Digital and Technological Transformation

Investigator: Luke Strickland

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.

This project is funded by the Australian Research Council.

Investigator: Mingming Cheng

This project is a pioneering initiative that aims to harness the power of social listening to identify and combat modern slavery online. It uses advanced social media analytics to detect potential instances of forced labour and trafficking activities across a range of social media platforms (e.g., TikTok). The expected outcomes of the project are twofold: firstly, it will provide a more comprehensive understanding of how victims of modern slavery use social media platforms; and secondly, it will develop effective strategies for identifying and aiding those at risk. By leveraging the vast amount of data available on social media, the project has the potential to make a significant impact in the fight against modern slavery, offering new insights and tools to assist with prevention and intervention.

This project is funded by the Social Media Research Lab and the Minderoo Foundation.