Old Threats, New Name? Generative AI and Visual Journalism
Generative AI applications have been hailed as “transformative,” “disruptive,” and posing a “threat to human journalists and media professionals.” Much of this discourse reflects longstanding concerns about the impact of technological change on both the production and consumption ends of journalism. Perhaps nowhere is this felt more strongly than in visual journalism, where fears about AI replacing cameras and associated implications are rife. These concerns resemble earlier debates about visual technologies, from the smartphone camera to social media, and intersect with fundamental debates about journalism’s boundaries and norms: what news “is,” how it is produced, and what we expect it to achieve. Amidst this hype and anxiety, we offer an analysis of AI’s risks to visual journalism that contextualises this technology against journalism’s existing tensions. Our study asks: How unique are the threats that generative AI poses to visual news? Specifically, we look across academic disciplines to interrogate three threats that are especially prevalent in the literature. Our conceptual evaluation is benefited empirically by dozens of industry perspectives spanning three continents, and allows us to identify exactly which threats, if any, that generative AI poses to visual journalism are new, and which are extant threats folded into more longstanding discourses.