**So, Niels Mede, tell us: who are you? And what do you do? ** I am a post-doctoral communication researcher in the Department of Communication and Media Research at the University of Zurich, and until recently, I was a visiting research fellow at the Oxford Internet Institute. My research centers around science communication, with a focus on public attitudes toward science and communication about science on social media and beyond.
Academic research enjoys a high level of trust among the society in Germany, not least because of its autonomy that is granted by the constitution. At the same time, the public expects research to leave its “ivory tower” and take on a more active role in addressing complex societal challenges such as the Covid-19 pandemic or climate change.
Abstract Artificial intelligence (AI) is increasingly contributing to scientific breakthroughs in many fields. It is also clear that openness and cross-disciplinary collaboration are becoming key features of the process of modern science. Yet, we know little about the intersection of these two developments – whether and how AI may shape openness and collaboration in research.
For most liberal democracies, scientific expertise is an important ingredient of political decision-making. Scientific forecasts and assessments of, for example, poverty or social mobility, the impact of exhaust fumes on public health or the risks of viral outbreaks, help governments to weigh arguments and decide on policy measures. But how exactly does scientific knowledge make its way into politics?
Evidence-based policy advice and evidence-based policy-making constitute two related concepts that are widely Evidence-based policy advice and evidence-based policy-making constitute two related concepts that are widely supported. Both political and scientific actors argue that political decisions should be based on scientific evidence in order to manage societal problems;
Since the 1990s, health experts have anticipated that we would be hit by an influenza pandemic in the not-too-distant future (cf. Caduff 2015; Lakoff 2008; Weir, Mykhalovskiy 2010). While we may have thought of pandemic primarily in terms of Covid-19 over the past two years, influenza pandemics have long represented the paradigmatic case of pandemic preparedness planning.
In academia, there is a clear understanding of how the quality of research work is assessed. This is done by academic peers in a peer review process. It is only then, through the discourse of expert opinion, that it is possible to determine whether the quality of a paper is good or poor. The peers themselves also determine when science is excellent without using formal criteria or even indicators. Science thus has a monopoly on quality;
***The COVID-19 pandemic experiences of many different countries have shown how an exceptional need for research evidence has led to rapid new deployments of scientists in advisory roles to aid policymakers in making evidence-informed decisions. (1) This has helped us learn how science advisors experience, and try to manage, the challenges of insufficient, evolving, and conflicting evidence as they work to inform public health decision-making.
What is trust and why is it important at the science-policy interface? How can you build trust when working with decision-makers? And what can you do when trust has been compromised or lost?
