Early Career Industry Fellowships - Grant ID: IE230100380
Funder
Australian Research Council
Funding Amount
$390,574.00
Summary
Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error a ....Enhancing comprehension of forensic science in the justice system. Failures to effectively communicate the accuracy and reliability of forensic evidence to courts can lead to unreliable convictions and miscarriages of justice. This project aims to understand how best to distil complex information about error and uncertainty in forensic expert opinion evidence for enhanced comprehension of forensic science in the justice system. Outcomes include evidence-based strategies for communicating error and uncertainty in forensic science and an accessible online dashboard for visualising known error rates in forensic disciplines. The knowledge gained from the project will help forensic experts to calibrate how they present their conclusions to courts for improved comprehension and evaluation of forensic evidence.Read moreRead less
Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits ....Where do inductive biases come from? A Bayesian investigation. This project aims to investigate the origin of our thinking and learning biases using state-of-the-art mathematical models and sophisticated experimental designs. Expected outcomes include bridging the gap between human and machine learning by pairing mathematical modelling with experimental work, forming a necessary step toward the development of machine systems that can reason like people do. This will provide significant benefits such as understanding how people operate so effectively in real environments, when even the most powerful computers struggle to handle the complexities of everyday learning problems.Read moreRead less
Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time ....Improving the diagnosticity of eyewitness memory choices. Eyewitness identification error is common and costly. This project aims to improve the quality of information provided by eyewitnesses, and the ability of police officers and triers of fact (e.g., juries, judges) to evaluate this information. Laboratory investigations will determine how best to test memory and confidence to achieve this aim. A new class of cognitive models will provide a unified account of response accuracy, response time, and confidence, suitable for application to computerized testing scenarios. The models and testing methods validated in the laboratory will be refined for application in eyewitness memory settings, facilitating better evaluation of identification evidence, and potentially reducing wrongful convictions.Read moreRead less