Understanding Public Data: Experts, Decisions, Epistemic Values (EDEV)

This project – promoted by IMT, IUSS, and SNS – intends to explore the scaffoldings of the epistemological framework, which underlies public decision-making when confronted with complex scientific data.

Description

As the Covid-19 pandemic has made dramatically clear, the public understanding and assessment of complex data – especially when sensitive and related to crucial aspects of people’s lives and health – can be hampered by a vast number of variables. Data must be presented in a correct and yet usable format. The public has to be made aware of both the advantages and limits of scientific methods and discovery processes. Experts must be credited with sufficient trust. The mathematical intricacies of statistical and probability reasoning must be made explicit and accessible at the same time.

The recent reception of sanitary and population data has revealed how difficult it is to provide a non-specialized public with the proper image of how scientific inquiry proceeds, and how arduous it is to convey proper models of reasoning to guide our decisions in uncertainty conditions, when high risks and significant moral dilemmas are at stake. Addressing these issues is not just a matter of public policy. It requires a solid and convincing epistemological framework grounded on the interaction between the philosophy of science, logical and critical reasoning, social epistemology and behavioural sciences.

The methodological assumption underlying the project is that the tools provided by logic, epistemology, philosophy of science, and critical reasoning can make a substantial contribution to a number of pressing issues. How are trained opinions to be credibly disseminated? How are experts to be trusted and how is public reputation to be grounded on firm and reliable bases? How should public belief be revised in light of scientific data, and how could logical fallacies be avoided in the process? How can high-stake decisions be made and motivated when confronted with partial and incomplete data? How can rationality be defined and defended in uncertainty conditions? More essentially, what are the epistemic values that should sustain both top-down knowledge dissemination on the part of scientific groups and policy-makers, and bottom-up reception of complex social scenarios and resolutions from the wider public?