When in 2016 Michael Gove claimed that “the people of this country have had enough of experts,” the great and good were shocked and alarmed.

“In certain segments of the population, there is undoubtedly a considerable distrust of experts,” economist Richard Portes lamented. Gove was seen as fanning these flames — of emboldening an anti-intellectualism that would trash the role of expert knowledge in policy making. For offended academics, the opposite of expert-driven policy was populist politicians ignoring evidence entirely.

That was always a false dichotomy, of course, as the pandemic proves. Specialist expert failure these past two years has been pervasive, whether in epidemiological modelling or macroeconomics. In fact, “the people who reasoned best across multiple domains, and made a lot of the right calls, were often generalists with significant experience talking to both political decision-makers and the educated general public,” says American public intellectual Tyler Cowen.

This observation highlights an important point. The opposite of deference to experts is not, in fact, populist demagoguery. As American thinker Russ Greene has written, an alternative to either expert tyranny or ignoring experts entirely is a culture where generalist intellectuals with broad knowledge, data skills, and deep curiosity challenge expertise and hold it accountable. We’ve seen this through the pandemic, where intellectuals have often bested public health specialists in getting the big calls right.

The World Health Organization amplified false Chinese statements about COVID-19 initially, while it dragging its feet on declaring an international emergency. Pandemic experts here clung to flu epidemic plans too, ignoring observable COVID-19 successes in East Asia and so ruling out any similar possibility of test-and-trace containment in the UK from the off. Most public health experts then pivoted to being extremely pro-lockdown, but stuck rigidly to this even as the context, and so the costs and benefits of restrictions, changed with the vaccines and omicron.

Epidemiologists proved especially stubborn. Their modelling usually ignored the role of voluntary behavioural change entirely, so erred on the side of assuming catastrophic public health outcomes absent government mandates and restrictions. Hence, Freedom Day was dubbed “criminal” by scientists, while the government’s scientific advisers called for more restrictions last Christmas. Both proved wrong in retrospect.

At various junctures, it’s instead been intellectually curious generalists who’ve got to grips with the data or trade-offs better — the sort of people former Boris Johnson adviser Dominic Cummings advertised to hire into Downing Street as “weirdos and misfits.”

In mid-March 2020, Silicon Valley’s Tomas Pueyo used simple modelling to slap down government adviser and epidemiologist John Edmunds, who at that time claimed this was not even an emergency. The model Caprice, who surmised that East Asia was dealing with the COVID-19 outbreak better than Europe, famously endured disdain from Dr. Sarah Jarvis for her advocacy of the South Korean approach on TV.

Public intellectuals such as Canadian economist Alex Tabarrok, who is not a scientist, advocated for significant liberalisations on testing, vaccine and therapeutic approval, observing that these could alleviate the pandemic’s costs much more efficiently than broad lockdowns.

The UK’s biggest success, of course, remains its vaccination program. It was venture capitalist Kate Bingham, an outsider, who oversaw a new taskforce to procure them. Since then, many amateur epidemiological models from mathematicians and economists have proven a better guide to UK infections and deaths than the government’s modellers, who now protest too much that their model outputs should not be considered predictions.

None of these examples of expert failure or generalist intellectual wisdom prove that expertise wasn’t needed or valuable in the pandemic, or that any Tom, Dick, or Harry could have undertaken decent analysis or dreamt up effective pandemic policy. The point is, there are serious pitfalls to giving highly specialised experts quasi-monopoly status over any policy, particularly for something as all-encompassing as COVID-19. Far from trashing expertise, a culture of open scepticism from non-experts can often significantly improve knowledge.

First, generalist intellectuals often think more holistically than specialist experts. “So-called science advisers often represented one discipline when what was required was integrating insights from many disciplines with careful consideration of tradeoffs and uncertainty,” economist Tabarrok told me. The pandemic touched almost every aspect of life. The idea that we could just “trust the science” and leave scientists to determine appropriate policy was always absurd.

Second, curious generalists do not tend to face the same reputational costs of errors that specialist advisers face, so can look at data more dispassionately. Particularly after getting the first weeks of the pandemic wrong, public health officials faced clear pressure not to downplay the virus later. The incentives for them in giving advice to policymakers were asymmetric in favour of always bigging up the worst case scenarios for deaths.

Finally, highly credentialed industries can get captured by groups that stifle various viewpoints, insisting on a level of conformity. Evidence from the U.S., for example, suggests that infectious disease scientists are the most left-leaning of all the scientific disciplines, implying more faith in paternalistic government policies in determining outcomes over regulatory liberalisation or voluntary decisions by individuals. A culture of intellectuals can counteract this groupthink or herding.

It’s common for Twitter users to mock how the platform moves from being a home for experts of epidemiology one week to a panel of Ukraine experts the next. But across a population, this curious intellectualism and free debate is something to aspire to for better public policy, not bemoan. Outside scrutiny, picking over experts’ ideas and forcing them to justify their thinking helps make analysis more holistic, checks groupthink, and counters the incentives to opt for policy based on catastrophising. Being sick of certain experts need not mean giving up on the pursuit of truth.