By Darcy WE Allen, Chris Berg, and Aaron M Lane
The Australian Prime Minister Scott Morrison wants to make deregulation and cutting red tape the centrepiece of the COVID-19 economic recovery.
This focus is not just welcome, but essential. Entrepreneurs need room to experiment with new business models without being held back by unnecessary rules — as we argue in our recent book Unfreeze: How to Create a High Growth Economy After the Pandemic.
But at the same time, developed world governments have spent at least three decades trying to cut burdensome red tape — with little obvious to show for it. The regulatory state just keeps expanding.
Existing regulatory policies such as sunset clauses have not worked to stem the steady growth in regulation and regulatory complexity. We need a new deregulation strategy.
The term ‘regtech’ describes how technologies such as blockchain, artificial intelligence and the internet of things can assist with regulatory compliance.
Now is the time for deregtech: using frontier technologies to identify, coordinate and incentivise deregulation.
Deregtech leverages technology not for compliance, but for policy reform.
Adopting the principles of permissionless innovation, institutional diversity, and private governance will be vital if we are to get a rapid recovery from the COVID-19 crisis. Deregtech is about designing specific mechanisms that governments can deploy to identify and encourage that deregulation.
At least in Australia, every government on both sides of politics has promised some form of deregulation as part of their election agenda.
It turns out that deregulation is hard. It’s hard for two reasons:
- First: it is hard to identify regulatory reductions that are strongly beneficial but at the same time politically easy. Few regulations do not have a passionate constituency behind them. Few regulations are completely pointless. But in aggregate, regulation adds to a significant economic burden.
- Second: policymakers might talk a good game about deregulation, but have little incentive to deregulate. All the incentives go in the other direction — towards more rules, more regulatory interventions.
To solve the identification and incentive problems of reform, governments have increasingly implemented ‘regulatory policies’. That is, policies and mechanisms directed at the regulatory process itself.
For example, sunset clauses and regulatory impact statements force legislators to more closely assess or revisit the burden of a given regulation. But these don’t propel forward deregulation. Other approaches try to use the flow of new regulation to reduce the stock of existing regulation. New regulations can be made subject to ‘regulatory budgets’ or ‘1-in, n-out’ policies. But these are highly sensitive to how we measure regulations and their burdens.
The economy is a dynamic complex adaptive system, and as it evolves so too must the regulatory state. In the wake of the pandemic, which has accelerated many economic and technological trends, this has never been more necessary.
Deregtech can be directed at regulatory analytics to better measure and grasp the extent of the regulatory state. The RegData project, for instance, counts the number of ‘restrictive clauses’ in regulations. New measurements encourage innovation in regulatory policies and make new mechanisms possible. RegData’s associated QuantGov initiative provides the tools for open-source policy analysis, rather than this being done within government departments.
With strong regulatory analytics — analytics that can be verified by observers from outside the government — tighter controls over a regulatory budget can be introduced, and affected industries can have a better understanding of the state of regulation.
These systems are not just a way to monitor regulation — they are an infrastructure on which deregulatory efforts can be built.
For instance, can we apply machine learning to identify regulatory changes that are unobservable to humans? Can technologies be leveraged to create new measurements to analyse regulatory overlap?
At the same time deregtech can encourage regulatory experimentation to reveal the costs and benefits of rules in practice. New technologies can act as the foundation for regulatory experimentation, encouraging competition between jurisdictions.
Inserting greater competition into governance, such as in special economic zones and charter cities, encourages discovery. On a more granular level, regulatory sandboxes attempt to reveal local knowledge about where regulatory burdens fall and what they are inhibiting.
Deregtech also encompasses more extensive regulatory automation, driving the enforcement and governance of regulations into private platforms. Blockchain platforms, for instance, enable complete enforceability of particular trading rules by incorporating them into the platform.
Deregtech will reduce the regulatory barriers that hamper our transition to a decentralised, automated and digital post-pandemic economy. The technological inputs of deregtech are here with us today. Now we just need to build them.
Darcy W.E. Allen, Chris Berg and Aaron M. Lane are with the RMIT Blockchain Innovation Hub in Melbourne, Australia.