Too Good to Be True? How to Spot AI Content

AI tools are becoming so advanced that the distinction between real and synthetic content is increasingly blurred. We scroll through perfect photos, flawless voices, and seamless videos while the technology behind the scenes improves rapidly. This is impressive, but also tricky: how do you know what to trust?

What does the law say?

Article 50 of the EU AI Act mandates clear labeling when content has been generated or manipulated by AI-this includes text, images, audio, and video. In practice, this is still rare and enforcement remains limited for now. Do not rely on a label; take your own verification steps seriously.

Quick check: Think like a fact-checker

Start with a healthy dose of skepticism. Is something too good to be true-too perfect, too convenient, or too spectacular? Then assume AI could play a role. Next, look at the context: where was this published, who shared it, and what is the sender's objective? Unknown sources and accounts without an established history warrant extra suspicion.

The date is a signal, not proof

Always check the publication or upload date. Videos from years ago can be re-uploaded or edited, and AI existed then too-though it was often less convincing. Therefore, view the date as an indicator rather than definitive proof. Combine it with other signals, such as inconsistencies in shadows, hands, teeth, earrings, text on signs, or mismatched lip-syncing.

Practical checks that actually work

• Reverse search (reverse image/video search) to find earlier usage or alternative context.
• Watch for artifacts: distorted fingers, 'waxy' skin, unnatural patterns, or mangled letters and logos.
• Listen critically: monotonous intonation, unnatural breath pauses, or identical vocal resonance can indicate AI audio.
• Compare multiple sources: real events leave traces across reliable media outlets and eyewitness reports.
• Check the creator: does the account have a track record, a clear bio, and a consistent style?

AI makes creation more accessible, but also makes deception easier. Do not blindly trust labels or likes; maintain your own verification ritual. If in doubt? Post a question ("source?") instead of sharing the content itself. This way, you help not only yourself but also your network to be more resilient against AI-driven disinformation.

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// About the author

Job van den Berg

Mede-oprichter, AI Keynote Spreker & Techondernemer

Tech-ondernemer (1989) met een achtergrond als socioloog (Research Master (MSc) in statistiek en sociologie) en een van de meest gevraagde keynote sprekers over AI en data in Nederland. Als mede-oprichter van Ai.nl, The Automation Group en Proxies leidt hij engineers die agentic AI van prototype naar productie brengen binnen enterprises. Op het podium vertaalt Job die hands-on praktijk naar concrete strategieën. Eerder was Job Chief Data bij o.a. DPG Media en Kantar. Hij is co-auteur van 5 boeken over AI waaronder 'AI Agents' en 'Handboek AI Strategie' en een veelgevraagd expert in de landelijke media.

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