The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synt ....The Misinformation Future—Confronting Emerging Threats. Misinformation presents challenges to public health and democracy. Though psychological research has explored processing mechanisms and countermeasures, new threats are arising that need to be confronted. This project aims to help meet these threats by (a) investigating misinformation impacts on future-oriented cognition and behaviours, with a focus on global long-term issues and (b) addressing the unique challenges posed by visual and synthetic (AI-generated) misinformation. The expected outcome is new knowledge on the processing and impacts of emerging types of misinformation and translation into practical interventions. These promise to benefit consumers, educators and policymakers, contributing to a healthier information environment.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE230100171
Funder
Australian Research Council
Funding Amount
$438,560.00
Summary
Integrated models of learning and decision making in complex tasks. How do people learn to make decisions in complex work systems when assisted by automation? This project will develop computational models of human learning and decision making that explain and predict complex decisions relevant to industries such as aviation and defence. It will examine how humans learn to use automated advice, how learning affects remembering to perform planned (deferred) actions, and factors that pose a risk t ....Integrated models of learning and decision making in complex tasks. How do people learn to make decisions in complex work systems when assisted by automation? This project will develop computational models of human learning and decision making that explain and predict complex decisions relevant to industries such as aviation and defence. It will examine how humans learn to use automated advice, how learning affects remembering to perform planned (deferred) actions, and factors that pose a risk to learning and adaptation. The expected outcome is a significant theoretical advance in human factors and cognitive psychology, and a tool for informing work design (e.g., computer interface, task allocation) and training, with the potential to reduce human error in safety-critical workplaces.Read moreRead less