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Featured 2024 Other Outputs Submission to the Senate Select Committee on Adopting Artificial Intelligence (AI)Curtis, Caitlin (2024). Submission to the Senate Select Committee on Adopting Artificial Intelligence (AI). Brisbane, Australia: The University of Queensland. doi: 10.14264/48dfdd6 |
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Featured 2023 Other Outputs Trust in AI: Country insights on shifting public perceptions of AI: Country findingsGillespie, Nicole, Lockey, Steve, Curtis, Caitlin and Pool, Javad (2023). Trust in AI: Country insights on shifting public perceptions of AI: Country findings. Brisbane, Australia; New York, United States: The University of Queensland; KPMG Australia. |
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Featured 2023 Other Outputs Submission to the Australian Government: Attorney-General’s Department review of the Privacy Act 1988 (Cth) - genetic and genomic dataCurtis, Caitlin, Hereward, James and Newton, Giselle (2023). Submission to the Australian Government: Attorney-General’s Department review of the Privacy Act 1988 (Cth) - genetic and genomic data. Canberra, ACT, Australia: Australian Government. Attorney-General’s Department. |
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2023 Other Outputs Trust in Artificial Intelligence: A global studyGillespie, Nicole, Lockey, Steven, Curtis, Caitlin, Pool, Javad and Ali Akbari (2023). Trust in Artificial Intelligence: A global study. Brisbane, Australia; New York, United States: The University of Queensland; KPMG Australia. doi: 10.14264/00d3c94 |
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2021 Other Outputs Trust in artificial Intelligence: a five country studyGillespie, Nicole, Lockey, Steve and Curtis, Caitlin (2021). Trust in artificial Intelligence: a five country study. Brisbane, Australia; New York, United States: The University of Queensland; KPMG. doi: 10.14264/e34bfa3 |
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Featured 2020 Other Outputs Submission to the Review of the Privacy Act 1988 (Cth)Curtis, Caitlin, Gillespie, Nicole and Lockey, Steve (2020). Submission to the Review of the Privacy Act 1988 (Cth). Australia: The University of Queensland & Australian Government: Attorney-General's Department. doi: 10.14264/501b50f |
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2020 Other Outputs Achieving Trustworthy AI: A Model for Trustworthy Artificial IntelligenceGillespie, Nicole, Curtis, Caitlin, Bianchi, Rossana, Akbari, Ali and Fentener van Vlissingen, Rita (2020). Achieving Trustworthy AI: A Model for Trustworthy Artificial Intelligence. Australia: The University of Queensland and KPMG. doi: 10.14264/ca0819d |
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2020 Other Outputs Trust in Artificial Intelligence: Australian InsightsLockey, Steve, Gillespie, Nicole and Curtis, Caitlin (2020). Trust in Artificial Intelligence: Australian Insights . Australia: The University of Queensland and KPMG. doi: 10.14264/b32f129 |
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2020 Other Outputs Human rights and technology project, submission #73 to the Australian Human Rights CommissionCurtis, Caitlin, Radke, Amelia and Hereward, James (2020). Human rights and technology project, submission #73 to the Australian Human Rights Commission. Human Rights and Technology Project: Australian Human Rights Commission. |
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2019 Other Outputs Policy futures: regulating the new economyHussey, Karen, Yarnold, Jennifer, McEwan, Christopher, Maher, Ray, Henman, Paul, Radke, Amelia, Curtis, Caitlin, Fidelman, Pedro, Vickers, Claudia and Brolan, Claire (2019). Policy futures: regulating the new economy. Policy Futures Brisbane, Australia: The University of Queensland. |
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2018 Other Outputs Submission to the Australian Human Rights Commission, Human Rights and Technology ProjectCurtis, Caitlin, Mangelsdorf, Marie and Hereward, James (2018). Submission to the Australian Human Rights Commission, Human Rights and Technology Project. Australia: Australian Human Rights Commission. |
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2023 Other Outputs Trust in AI: 2023 Global study on the shifting public perceptions of AI: Global Executive SummaryGillespie, Nicole, Lockey, Steve, Curtis, Caitlin and Pool, Javad (2023). Trust in AI: 2023 Global study on the shifting public perceptions of AI: Global Executive Summary. New York, NY, United States; Brisbane, Australia: KPMG International; The University of Queensland. |
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2020 Other Outputs PrivColl: Practical Privacy-Preserving Collaborative Machine LearningZhang, Yanjun, Bai, Guangdong, Li, Xue, Curtis, Caitlin, Chen, Chen and Ko, Ryan KL (2020). PrivColl: Practical Privacy-Preserving Collaborative Machine Learning. |
