Science for Policy Scientific Advice Mechanism

This is probably the last podcast in the world to get round to talking about how AI is changing the world -- but we wanted to wait until we had the right people in the room to talk specifically about AI in relation to science, policy, and science-for-policy. If you like this conversation with Professor Andrea Rizzoli and Manuel Kugler -- and you will like it! -- stay tuned in the coming months, because we've got more AI-themed episodes up our sleeves.

It's sometimes easy to forget that even the most well-designed science advice institution, and even the most persuasive advisor, are still operating as part of a broad ecosystem in which both policymakers and the general public are exposed to vast quantities of ostensibly factual information of varying quality, much of it mediated through algorithms. In this episode, Caitlin Chin-Rothmann from the Center for Strategic and International Studies in Washington DC talks us through this broader context and how science advisors can adapt to it.

Why does evidence sometimes land and sometimes not? Why do some policies fail even though the evidence suggests they should succeed?  And what can we do about it? Saying "it's all about the context" is easy, but what does this actually mean? And more importantly, how can we make that into a useful insight in advance, rather than just a post-hoc justification for things not working out?
Vanesa Weyrauch and Leandro Echt have looked into this question in some detail, and their organisation, Purpose & Ideas, created a framework to tackle exactly these questions. In this episode, they discuss with Toby Wardman of the SAM not just why context matters, but what that actually means and what we can do about it.
 
Resources mentioned in this episode
Context Matters framework: https://www.purposeandideas.org/post/context-matters-but-are-we-prepared-to-build-on-this 

Politicians don't really have a great understanding of the citizens they serve, according to Michael Bang Petersen. In place of evidence from decades of psychological research, they tend to substitute their own instincts and common sense, together with more or less apposite fragments of behavioural science and economics. Nowhere was this more evident than during the early days of the Covid-19 pandemic, when opportunities to build trust and communicate science were squandered. Tune in and settle down for an intriguing tour of how things ought to be done.

When countries set themselves ambitious targets such as the UN sustainable development goals, then realise they don't have the evidence sources they need to monitor progress towards those targets, how do they square the circle? In some cases, it's with so-called 'citizen science', in which non-professional scientists gather and evaluate data — often on a big scale — to fill the gaps.
 
Dr Dilek Fraisl is an expert in using citizen science to address sustainability challenges. In conversation with Toby Wardman, she discusses both the value of using crowdsourced data, and the challenges that arise when presenting it to policymakers.

How do scientific models inform policymakers? How can they keep countries honest in international climate negotiations? When is uncertainty not so much of a problem? And how much does it matter if policymakers don't instantly grasp the ins and outs of a model which takes six months for scientists to learn? Join the SAM's Toby Wardman on a deep dive into what happens when scientific models meet international politics.