Designing a regulatory framework that ensures the safety of users and the public while facilitating the commercial use and consumer enjoyment of disruptive innovation is a challenging undertaking. This is particularly true in contemporary settings, where innovation is quicker and the global dissemination of that technology is much faster. The so-called “pacing problem” between innovation and regulation suggests that innovation driven by science and technology is accelerating, yet, simultaneously, federal and state agencies’ regulatory processes have slowed down as I discuss here. Given the intensifying pacing problem between regulation and innovation, regulators often struggle to keep up. The last two decades offer multiple examples of such regulatory struggles: fintech, genetically modified food, artificial intelligence, and, of course, driverless cars. Some evidence exists that the regulators are falling even further behind than the historical average because of the unprecedented exponential nature of innovation in this decade.
But a less-documented aspect of this issue concerns what we might think of as the basis or foundation of any regulation, namely some empirical facts about the technology being regulated and its likely social, economic or health effects. In this respect, regulation is always premised on a selection of relevant facts about a particular technology. Crucially, the selected facts are those that are seen as relevant by the regulators in deciding what, when and how they should make a regulatory intervention.
The “what” question concerns identifying the disruptive technology that must be regulated or requires regulatory reform. Demarcating the scope of a technology may not always be self-evident. For example, when should a trading algorithm be thought of as autonomous, rather than merely providing trader assistance? Facts about a particular technology are crucial for this kind of definitional judgment.
The “when” question concerns the timing of any regulatory intervention. This entails ensuring that regulation is not adopted so soon that it stifles or distorts technological development, but not adopted so late that problems arise as a result of the absence of effective regulation.
The “how” question is about the form and substance of the regulation. Should the technological innovation be encouraged, prohibited or restricted in some way? And what substantive rules or principles should be adopted to achieve this regulatory goal?
In each case, these policy judgments are made by politicians and bureaucrats based, in large part, on facts provided by experts. The delegation of regulatory decisions to a combination of democratically chosen politicians and bureaucrats/experts is one way of conceptualizing the distinctiveness of political modernity.
Policymakers are more interested in the identification of the relevant facts for rulemaking. Some of the relevant facts may be obvious. Other facts may be very difficult to empirically establish or may be contested, even by experts in that field. The task of establishing facts about new technology may be made difficult by the lack of an adequate sample or other reliable data on the effects of new technology. The “relevant facts” that form the basis of regulation are never going to be obvious or settled. The regulation of any disruptive new technology is always going to be reactive and based on an uncertain and politicized factual basis. Identification of relevant or irrelevant facts may also be distorted or otherwise influenced by the concerns of entrenched interests about new (and commercially threatening) technologies. To some degree, these kind of difficulties have always been around, at least since the rise of industrial capitalism and the acceleration in technological advancement that it facilitated.
An obvious solution to this regulatory dilemma might be to adopt some form of policy experimentation, i.e., testing different regulatory schemes and then comparing the results. But such experimentation poses a problem for regulators. Too often, “success” for regulators is defined in negative terms as the avoidance of catastrophe. Avoiding grounds for criticism inevitably results in an overly cautious approach (the “precautionary principle”). However, from the perspective of entrepreneurs and consumers, such caution can be a disaster or at least less preferable. The result is that, all too often, there is a disconnect between regulation and commercial and consumer access to that innovation.
Increased reliance on different sources of data surrounding new technologies can provide some signals or clues about what, when and, to a certain extent, how to regulate. Using such signals facilitates dynamic forms of regulation.
As I show here, of particular importance in this context is data relating to investment in new technology and innovation. A plethora of investment data is readily available to make accurate predictions regarding what the next “big thing” is likely to be. Such data can be used as an index or proxy of the necessity of regulation. Because start-up companies are the ones that usually challenge existing rules, laws and regulations, private data sources are widely available. The proliferation of the better hand-collected global databases on the market, such as CB Insights, PitchBook and Mattermark, can make an important contribution to a “data-driven” regulatory approach.
Investment data can help to develop a list of technologies and issues that need to be the focus of regulatory attention. From such data, rulemakers can get a better — and earlier — sense of which technologies are developing and which technologies need regulatory attention. This might then allow regulators to be more pro-active and avoid wasting resources on technologies that are unlikely to make it to market. It would also allow regulators to more accurately define the scope of a technology by focusing on the type of firm that is attracting attention.
Britain’s Financial Conduct Authority (FCA), in April 2016, broke new ground by announcing the introduction of a “regulatory sandbox,” which allows both start-up and established companies to roll out and test new ideas, products and business models in the area of fintech (i.e., new technologies aimed at making financial services, ranging from online lending to digital currencies, more efficient). The idea behind the sandbox is to provide a safe space for testing innovative products and services without being forced to comply with the applicable set of rules and regulations. With the sandbox, the regulator aims to foster innovation by lowering regulatory barriers and costs for testing disruptive innovative technologies, while ensuring that consumers will not be negatively affected.
This post comes to us from Wulf Kaal, an associate professor and the director of the Private Investment Fund Institute at the University of St. Thomas School of Law. It is based on a recent paper he wrote with Mark Fenwick and Eric P. M. Vermeulen, “Regulation Tomorrow: What Happens When Technology is Faster than the Law?”, which is available here.