal data and aggregate non-personal data.
• However, this access is not an unconditional right. Different data seekers have different rights over the kind of data being sought.
• Private organizations can conditionally access raw and aggregate non-personal data.
• These conditionalities will have to be streamlined with the larger economic and social policies of a country.
• A semi-common approach would need a thorough re-ordering of the current way in which data is hoarded and kept under the exclusive ownership of platform capitalists.
• One would need to build an equitable data market that encourages production through cooperation.
• Furthermore, a semi-common approach would help foster data-driven solutions and innovation in sectors that desperately need it.
  • For example, NITI Aayog had commented that the agriculture sector, which desperately needs more data-driven innovation, would only have a mellow response from private AI players due to low profitability in comparison to other sectors.

Conclusion

Therefore, a semi-commons approach, in order to be actualized, calls for a thorough change of perspective wherein data should not be thought of as the exclusive property of one person or company but as a form of social commons which needs to be properly regulated and redistributed

Exam track

Prelims take away

• The semi-commons approach
• Data protection bill, 2019
• EU
• NITI Aayog