{"id":82261,"date":"2025-06-12T10:03:00","date_gmt":"2025-06-12T08:03:00","guid":{"rendered":"https:\/\/schaltzeit.com\/?p=82261"},"modified":"2026-09-26T23:38:59","modified_gmt":"2026-09-26T21:38:59","slug":"zwischen-pixel-und-wahrheit","status":"publish","type":"post","link":"https:\/\/schaltzeit.com\/en\/between-pixels-and-truth\/","title":{"rendered":"Between pixels and truth"},"content":{"rendered":"
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How Veo 3 & Midjourney 7 are shaking the foundations of digital information<\/h4>\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\tOpenAI often plays the role of icebreaker in generative AI: in February 2025, Sora showed publicly for the first time that cinema-quality text-to-video is within reach \u2013 just a few months later, Google followed up with Veo 3, an (even) more impressive specialized model, complete with native soundscapes, lip-synced dialogue and 4K physics. \t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
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A similar pattern has shaped the image segment: DALL-E 3 was the big media \u201caha\u201d moment. It was followed by providers such as Midjourney and Stable Diffusion, which offered finer controls and generated more convincing images. Midjourney is now available in version 7 and outpaces other models with its draft mode and visibly better anatomy.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Reality on demand<\/strong><\/p>

Anyone who watches Veo clips notices how thin the line between simulation and recording has become.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t

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Even AI detection methods are increasingly failing \u2013 and so are humans: a recent study<\/a> finds that not one but two large language models pass the classic Turing test; GPT-4.5 was judged to be human in 73% of cases.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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Epistemic erosion<\/strong><\/p>

If texts can already deceive us, what does it mean that videos and images now make the same claim to reality? Classic forms of evidence \u2013 photos, film footage, original audio \u2013 are losing their probative power. Trust is shifting from sensory perception to metadata chains such as C2PA signatures or hash stamps, which are meant to make origin and editing traceable. Without such \u201ccontent credentials,\u201d we face information pollution in which the authentic and the synthetic sit side by side like two identical coins \u2013 only one of them is gold.<\/p>

When any scene can be generated at will, the line between the real and the possible blurs. Will information in the future consist of nothing but probabilities? Will its value be measured more by usefulness than by factuality? And who actually owns a reality that is created by algorithms and merely curated by users? These questions are philosophical, but their echo has long since reached practice.<\/p>

Implications for foresight & futures studies \u2013 an in-depth look with a focus on risks<\/strong><\/p>

With every new generation of language, image and video models, the bottleneck of futures analysis shifts: the core task is no longer finding information, but proving its authenticity. Security reports already speak of a \u201csecond pandemic of disinformation,\u201d because deceptively real AI videos and voices make social engineering attacks possible at everyday speed. The growing quality of synthetic voice deepfakes in particular is seen as a gateway for fraud and identity theft \u2013 a scenario that Pindrop and other cybersecurity providers listed as a top risk in 2025.<\/p>

Where weak signals are rare to begin with, synthetic noise dilutes them until they become indistinguishable. Without hash matching, C2PA signatures or cross-media verification, a viral video that supposedly shows new consumer behavior could always be a carefully staged fake. The paradoxical effect: the more spectacular the \u201cevidence,\u201d the lower its informational value \u2013 because it is precisely the most convincing images that are most attractive for disinformation.<\/p>

Economic scarcity is shifting from production to verification. Reliable proof of origin is becoming an expensive resource: computing power for deepfake detection, expertise in source criticism, legal safeguards against false quotes. As a result, decision cycles grow longer \u2013 anyone who wants to assess future trends seriously needs more time and budget to ensure information hygiene. Small organizations risk being left behind in this \u201cproof-of-reality economy.\u201d<\/p>

A fundamental problem of knowledge assessment<\/strong><\/p>

In practice, the question of whether a piece of information is \u201ctrue\u201d is losing priority to the question of what it does. This paradigm shift is not an academic sideshow but a societal tipping point:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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