Social Credit Systems And Platform Economies
China’s social credit system has been instrumental in enabling public behavior to be in sync with what the government needs it to be for a post-covid economy. Part of the reason citizen monitoring and incentive design has been relatively easier to implement in the context of COVID for China — has been their social credit system. The implementation of the official version of China’s Credit Scoring system used by the government may not necessarily be as dystopian as western media portrays it to be. It is only when it is clubbed with private enterprises and the resources they hold alongside their ability to restrict platform access that the system becomes deadly for the average citizen in China. What needs to be noted though is that much of technology enabled platforms already exploit data to make profiles on its users. Ebay for instance relies on reviews while Uber decides on which driver comes to pick you up on basis of the review previous drivers have left on the user. We live in an age of microeconomics that update in real time on the basis of data points that are generated, stored and shared within platforms like Uber. They rate its users in a fraction of the time traditional rating agencies take and monitor user behavior in a far more dystopian fashion.
This matters in the context of India as we turn to an increasingly digital nation. The groundworks for a dystopian data driven society that excludes users erroneously is already here between the rise of Aadhar and centralised payments networks. India does not have a public credit scoring system yet but in the absence of strong data-privacy and emerging awareness from users of how their personal data can be used against them: we may be setting our citizenry up for exploitation. This is not to raise alarm and suggest that a national scale credit scoring system should never be allowed. In order to make a transition towards a $5 trillion economy, India needs to embrace the tools of the future which includes open-distributed ledgers (blockchains), big-data and data-streams between entities. What needs to happen in parallel is the groundworks to enable users to use it to their advantage.
Going Beyond Financial Data
Users can be discriminated against in a system where only enterprise and governments have a say on how data is used. One way this already plays out is when Aadhar login systems fail to function when users are looking to authorise themselves. As we have seen in some of the surveys we did in the past, lack of access to personal data is a leading reason for individuals not switching jobs. While the rise of data fiduciaries draws clear reasoning on when and how often a person’s data will be accessed, it’s restrictive on what kind of data can be stored. Currently it looks only at financial data. This may fail to create a holistic view on the individual. Allowing enterprises to have free reign on all forms of personal data may not be desirable: it could be used against the citizenry by creating profiles of them. We propose, that the same model can be further extrapolated for multiple types of data. Purchase habits, fitness data (from phones), media consumption and location data could be shared and tradeable in an open-market with the passage of time. According to a paper titled The Non-rivalry of Data (Tonetti), an efficient market involving data-sets can be made possible only when enterprises within it have commercial access to data owned by one another. This “transfer” of data may not happen through enterprises sharing it with one another but rather by consumers willfully sharing their datasets with them as part of an economic transaction. If users are empowered to port, sell and retract access to their data, firms will be competing on a more even plane instead of competing from the position of a data monopoly. More importantly, it will spur innovation among small and medium enterprises who until then did not have access to the data sets in the first place. Directly sourcing data from individuals will also create a “free-market” wherein individuals choose which firms to support on basis of how efficient they are with privacy.
Data-markets as groundworks for a $5 Trillion Economy One way to think about why this is necessary would be to understand it from the lens of wasted resources. This is, the data that is not digitised or made available for consumption by third parties. Businesses processes and models can be evolved from digitising and creating a marketplace of data where the state, enterprise and average individual has equal footing. As of today, instead of being a regulator, the state is tied up with being the entity responsible for storage of data while enterprises have far too much leeway in how it uses this data against users. The other is that while early expenses for digitising and creating an open-data marketplace for all kinds of data will be heavy, the benefits will be manifold. Smaller, more nimble teams could use this to accelerate healthcare analysis, education, detection of fraud and even self-driving cars as the complexity of data in these marketplaces evolve. More importantly, the view that India can somehow become a $5 trillion economy without creating the groundworks for the transfer, storage and trade of a modern data commodity like data could be highly outdated. A major part of what will take us to being a 21st century economic superpower will be the drastic reduction in marginal cost of production that comes from switching from an economy that focuses heavily on physical manufacturing to digital production.
This transition towards the digital will however not happen on its own. The average person needs to be empowered with the means and mechanisms to store their data and allow access to it. One way this is already playing out in China is through their debit cards focused on their digital CNY initiative.
Taking into account all these factors:
We are proposing a consortium that involves key market players, state entities, institutions and communities that manage the open source skill based (moving beyond financial transactions) social credit system (SCS); whose data is distributed and ownership lies with the individuals. If such a technology is rolled out in India, what impact will it have on individual, societal, market and state level? Our objective analysis on this lies here.
References: 1. China’s social credit system — https://www.wired.com/story/china-social-credit-score-system/ 2. Non Rivalry of Data — https://www.aeaweb.org/articles?id=10.1257/aer.20191330 3. Europe’s data privacy crackdown — https://www.vox.com/policy-and-politics/2018/4/5/17199754/what-is-gdpr-europe-data-privacy-facebook