The way society thinks about an issue determines how it responds. This project seeks to understand public discourse around cycles of disadvantage in Australia by analysing public texts across media and parliamentary speeches. This will enable us to better understand what the public thinks about disadvantage and the factors that shape it. It will also help us understand what forces in turn shape the discourse.
This project aims to improve how we understand the impact that robots have on public space, and to identify the policy implications of this rapidly emerging technology. It brings interdisciplinary conceptual and methodological frameworks to a new study of human-robot interaction and new applications of socio-affective robotics, focusing on public perceptions of their design and behaviours. This includes participatory co-design workshops, discussion of scenarios of the near future, and a series of events to disseminate findings.
Disrupting and preventing deepfakes: Responding to AI-Facilitated abuse
AI is transforming the landscape of technology-facilitated abuse through the creation of pornographic deepfakes, that is, AI-manipulated imagery non-consensually transposing faces onto the bodies of people in sexual, nude or intimate contexts. The blatant commercialisation of AI-technologies has broadened its accessibility beyond the motivated technological expert, with a high-powered computer and graphics processing unit, to the everyday person. The challenges in regulating deepfakes raises questions around digital criminality, ethics, measurements of harm, civic responsibility and social justice participation. It is these challenges that this innovative interdisciplinary research seeks to address.
This transdisciplinary project helps public decision-makers tackle complex public problems by using AI in new and innovative ways. We are undertaking social and policy research to understand the needs and concerns of decision-makers to ensure the AI solutions we develop address these, while at the same time building AI tools that analyse data and generate actionable insights in ways that empower decision-makers to make evidence-informed decisions and support the achievement of sustainable development.
The past ten years or so have seen artificial intelligence (AI) technologies become a prominent topic of discussion across Australian society - yet, the ongoing implementation of these technologies remains a highly contested topic. Based on a nationally-representative public opinion survey of over 2000 Australian adults (n=2,019), this Monash Data Futures Institute report examines key areas of public understanding, optimism and concern regarding the societal application of AI technologies. As industry and policy-makers continue to develop, implement and manage AI across most areas of Australian society, this report explores the often-overlooked views of the general public – in many ways, the ultimate ‘end users’ of these powerful technologies.
Contemporary populism has transformed political anger into widespread rebellion against ethnic and cultural pluralism. Yet anger is a double-edged sword: it can fuel contempt for immigrants and asylum seekers, but it can also motivate protest against their unjust treatment. This project integrates political philosophy, applied behavioural science and data sciences, using game theoretical and agent-based modelling, informed by real social data, to explore why negative forms of anger become common in societies, and to provide potential strategies to transform anger into a positive democratic force.
Net zero precincts: Citizen data commons and technological sovereignty
Local sustainability initiatives often lack meaningful community engagement in data governance. This project developed a novel participatory approach to enable multiple stakeholders to co-design and co-appraise data governance prototypes in the context of the Monash Net Zero Precinct. Results reveal the importance of harnessing community engagement to reflect the contexts, values and interests of diverse stakeholders and empower multilevel participation in data governance.