A fast comparative method for historical linguistics. Linguists are able to infer ancient histories of languages by a procedure known as the Comparative Method. Its results are used in related studies of human genetic and cultural change. However, the Comparative Method is a manual-only process and thus currently is a bottleneck for the science of unravelling the human past. This project aims to overcome this limitation and significantly accelerate linguistic discovery, by combining recent advan ....A fast comparative method for historical linguistics. Linguists are able to infer ancient histories of languages by a procedure known as the Comparative Method. Its results are used in related studies of human genetic and cultural change. However, the Comparative Method is a manual-only process and thus currently is a bottleneck for the science of unravelling the human past. This project aims to overcome this limitation and significantly accelerate linguistic discovery, by combining recent advances in computational language processing, statistics and cultural-evolutionary modelling. By producing innovative mathematical means for rapidly discovering ancient language relationships, it will enable a breakthrough in our capacity to uncover human linguistic, genetic and cultural heritage worldwide.Read moreRead less
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