Title: Combating Misinformation: Enhancing Large Language Models with Psychologically Informed Machine Learning

Speaker: Francisco Zanartu

Summary:
Climate change misinformation is ubiquitous, erodes public trust in science and scientific institutions and obstructs urgently needed climate adaptation policies. However, little progress has been made on documenting and detecting fallacies in climate misinformation. In this study, we apply a previously developed critical thinking methodology for deconstructing climate misinformation, in order to develop a dataset mapping different types of climate misinformation to reasoning fallacies. We aim to use this dataset to develop a machine learning model for automatic detection, laying the groundwork for development of solutions where automatically detected climate misinformation can be countered with generative technique-based corrections.

WED 15 NOVEMBER 2023 16:00-17:00 (AEDT, Melbourne Time)

MEETING ID: 873 1557 5255; PASSWORD: 778635