Industrial Transformation Training Centres - Grant ID: IC210100008
Funder
Australian Research Council
Funding Amount
$4,282,859.00
Summary
ARC Training Centre for Behavioural Insights for Technology Adoption (BITA). Australia needs accelerated adoption of innovation technologies to improve outcomes in health, agriculture and cybersecurity. Despite technically viable solutions, innovations fail to be adopted due to behavioural barriers. Behavioural approaches can promote significant gains by bridging the barriers to technology adoption. The Centre for Behavioural Insights for Technology Adoption will boost national productivity by i ....ARC Training Centre for Behavioural Insights for Technology Adoption (BITA). Australia needs accelerated adoption of innovation technologies to improve outcomes in health, agriculture and cybersecurity. Despite technically viable solutions, innovations fail to be adopted due to behavioural barriers. Behavioural approaches can promote significant gains by bridging the barriers to technology adoption. The Centre for Behavioural Insights for Technology Adoption will boost national productivity by identifying, designing and evaluating solutions that address these barriers. By uniting industry and government with world-leading interdisciplinary researchers, the Centre will build transformative capability in people, data and solutions and support Australian organisations to achieve higher returns on technology investment.Read moreRead less
Learned Academies Special Projects - Grant ID: LA170100025
Funder
Australian Research Council
Funding Amount
$210,000.00
Summary
Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social med ....Big data in Australian research: issues, challenges and opportunities. This project aims to enhance discovery, productivity and translation within and between disciplines in Australian research through better utilisation of big data. Advances in our ability to capture, store, process and analyse large data sets are transforming many parts of society, including the research sector. Machine learning, for example, will allow data-driven analysis of massive, unstructured data sets such as social media archives or financial records in ways that will shed new light on many complex research questions. This project will map existing capability and infrastructure within and across disciplines, identify common and discipline-specific practices, challenges and opportunities, and assess technology, infrastructure, training and collaboration priorities for Australia.
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Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification ....Theoretical Foundations of Ethical Machine Learning. The project aims to develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project aims to develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of the inevitable trade-offs between fairness and utility. The benefits of the project should include better ways of managing these trade-offs, a competitive advantage for Australian firms developing the technology, and will ensure that the country retains a social license to use the technology.Read moreRead less
Hybrid optimisation for automatic large-scale video annotation. Optimization is the basis for solving many problems in Computer Vision, such as three-dimensional geometry recovery, image segmentation, scene labeling and object recognition. This project will develop new optimisation techniques and demonstrate their suitability for large-scale video annotation, which is key to visual data mining and scene understanding.
Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expecte ....Data sharing with strong privacy against inference attacks. This project aims to develop theories and techniques for strong protection of personal information in sharing large datasets such as national health data or census records. It intends to achieve this through developing new information theoretic methods for synthesising datasets with proven high fidelity and protection against re-identification and inference attacks, where attackers try to learn probability of sensitive data. The expected outcomes are algorithms for public and private sector data curators to dial up or down their data access arrangements based on privacy risks and fidelity demands linked with different data types and uses. This project intends to enable Australians to securely benefit from valuable data in decision making.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL200100176
Funder
Australian Research Council
Funding Amount
$3,128,080.00
Summary
Theoretical Foundations of Ethical Machine Learning. The project will develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project will develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of t ....Theoretical Foundations of Ethical Machine Learning. The project will develop a systematic theory of ethical machine learning. Machine learning is a powerful and pervasive technology that is already having a huge impact on Australia. When applied to data about people there are a range of ethical harms that can arise (fairness, and privacy are two of them). The project will develop a rigorously grounded foundation for managing such ethical harms. For example it will allow the quantification of the inevitable trade-offs between fairness and utility. The benefits of the project will include the best possible ways of managing these trade-offs, competitive advantage for Australian firms developing the technology, and will ensure that the country retains a social license to use the technology.Read moreRead less