Authenticity is a key problem for understanding and managing the impacts of generative AI and synthetic media in society, and a central target for automated decision-making systems in the information and media environment. From trustworthy news reporting to identity verification for social services and the everyday risk of scams, generative AI and synthetic media present significant real-world implications for practitioners, institutions, and publics in Australia and elsewhere. A wide range of technical solutions collectively understood as authenticity infrastructure promise to address these issues; but if adopted and embedded at scale, some of these solutions could have potentially significant downstream effects on stakeholders and implications for society.
This project will critically examine the assumptions underpinning these developments and debates, assess the technical and legal challenges associated with them, and explore novel technical responses that contribute to more responsible, ethical and inclusive ADM systems. In doing so, the project will draw on the multidisciplinary expertise of the Centre and our partners to negotiate and navigate authenticity as both socio-technical challenge and as a contested cultural idea. It will also examine what happens after any determination of authenticity, including mechanisms for explaining and communicating determinations and increasing trust in such measures.
Objectives:
- Produce a cross-disciplinary understanding of the problem of authenticity in the context of Generative AI;
- Study and map the field of Authenticity-as-a-Service (AaaS), providing a detailed account of its infrastructure, operations, and political economy;
- Analyse how the integration of authenticity infrastructure is already playing out in practice in specific sectors, and impacting or likely to impact specific communities;
- Within the Generative AI Test Range environment, simulate and evaluate competing ADM techniques for addressing the problem of authenticity in a range of real-world scenarios; and
- Build on our findings to develop improved tools and techniques, and produce and share guidelines for explanation and communication for a range of stakeholders and audiences.
Project team
- Prof Jean Burgess
- Prof Chris Leckie
- Prof Anthony McCosker
- Assoc Prof Michael Richardson
- Dr Ariadna Fernandez
- Dr Aaron Snoswell
- Dr T.J Thomson
- Dr Luke Munn
- Prof Flora Salim
- Dr Sarah Erfani
- Assoc Prof Jeffrey Chan
- Dr Silvia Silvia Montaña-Niño
- Dr Michelle Riedlinger
- Assoc Prof Julia Stoyanovic
- Prof Wiebke Loosen
- Dr Jake Goldenfein
Project partners
- Australian Broadcasting Corporation
- Australian Red Cross
- Centre for Responsible AI, New York University
- Hans Bredow Institut
Collaborating organisations
Project funding
- Australian Government through the Australian Research Council – ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S)
Funding / Grants
- Australian Government through the Australian Research Council – ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S)
Chief Investigators
