They like the tool, but they don’t like the perceived demonization: After Instagram instituted a label on images to clearly identify those that were AI-generated, many photographers stood up in arms, angry that it also included images retouched using AI. “It is not the same,” they say. “Retouching,” they say,Continue Reading

In today’s hyper-connected world, we’re facing an unprecedented deluge of digital content. From photos and videos to articles, books, and music, the sheer volume of available material is staggering. But what happens when there’s simply too much content? The Content Explosion: By the Numbers To truly grasp the scale ofContinue Reading

As we progress in our new decade, an invisible crisis is unfolding. In our digital age, where images can be manipulated effortlessly or generated entirely by artificial intelligence, our faith in what we see is crumbling.  Since we rely on our senses to make decisions about the world—particularly our senseContinue Reading

Four visual AI platforms are setting industry standards by training their models on ethically sourced data, compensating creators fairly, and preventing the generation of copyrighted content. Adobe, Getty Images, Shutterstock, and Bria.ai have established revenue-sharing and bonus systems, with vast proprietary image databases, to support ethical AI development. These companies are leading the charge in demonstrating that AI can succeed commercially while adhering to responsible data practices and bypassing the need for regulatory oversight.Continue Reading

On January 14, 2014, photographer Narciso Contreras was dismissed by AP for editing a war photo, raising issues of journalistic integrity and trust. Recent advancements like the Content Credentials metadata framework aim to restore authenticity in images, flagging edits and AI involvement. Major tech companies, camera manufacturers, and news agencies are adopting this transparency standard, signaling a paradigm shift in the credibility of visual content.Continue Reading

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Major tech companies like Google, Meta, and OpenAI are labeling AI-generated images as “AI-generated” to distinguish them from authentic photos. These labels support the C2PA standard which is gaining industry support, emphasizing transparency for consumers and protection against deceptive imagery. An upcoming panel will discuss the effectiveness and future of these labeling practices, although the system isn’t foolproof due to the potential to manipulate image metadata. The industry is also exploring AI detection tools as another method to identify AI-generated content.Continue Reading

Deepfake technology struggles with the uncanny valley not just in visuals but in narrative believability. Effective deepfakes are subtle, avoiding suspicion by mimicking mundane reality. The major challenge for deepfakes, as illustrated by elections and AI-generated images, lies in crafting convincing stories, not just in visual realism. Education helps people discern truth, highlighting the need for vigilance in the face of potential misuse of digital manipulation.Continue Reading

The year 2024 marks a milestone in digital imagery evolution as groundbreaking technologies redefine visual expression. Generative AI revolutionizes visual content, while Extended Reality (XR) and Neural Radiance Fields (NeRF) reshape 3D modeling. These innovations permeate every aspect of our visually-driven society, promising a future where physical and digital realities merge in unprecedented ways.Continue Reading