Deepfakes
Alternative labels
AI generated fakes
Artificially generated content
Synthetic content ( images, audio and video)
Report
Political deepfakes and the new laws in NSW
Political deepfakes are AI-generated digital content that depict a politician doing or saying something they did not do or say. This paper outlines the potential adverse impacts of political deepfakes, summarises New South Wales reforms, and examines legislative developments in other jurisdictions. It also discusses other measures that can be used to combat political deepfakes.
Report
Characteristics of image-based sexual abuse recorded by police
This bulletin describes the findings of an analysis of 771 individuals proceeded against by police for image-based sexual abuse (IBSA) offences in four jurisdictions in 2022–23: Australian Capital Territory, New South Wales, Northern Territory and Victoria. It discusses implications for prevention and detection of IBSA offending, and underlines the need for tailored responses to IBSA...
Report
Sexually explicit deepfakes and the criminal law in NSW
This paper presents data on the increasing prevalence of sexually explicit deepfakes and discusses their harmful impacts. It identifies three gaps in NSW’s offences, finding that the non-consensual creation of sexually explicit deepfakes of adults is unprohibited in NSW. It proposes amendments to the NSW’s offences along the lines of the new Commonwealth and Victorian...
Briefing paper
Content Credentials: strengthening multimedia integrity in the generative AI era
The abuse of AI-generated media poses a significant and growing cybersecurity threat, creating an urgent need to bolster information integrity. This joint publication outlines leading approaches to confirming the provenance of digital content and recommends the swift and widespread adoption of Content Credentials across the information ecosystem.
Briefing paper
Free and fair: election law in the age of AI
This briefing paper explores the impact of AI-enabled disinformation and fake content on democratic processes and investigates the potential obligations of states to protect elections from it. The paper argues that although not currently legally bound to do so, states should take proactive measures to defend elections from AI misuse.