Improving workplace productivity via an AI-based physical activity chatbot . This project aims to develop, train and evaluate a physical activity chatbot using artificial intelligence and machine learning to improve workplace productivity in sedentary office workers. Productivity losses, due to high numbers of physically inactive workers, cost the Australian economy $14 billion per year. The cost of effective and scalable workplace physical activity programs acts as a barrier to their implementa ....Improving workplace productivity via an AI-based physical activity chatbot . This project aims to develop, train and evaluate a physical activity chatbot using artificial intelligence and machine learning to improve workplace productivity in sedentary office workers. Productivity losses, due to high numbers of physically inactive workers, cost the Australian economy $14 billion per year. The cost of effective and scalable workplace physical activity programs acts as a barrier to their implementation. As such, innovative programs that can reach large numbers of workers at minimal cost are needed. This project aims to generate new knowledge on the use of artificial intelligence to achieve behavioural improvements and will lead to the development of a new type of behaviour change program with broad applicability.
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Discovery Early Career Researcher Award - Grant ID: DE210100357
Funder
Australian Research Council
Funding Amount
$427,320.00
Summary
What determines your face identification accuracy? Accurate face identification underpins normal social functioning and important identity verification procedures in society, government and the justice system. However, there is little understanding of the cognitive processes that give rise to individual differences in face identification. This project aims to develop a new cognitive model that characterises how holistic and part-based processing combine to determine individual differences in fac ....What determines your face identification accuracy? Accurate face identification underpins normal social functioning and important identity verification procedures in society, government and the justice system. However, there is little understanding of the cognitive processes that give rise to individual differences in face identification. This project aims to develop a new cognitive model that characterises how holistic and part-based processing combine to determine individual differences in face identification. Expected benefits include advancing knowledge of human face perception, and evidence-based training and personnel selection tools to improve decision accuracy, help police prevent crime and terrorism, and avoid wrongful conviction of innocent suspects.Read moreRead less