Promise and Pandemic: Reshaping Science Advice (for INGSA 2021)

Some thoughts ahead of my opening plenary for the International Conference on Science Advice to Governments INGSA 2021 plenary (https://ingsa2021.org/day-1)

Historically, science advice was shaped by events (e.g. the oil crisis led to the setup of US Dept of Energy). The ongoing pandemic is likely to influence the future of science advice to governments. Now, science advice is not a straight process where scientists describe evidence, and then policy makers act on it. Instead, we get a divergent and at times counterintuitive range of policy outcomes across countries. This is because decision makers take into account political constraints, resource constraints, value divergences and other trade-offs in addition to scientific evidence. We may need science advice to meet decision makers as humans who are prone to biases and pressure.?

One suggestion is to change the type of “science” and “advice” in peacetime and crisis modes.

Peacetime mode - advice? Crisis mode - advice?

Natural sciences “Classic” science advice as. Balance between credibility and rigor

technical input to regulation, versus timeliness and urgency.

large national programmes.??

Nat. Sci + Soc Sci Identify library of risks with ?

+ Engineering cross cutting policy implications.

?

In the table, the upper left quadrant is “classic” science advice - technical input to regulatory agencies or large national programmes, and science here typically denotes the natural sciences. The process is meant to be slow and deliberative, and not a good fit during crisis.?

The right quadrants are where policymakers find it hard to balance between credibility and rigor versus timeliness and urgency during crisis mode, if the science is uncertain. For example, we risk confusing the public with technical caveats to protect scientific rigor. Science gives us vaccines, but pandemics are social. Where there are social spill-overs, we need to marry natural sciences with social sciences and a healthy dose of engineering so that we can scale up solutions like trace/test. Having said this, it is very hard to get this balance right and both science and policy-making come out looking poorer for it. What if instead we invest in building up resilience and identifying blind-spots upstream during peacetime??

This means investing in the lower left quadrant, such as assembling a library of risks (e.g. a Carrington event) with cross-cutting implications requiring a team from natural, social sciences, engineering and policymakers. Run small scale experiments to help identify blind-spots and build out response capacities early on. Some of this may include cross-border capacities like regional vaccine production capacity, more coordination among scientists in a growing g-zero world. Trust built up during peacetime through these networks, information exchanges with clear rules of engagement helps to narrow perception/expectation gaps and facilitate crucial two-way communication the system needs to do well when crisis hits.?

Science-policy alignment can also be a double-edged sword if it is seen to politicise science, but this can be mitigated with safeguards to avoid groupthink and institutional capture.