Meaningful participation in important scientific discourses requires specialist knowledge. For example, to evaluate the safety of a plan to deploy machine learning in public infrastructure, some understanding of current techniques and their range of applicability is required; likewise, climate data cannot be meaningfully analysed by someone who lacks prior experience in statistics. Access to specialist training of this kind is presently centralised in the universities and gated behind tuition fees and time barriers.

We will answer the erosion of public trust in the scientific process with a credible invitation: join us, learn our methods, and contribute to the discourse. To that end, we aim to build sustainable infrastructure for a decentralised network of publicly accessible online courseware, textbooks, tutorials, and social media that will serve as the roots of a new and serious partnership between the public and the scientific community.

Investigators: Jonathan Sterling, Anil Madhavapeddy