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Research Topic : Prevention programs
Field of Research : Criminology
Socio-Economic Objective : Law Reform
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP170100706

    Funder
    Australian Research Council
    Funding Amount
    $336,874.00
    Summary
    Preventing intimate partner homicide. The project aims to develop a framework for an integrated whole systems preventive approach to intimate partner homicide – the most common type of violence against women worldwide and the leading cause of death amongst Australian women aged between 15 and 44. The project will review a decade of intimate partner homicides in Australia to identify points of intervention that might have prevented killings. This knowledge is intended to inform and help develop a .... Preventing intimate partner homicide. The project aims to develop a framework for an integrated whole systems preventive approach to intimate partner homicide – the most common type of violence against women worldwide and the leading cause of death amongst Australian women aged between 15 and 44. The project will review a decade of intimate partner homicides in Australia to identify points of intervention that might have prevented killings. This knowledge is intended to inform and help develop a more risk-sensitive preventive approach to intimate partner homicides in Australia and overseas, enhancing women’s security and preventing their deaths.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP230100241

    Funder
    Australian Research Council
    Funding Amount
    $272,025.00
    Summary
    Sexualised Deepfakes: Predictors, Consequences, Responses and Prevention. Artificial Intelligence is changing how perpetrators sexually abuse. Yet little research has explored this, and laws and digital platforms are failing to keep pace. This project aims to identify the predictors, harms and consequences of sexualised deepfakes (a form of Artificial Intelligence-Facilitated Abuse) and produce evidence to inform legal, technological and social responses to this growing problem. Expected outcome .... Sexualised Deepfakes: Predictors, Consequences, Responses and Prevention. Artificial Intelligence is changing how perpetrators sexually abuse. Yet little research has explored this, and laws and digital platforms are failing to keep pace. This project aims to identify the predictors, harms and consequences of sexualised deepfakes (a form of Artificial Intelligence-Facilitated Abuse) and produce evidence to inform legal, technological and social responses to this growing problem. Expected outcomes include increased understanding of the drivers of abuse, the development of improved prevention resources and social, technological and legal responses for digital platforms, organisations and government. Expected benefits include improved laws, policies and practices to prevent Artificial Intelligence-Facilitated Abuse.
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