While global economies have sent their growth-obsessed capitalistic policy approach on a hiatus for the year, with even the disgraced dragon dropping its annual economic growth targets for the first time since the 1990’s, the competitive aspect of the battle against COVID-19 has not left the grounds of policy-making. Taiwan has surfaced as a recent beneficiary of the comparative analysis initiated by global media houses. The nation is being rightfully lauded for managing to contain the current number of active cases under 500, despite its close proximity and intimate relations with China, the epicentre of the crisis.
Besides proper screening, increasing testing capacity and mass insurance, the nation implemented a dynamic containment plan that required the government to partner with the local telecom operators in order to ensure that suspects were properly quarantined by tracking their GPS locations. The surveillance is said to be so precise that one asymptomatic carrier claimed via Twitter that the local police arrived at his doors within half an hour when he accidentally switched off his phone in the early morning hours, back in April.
During ordinary times, even a mild parliamentary discussion on tracking private data by the government would have been globally marketed as a sign of the nation becoming a digital dictatorship. However, the current crisis has demonstrated that perhaps drawing inferences from private data and using them as a public good has benefits that exceed the costs involved, while simultaneously upholding the privacy of individuals. (A public good is a non-excludable, non-rivalrous good, i.e., individuals may consume without paying for it and one individual’s consumption does not hinder that of the other individuals).
In order to correctly recognise the benefits of private data as a public good, one must acknowledge that the lack of information is a fundamental economic problem, in the non-textbook economic setup. Lack of resources then becomes a secondary issue in policy making, since a data inference needs to be drawn first to decide the direction of redistribution before subjecting it to any resource constraints. Often policymakers resolve the information problem by statistical sampling which is in itself expensive. Data can become quickly outdated which may lead to non-representative samples and other specification errors.
However, when digitalisation comes into the picture, it brings in better solutions to the information problem. It assists not only in policymaking but also in enforcing free-market equilibrium in certain markets by increasing the degree of market efficiency and allowing smoother real-time price discovery mechanisms, thus minimising distortions. An example would be E-NAM (Electronic National Agricultural Market), the online trading platform for agricultural goods, launched by the Indian government, which now has a membership of nearly 4.5 million farmers.
Other indirect and more relevant advantages of digitalisation include the large scale database of the digital footprints of a population. Presently, smartphones have become a very accessible device in even developing and emerging nations. The data generated by these devices is mainly with the concerned individual’s telecom operator, as well as other private parties that collect data from the users who install their mobile applications, e.g. Google, Facebook, etc.
While the private app developers have facilitated the birth of controversial practices like that of surveillance capitalism, by utilising the competitive edge provided in advertising avenues, the data generated can still be deemed an instrumental tool in studying various macro-level indicators about the population. For instance, by studying the pathway of the telecom antennae one’s device was connected to, one can easily track the real-time mobility of a population and generate migration patterns. Upon analysing the frequency and multitude of online transactions made in a certain period, one can even concretise their hypothesis about the direction of the economy in general.
If governments, like that of Taiwan, consistently manage to extract benefits out of aggregates of anonymised private data, they can manage to do so without violating individual rights as well as without robbing private benefactors off of the competitive edge generated by the data. The Economic Survey 2019, published by the Indian government, rightfully stated that data is of the people, for the people, and by the people. It acknowledged the lack of clarity and sophistication in the law specifying the ownership of data and elaborated upon the need to take advantage of the multitude of data that is generated. Due to data explosion, the marginal costs of data storage have fallen drastically, with one-gigabyte storage requiring a mere ₹3.48 now, as compared to ₹61,000 back in 1981.
Even dissemination costs are negligible owing to real-time transfers over the internet. The marginal benefits, which include evidence-based policymaking, targeted implementation of the same and augmentation of accountability, easily outweigh the costs involved. Of course, in order for these benefits to be realised, there needs to be uniformity in the data circulated. Many schemes have already been launched as an initiative to merge data, such as the ‘Samagra Vedika’ initiative by the Telangana State government in India.
The concerns about privacy are certainly valid since once the government gets its hands on the data; it may do with it as it pleases, which is why better laws need to be in place. Private data is very intimate individually, but collectively, it generates great value for the society, and hence, it is important to provide the data in an anonymised and aggregated form to the government. In the light of COVID-19, greater weight is added to the argument of involving public officials in the picture, not simply because we must track the cases and localise the spread, but also because it will help in conducting future studies to deduce patterns and give early warning signs. The debate is ongoing, but it is high time we make use of the data that is at our disposal to its full potential, in a manner that aligns with the population’s core values about the issue.
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