ONLINE: Jason Konek (Bristol): “Aggregating Imprecise Forecasts Using IP Scoring Rules”

Due to the current COVID-19 situation this event will now take place online via Zoom. 

Everyone is welcome to join using a computer with access to the internet and Zoom. To take part just follow these instructions:

• Download Zoom
• Join the event any time from 4:15pm via this link: https://lse.zoom.us/j/93256060222

Please note that these events are routinely recorded, with the edited footage being made publicly available on our website and YouTube channel. We will only record the audio, the slides and the speaker and will not include the Q&A section. However, any question asked during the talk itself will feature in the final edit.

Abstract: The mathematical foundations of imprecise probability theory (IP) have been in place for 25 years, and IP has proved successful in practice. But IP methods lack rigorous accuracy-centered, philosophical justifications. Traditional Bayesian methods can be justified using epistemic scoring rules, which measure the accuracy of the estimates that they produce. But there has been little work extending these justifications to the IP framework. In this talk, I will first outline some initial work developing scoring rules for imprecise probabilities: IP scoring rules. Then I will explain why a range of impossibility results for IP scoring rules should not concern us. Finally, I will use IP scoring rules to engineer a new method for aggregating imprecise forecasts.

Jason Konek is a lecturer in philosophy at the University of Bristol.