How Is Artificial Intelligence Reshaping Visual Trust? A Review of Photography, Image Manipulation, and the Crisis of Authenticity in Digital Media

Myrah Dabboo Ratnani

How Is Artificial Intelligence Reshaping Visual Trust? A Review of Photography, Image Manipulation, and the Crisis of Authenticity in Digital Media

Author(s)	Ms. Myrah Dabboo Ratnani
Country	India
Abstract	Photography has always been privileged in its position as evidence, being regarded as the image that "must have been there" because the image itself is a record of a physical meeting between a scene and a surface. However, that relationship becomes more complicated when it comes to artificial intelligence. Today, generative systems can also create photorealistic images, without relying on a photographed referent, and the more and more widely available editing tools can manipulate authentic images at a level of semantics. This review explores the implications of that change on visual trust. It takes as its theoretical moorings three vital concepts: Barthes's idea of photographic indexicality, the recorded history of photographic manipulation, and Chesney and Citron's idea of the liar's dividend. The following foundations are challenged with the latest evidence of human detection, machine detection and provenance technologies. Human performance becomes less reliable and less consistent: Nightingale and Farid found that for images, participants were only 48.2% accurate when distinguishing real from AI-synthesized faces, and a multimodal study in 2025 showed a 49.4% accuracy for images. While machine detectors are successful in highly controlled benchmarks, cross-generator generalization, compression, resizing and model evolution are ongoing problems. The central issue no longer just has to be whether a specific image is bogus, the review says. The more fundamental issue is that the question of convincing undermines the presumption of all images, even of a real object, and particularly the presumption of their verisimilitude. Detection must not therefore be the primary concern for authentication. New systems like C2PA Content Credentials and SynthID move the issue away from the pixel to the origin and transformations, but don't validate semantic verity. The paper argues that visual trust is transforming from an indexical to a chain of custody model (provenance, forensic analysis, contextual verification, institutional accountability).
Keywords	Generative AI, Visual Trust, Photography, Deepfakes, Image Forensics, Provenance, C2PA, Synthetic Media
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 5, September-October 2026
Published On	2026-10-14

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How Is Artificial Intelligence Reshaping Visual Trust? A Review of Photography, Image Manipulation, and the Crisis of Authenticity in Digital Media

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