Special Track 3
Title: Arguments, algorithms and tools: what do we need to shape policy and confront misinformation post-pandemic?
Jaron Porciello, Cornell University (corresponding author)
Ulrike Hahn, Birkbeck College
Stephan Lewandowsky, University of Bristol
The COVID crisis has turned the world upside down. It has revealed societies’ fissures and pressure points as it has mercilessly revealed any lurking weaknesses in our existing systems and structures. The public and scientists have witnessed an explosion of scientific research across all disciplines –much it of understanding the nature of the virus itself—in addition to a well-spring of data science, meta-science and science communication, some of it drawing on state-of-the-art AI and machine learning tools designed to help scientists and non-scientists keep current on the explosion of knowledge.
The pandemic has brought into sharp focus questions surrounding the development, discussion, and diffusion of research. The wider issues they raise as they pertain to the ways science is and could be conducted in online information environments, whether this is among scientists themselves, in the interaction between scientists and policy-makers, or in interaction with the general public.
This special track will consider what we have learned as we emerge from the COVID-19 pandemic. What are the tools, systems, data governance models and types of experts that we need to foster science and help maximize its societal benefits well beyond the pandemic context? We will pay special attention to the role of media in the dissemination of new scientific findings alongside misinformation: expediency, if nothing else, during the pandemic has necessitated the use of extant social media platforms for science-to-science, science-to-policy, and science-to-public discourse.
We will bring together a mix of contributed papers and panel discussions to explore the relationship between discourse quality and algorithmic mediation. More specifically, we invite contributions on the following topics:
- COVID-19 required urgency to produce, react and make decisions based on scientific data. How have platforms tuned to the maximization of advertising revenue failed and succeeded to serve the epistemic goals of scientists? How did the fine-tuning of algorithmic behaviours on platforms like Twitter and YouTube end up impacting decision-making processes, psychology and behaviour of the individuals using these platforms? Are there new opportunities to re-purpose and extend existing tools to promote high-quality science discourse?
- Preliminary scientific findings find themselves in a complex set of dynamics between science, policy makers, public opinion, non-traditional `outlets’ for scientific research and the media that seem deeply problematic for the integrity of the scientific process. Many of the traditional systems of peer-review and science policy were arguably already challenged by the pre-crisis state of affairs, and the pandemic has placed huge additional demands on these system. Platforms that could reward expediency and transparency, in part by increasing usage of existing machine-learning algorithms, saw dramatic increases in usage and content. They have replaced some quality-control and review functions that were previously designed for humans. If the principles of expediency, transparency and informal review are to become part of the new normal, then what models of data governance and science policy do we need to encourage? What types of sociotechnical models do we need to encourage unbiased decision-making?
- The pandemic clearly challenged the traditional science-to-policy interface. Scientists in all disciplines were called on to act as intermediaries and build trust between the general public and policy-makers. Scientists were vetting “emergent science” as it was published on social media platforms, resulting in at least one high-profile retraction. This has pushed the job of technical discussions and scientific peer-review into a new social space and one where publishers do not wield as much power over the dissemination of scientific ideas. However, oversight is important, and in this panel we invite novel ideas for governance systems, online tools and financing mechanisms that we need in order to make successful and long-lasting changes towards creating new systems for science.
- There is evidence that shows that the same misformation tactics and campaigns that have been used for climate change (among other issues) are the same ones casting aspersions about the COVID-19 vaccines. How can we prevent bad actors from overwhelming public systems and reduce opportunities for misinformation campaigns based on expedient science now, and in the future?