A pandemic that “left no country untouched” and “upended health systems” even in the world’s most developed nations, those were some of the words used by the World Health Organization to describe the COVID-19 crisis. The impacts of this crisis left almost no sector intact, rippling through the realms of public health, the economy, social and psychological welfare, transport, among many other sectors. Such hard-hitting and large-scale crises naturally carry significant challenges for policy and governance, to which a burgeoning body of policy and governance research attempts to find remedies. Here I focus on salient regulatory implications spurred by the need for learning in the context of COVID-19 policy responses.
At the outset, we need to to take a step back and consider the policy landscape of the COVID-19 crisis – we shall then see how policy learning and regulation are entwined.
Over the years, researchers have observed the concepts of “wicked” and “super wicked crises” emerge (though the two concepts are not identical, they come quite close for the purposes of our discussion). Such crises share a few core characteristics, such as: stringent temporal constraints (i.e., time is running out), complexity and ambiguity (i.e., no clear set of solutions exist and problem synthesis is challenging), low tolerance to failure (i.e. policymakers have no right to be wrong), and each solution we attempt significantly alters reality and discounts the remaining set of solutions available. Furthermore, such crises do now allow for an immediate test of success (i.e. we cannot immediately know if we have got it right).
Unfortunately, the process of learning in complex systems to formulate effective regulatory responses (i.e., largely policy learning) is neither simple nor straightforward
In such conditions, policymakers and decision-takers need to activate an intensive process of “learning” in order to formulate adequate regulatory responses. Learning enhances sensemaking. It enables policymakers to better understand complex problems, and thus better respond to them. That is the logic: let us learn so that we are able to better respond, Unfortunately, the process of learning in complex systems to formulate effective regulatory responses (i.e., largely policy learning) is neither simple nor straightforward. It also does not just come in one variety. There are various modes of learning, a myriad of recipes on how to do it, and debates on what actually qualifies as learning and learning quality . We can learn the wrong lesson about regulatory lockdowns, for example, or the lesson is efficient in terms of resource usage, but it does not meet our good governance criteria.
Claire Dunlop and Claudio Radaelli have introduced a typology that helps us identify functional modes of learning for different contexts, and separate them from the others. They consider four main modes of policy learning: epistemic learning (from scientists and experts), hierarchal oriented learning, bargaining-oriented learning, and reflexive learning. Identifying a highly functional learning mode from the aforementioned ones, this model is based on two main dimensions: problem tractability and certification of actors. Problem tractability describes the degree of uncertainty surrounding the problem at hand, and certification of actors describes the degree to which a socially certified group of experts (individual or institutional) exist to provide insights on the problem at hand. Now, looking at COVID-19, we see a problem of low tractability (i.e. high uncertainty) and technical complexity as well as a high certification of actors.
The COVID-19 crisis has shown the need for broadening the horizon on what we mean by “learning from experts” in providing regulatory responses
Though learning from experts is an established approach to this crisis, it is not a straightforward operation. The COVID-19 crisis has shown the need for broadening the horizon on what we mean by “learning from experts” in providing regulatory responses. In many cases, we have seen that the sole or almost exclusive reliance on single strands or perspectives of expertise driving responses to such ambiguous multi-dimensional crises might not be sufficient. Broadening the horizon on what we define as “expertise” takes us in two main directions. Vertically (intradisciplinary) and horizontally (or interdisciplinary).
On an intradisciplinary level, policymakers need to assimilate scientific advice from a range of varying opinions within the core discipline informing regulatory options (be it medical in the case of COVID-19). Regulators must deliberate with medical experts and epidemiologists arguing different perspectives on potential courses of actions (e.g., advocates of lockdown as well as advocates for a controlled no-lockdown). Such an approach allows for the integration and evaluation of multiple perspectives as well as safeguards against pre-established sensemaking frames, political priorities, biases and policy legacies.
On an interdisciplinary level, the exclusive reliance on medical scientists and experts might not be sufficient to yield effective policy responses to a large-scale hard-hitting crisis with significant social, economic and psychological implications. Though predominantly medical, COVID-19 regulatory responses (such as social distancing, staying home, regular disinfecting, etc.) are embedded within a larger social context where the public’s acceptance and compliance play a critical role in saving lives. Here, research calls for a feast of expert interdisciplinarity of multiple dimensions. Not only that we need a set of diverse medical and epidemiological experts (with varying perspectives), we also need to involve social, behavioural and economic experts (among others) to be able to adequately interface with the multi-dimensionality of this crisis. The lack of such multi-dimensional expertise approach has caused cause critical flaws in COVID-19 policy responses. In some countries, there was growing depreciation of compliance to policies and guidelines. This has led in many cases to large-scale breaches of COVID-19 control regulations, which subsequently worsened the epidemiological situation as we’ve seen repeatedly in Belgium for example.
Regulation is particularly critical during such crises for various obvious reasons. Here, I would like to focus on two levels of regulation: An external outward facing level, and an internal inward-looking level.
Naturally, epistemic policy learning positions epidemiologists and medical scientists as primary producers of standards. They inform policymakers on key actions needed. For example, a final recommendation on critical thresholds for viral reproduction rates, hygiene standards (such as wearing of masks, distancing standards, disinfection, etc.), epidemiological characteristics and vulnerable groups, etc. Along with expertise from other domains, this results in creating policy tools and governance arrangements in regulatory forms relayed to the public. However, epistemic policy learning is no straightforward endeavour as there are significant complexities to manage in order to effectively cultivate knowledge under conditions of crisis.
This calls for an innovative approach for inward-looking regulatory frameworks. Working with “expertise” under conditions of ambiguity, uncertainty and intense scientific contestation (natural in early stage knowledge development) can be very problematic. This brings forward challenges such as identifying relevant expertise, governance of deliberation among several expert perspectives both within and across disciplines as well as adjudicating insights from inherently different epistemologies within and across fields of expertise.
Under these conditions, a clear, deliberate and established regulatory approach can be critical for the fruition and utilization of expert advice. The lack thereof not only compromises the inner workings and quality of expert insights as a core driver for policy responses. It also compromises the public’s perceived validity, acceptance and compliance of such advice. Here, one would be remiss to overlook the link between internal regulation of expert deliberation and the external public-facing regulation. Looking at different COVID-19 responses, we can see how several examples of malfunctions of internal regulations have manifested themselves in catastrophic public-facing regulation issues.
The lack of a clear well-established regulatory approach to cultivating expert advice has plagued the English response to the pandemic
Take the case of England, the lack of a clear well-established regulatory approach to cultivating expert advice has plagued the English response with accusations of suppressing relevant expertise, cherry-picking self-serving expert advice, creating an epistemic black box that cannot be challenged or scrutinised and a phenomenon of public distrust in government action ultimately costing lives. Another case observed in Belgium, (a country with a conventionally highly fragmented and complex regulatory structure) shows how the lack of an overarching inward-looking regulatory framework results in fragmented isolated epistemic islands. With a labyrinth of COVID-19 committees, relevant expertise can be overlooked. This also resulted in the inability to balance critical interdisciplinary insights forcing the government’s own group of experts on the lockdown exit strategy to quit after claiming that “all balance is lost” when it comes to integrating their insights with those from medical experts.
While the two regulatory levels can be significantly different when it comes to tools, audience and governance arrangements, they are joined by the very nature of policy learning modality that underpins the regulatory response. In such cases, it’s crucial to have a clear, accountable and publicly defensible regulatory framework not only in terms of policy rules but also and more fundamentally rules about expertise management and expertise integration. This becomes particularly critical in a world of conspiracy theories, and widespread scepticism against science. Whilst researchers are encouraged to invest intellectual resources in refining the scope conditions and characteristics of such regulatory frameworks, recent research and observation give us a glimpse into broad features to observe. Such features include the emphasis on transparency, superordinate structures, integration management and boundary-spanning tools.