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
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
Synthetic genes as reference standards for biology and biomanufacture. Reference standards are needed to improve the measurement of biology and the reliability of biomanufacturing processes. This project aims to engineer synthetic genes capable of acting as reference standards for DNA, RNA and protein. The synthetic genes can be transcribed into mRNA standards, and translated into protein standards, and be further integrated into living cells to measure internal cellular processes.
The outcomes ....Synthetic genes as reference standards for biology and biomanufacture. Reference standards are needed to improve the measurement of biology and the reliability of biomanufacturing processes. This project aims to engineer synthetic genes capable of acting as reference standards for DNA, RNA and protein. The synthetic genes can be transcribed into mRNA standards, and translated into protein standards, and be further integrated into living cells to measure internal cellular processes.
The outcomes include a unified understanding of gene expression and more accurate next-generation sequencing and mass-spectrophotometry technologies. The synthetic genes also allow standardisation and optimisation of biomanufacturing processes that will produce mRNA and biologics products at a higher purity and lower cost.Read moreRead less