SUMMARY
While the rest of the world has entered into the 21st Century, more often than not, policymakers are forced to rely on incomplete, imperfect, and outdated information in their decision making
By leveraging computational computing solutions, policy makers could gather data from multiple companies and run algorithms to derive insights
Confidential computing is already used in mobile devices but hasn’t seen much uptick in the enterprise and GovTech space due to complications around using the technology
The Information Age has brought with it, new opportunities, new challenges, and new ways of doing things. In 2017, The Economist published a story which bluntly stated that “The world’s most valuable resource is no longer oil, but data.”
Since then, this saying has been repeated endlessly. If data is the currency of the world today—and the fuel for economic growth, important decision making, and indeed national safety—why, then, are public and political leaders failing to leverage data flows to inform their decision making processes?
The answer—security and privacy concerns. While the rest of the world has entered into the 21st Century, more often than not, policy makers are forced to rely on incomplete, imperfect, and outdated information in their decision making. This of course leads to suboptimal results for entire nations and regions. Technology, however, may have an answer.
Privacy Solutions For Policy Makers
Public policy making is a difficult task. Policymakers across the globe are expected to make decisions which will help them achieve the economic and social goals of their nation; against a backdrop of a rapidly changing local and international landscape. This means that policy makers are required to analyse economic trends and data points to ensure that their policies are the most appropriate ones possible—access to appropriate information, therefore, is essential to the creation of sensible and effective policy.
Traditionally, high-level historical information has been available to leading policy makers and government officials. However, as the rate of change across society and the economy have sped up—policy makers can benefit from access to real-time and detailed information necessary for policy formation to match the speed of change.
In the absence of such information, policy makers may come up with sub-optimal solutions that are based on outdated data points. For example, if a country wants to boost domestic manufacturing, relevant policy makers should know details around the quantity, price, supply, and demand of certain imported products. Much of this data resides with market actors, not with the government. However, sharing such sensitive and confidential data might not be possible market actors for numerous reasons, including confidentiality and risks of data leakages.
Privacy Concerns
A lack of assured privacy of information shared with government agencies is one of the leading reasons that enterprises are reluctant to provide sensitive data to policy makers. Let’s take the challenges faced earlier this year by the Government of India as an example.
Through its investment promotion division, the government asked automakers within the country to provide information on the source and cost of their imported components, including product details and their respective costs. The intention was to use this information to curb a perceived over reliance for imports on specific markets, and to build up strategic sectors of the economy. Not only would this benefit the public sector but also private market actors.
Unfortunately, due to the sensitivity of pricing data, automobile manufacturers were unwilling to share this information. Automobile industry insiders made it clear that privacy concerns lay at the heart of their refusal to cooperate with public authorities, stating that if details surrounding pricing and procurement strategy were leaked to competitors, it could prove to be detrimental to their business.
Technology May Be The Answer — Confidential Computing
Faced with this problem, there is a requirement for a comprehensive solution. Enter confidential computing! Confidential computing is a new form of privacy preserving technology which encrypts data while it is being processed. Confidential Computing also allows for data to be pooled across multiple sources to derive insights without sharing the underlying data between different contributors—that is, one company can combine its sensitive data with another company’s proprietary information to create a more holistic data set—without either company sharing any data or intellectual property it doesn’t want to share.
By leveraging computational computing solutions, policy makers could gather data from multiple companies and run algorithms to derive insights. This could be done in a manner which means that even the policy makers won’t have access to raw data—they would receive total outputs but not the isolated data sets input by each company. Since, the raw data is not shared, these data processing innovations safeguard policy makers as well as market actors from the risk of data leakages and breaches.
Confidential computing is already used in mobile devices but hasn’t seen much uptick in the enterprise and GovTech space due to complications around using the technology. However, we are increasingly seeing enterprise-ready solutions coming to the fore. For example, the Conclave platform simplifies working with confidential computing so that organisations can focus on business logic and utilising the key industry-level insights gained through their newly deployed computational computing solutions.
Looking Ahead: Data-Driven Policy
Such technological solutions could be equally used by policy makers to maximise the efficacy of the insights they use to make important decisions on a national level—and would have a profound impact on the economy and society at large.
By overcoming the data security concerns which plague the current information-sharing process which feeds into decisions of national and international importance, innovations in privacy preserving technologies such as computational computing may set the stage for a new era of policy making. Armed with tools fit for purpose, we may finally see our government officials make data work for them—converting the immense value it holds into tangible public benefits, which is something everyone can support.
