Can you trust what looks real?

Introduction

Synthetic media has changed the economics of deception. In earlier eras, creating a convincing fake photograph, video or audio recording often required specialist skills, time and resources. Today, generative AI tools can produce realistic images, voices and video clips in minutes. The result is not simply that more false content exists. The deeper problem is that quick judgement has become more expensive. A reader scrolling through a mixed social feed must spend more time, attention and verification effort to decide whether a dramatic image or clip deserves trust. In a media environment where entertainment, humour, activism, advertising and news appear side by side, synthetic content weakens many of the visual shortcuts people once relied on. TIM Review+2Center for News, Technology & Innovation[timreview.ca]timreview.caTIM ReviewThe Emergence of Deepfake Technology: A Reviewby M Westerlund · 2019 · Cited by 1987 — Deepfakes are the product of artificial…

The challenge is especially important for news trust. A striking image can arrive before any reporting, accumulate shares before verification, and influence discussion even after being debunked. Synthetic media therefore raises the cost of fast judgement precisely because it targets the conditions under which people often consume information: quickly, socially and emotionally.[UNESCO+2Sage Journals]unesco.orgdeepfakes and crisis knowingDeepfakes and the crisis of knowing27 Oct 2025 — The threat of misinformation and disinformation, now massively amplified by synthe…

Why synthetic visuals strain old trust cues

For much of modern media history, people used practical trust cues when assessing images. Photographs were not automatically believed, but many viewers assumed that a clear visual record at least began with a real scene. Editing existed, yet producing convincing fabrications required effort and expertise.

Generative AI changes that balance. Modern systems can create scenes that never happened, place real people in fictional situations, alter existing photographs, or generate entirely synthetic faces that resemble ordinary portraits. Deepfakes are only one part of a broader category of synthetic media that includes AI-generated images, audio and video. What distinguishes the current moment is not the existence of manipulation but the scale, speed and realism with which it can be produced. Center for News, Technology & Innovation+2TIM Review[cnti.org]cnti.orgsynthetic media deepfakesCenter for News, Technology & InnovationSynthetic Media & Deepfakes6 Oct 2025 — Deepfakes are AI-generated audio, video, or images that c…

Research increasingly suggests that human intuition is a weak defence. Studies examining people’s ability to distinguish authentic content from AI-generated material have found that performance often approaches chance levels, especially as generation quality improves. Confidence is frequently higher than accuracy, meaning people can feel certain while being mistaken.[arXiv+2arXiv]arxiv.orgarXiv Testing Human Ability To Detect Deepfake Images of Human FacesTesting Human Ability To Detect Deepfake Images of Human FacesDecember 7, 2022…Published: December 7, 2022

This creates a practical problem for feed-based news consumption. Traditional visual clues such as photographic realism, apparent eyewitness evidence or emotional authenticity become less reliable. The viewer must therefore spend more effort evaluating source, context and provenance rather than relying on appearance alone.

How AI fakes mix entertainment, rumour and public affairs

One reason synthetic media is difficult to evaluate is that it rarely arrives labelled as a political hoax. The same tools used for comedy, fan art, advertising, parody and creative experimentation can also produce misleading content. Humour, persuasion and fabrication can coexist within a single post.

A synthetic image may begin as a joke, circulate as a meme, then become detached from its original context and be interpreted as evidence. A fabricated photograph can spread because it is emotionally compelling rather than because it makes a specific factual claim. In mixed social feeds, users often encounter content outside its original setting, making context loss a major factor in misunderstanding.[UNESCO]unesco.orgdeepfakes and crisis knowingDeepfakes and the crisis of knowing27 Oct 2025 — The threat of misinformation and disinformation, now massively amplified by synthe…

Public affairs become entangled with these dynamics during crises and breaking events. Disaster imagery, conflict footage and political content often spread before verification is complete. The speed of social sharing rewards dramatic visuals, while verification usually takes longer. During emergencies, fabricated or AI-enhanced images can attract attention precisely because they intensify emotional reactions.[New York Post]nypost.comA simple vista, las fotos muestran a una niña con un chaleco salvavidas sosteniendo un perro bajo la lluvia. Sin embargo, las imágenes pr…

Recent controversies involving AI-generated images of public figures illustrate another mechanism. Viewers may react before investigating authenticity because the image appears plausible, aligns with existing beliefs or provokes outrage. Even when corrections arrive later, the initial impression can influence public discussion.[The Guardian]theguardian.comIn a Facebook post, Meloni criticized political opponents for using such fabrications to attack her and highlighted the broader risks of…

The result is not always direct belief in a falsehood. Sometimes the outcome is broader uncertainty. Research on deepfakes suggests that exposure can increase doubt and reduce trust in information environments generally. People may become less certain about what is true rather than fully convinced by a specific fabrication.[Sage Journals]journals.sagepub.comSage JournalsDeepfakes and Disinformation: Exploring the Impact of…by C Vaccari · 2020 · Cited by 1585 — We find that people are more…

The hidden cost: more verification, more uncertainty

The phrase “cost of judgement” refers to the effort required to evaluate information. Synthetic media increases that cost in several ways.

First, it expands the number of items that deserve scrutiny. A dramatic image can no longer be treated as evidence simply because it looks authentic.

Second, it raises the technical demands placed on ordinary users. Assessing authenticity increasingly involves checking metadata, searching for original sources, comparing reports across outlets or using verification tools. Activities once associated mainly with journalists and investigators are becoming more relevant to everyday media consumers.[Cambridge University Press & Assessment]resolve.cambridge.orgCambridge University Press & Assessment9 Images, Reverse Image Searching and DeepfakesA reverse image search can be produced from both in…

Third, synthetic media creates what some researchers describe as an environment of indeterminacy. When realistic fabrications become common knowledge, genuine evidence can also be questioned. A real image may be dismissed as fake, while a fake image may be defended as real. The public is left with more uncertainty and fewer widely shared assumptions about what visual evidence means.[Sage Journals]journals.sagepub.comSage JournalsDeepfakes and Disinformation: Exploring the Impact of…by C Vaccari · 2020 · Cited by 1585 — We find that people are more…

This is one reason experts increasingly discuss information integrity rather than only misinformation. The issue is not simply removing false content. It is preserving confidence that authentic evidence can still be recognised and trusted.[United Nations]un.orgsafeguarding human rights and information integrity age generative aimore…

What to check before sharing a dramatic image or clip

The most effective response is often slower judgement rather than instant judgement. A few basic checks can dramatically reduce the chance of amplifying fabricated content.

Check the source before the image. Ask who first posted the material. Is the original source visible, identifiable and accountable? Anonymous reposts deserve greater caution.

Look for independent confirmation. If a dramatic event genuinely occurred, multiple credible organisations or eyewitnesses are often reporting it.

Search for the image elsewhere. Reverse-image search tools can reveal whether a picture is old, altered or being reused in a misleading context.[Cambridge University Press & Assessment]resolve.cambridge.orgCambridge University Press & Assessment9 Images, Reverse Image Searching and DeepfakesA reverse image search can be produced from both in…

Inspect details carefully. AI-generated images can still contain inconsistencies involving text, hands, reflections, backgrounds or object relationships. These clues are not definitive, but they can justify further checking.[codecentric AG]codecentric.decodecentric AGDeepFake: Detect AI-Generated Images in 5 StepsDeepFakes are everywhere! Learn how to detect AI-generated images in minutes…

Pause when content triggers a strong reaction. Synthetic media often succeeds because it provokes surprise, anger, amusement or sympathy. Emotional intensity is a reason to verify, not a reason to share immediately.[LinkedIn]linkedin.comMa'aly Hazzaz's Post#FakeNews #Disinformation #Misleading #LackOfContext The challenge… As AI-generated content and deepfakes…

Look for provenance signals. Emerging authenticity systems and content-credential initiatives attempt to document where media came from and whether it has been altered. They are not perfect solutions, but they represent an effort to restore trust signals that are disappearing in AI-heavy information environments.[fotoware.com]fotoware.comcontent authenticityHow to protect trust in the digital age28 May 2026 — Learn how Content Authenticity can protect trust in digital content by verifying ori…Published: May 2026

Can you trust what looks real?

The practical answer is neither complete trust nor complete scepticism. Synthetic media has made appearance a weaker signal than it once was, but it has not made truth impossible to establish. What has changed is the amount of work required.

In mixed social feeds, realism alone is no longer a reliable indicator of authenticity. A convincing image may be genuine, manipulated, satirical, synthetic or entirely fabricated. The reader who wants accurate information must therefore spend more effort examining source, context and corroboration. Synthetic media raises the cost of quick judgement because it forces people to replace visual instinct with deliberate verification. In the age of social media and AI, the most valuable habit may be the simplest: treating “it looks real” as the beginning of an investigation rather than the end of one.[Center for News, Technology & Innovation+2UNESCO]cnti.orgsynthetic media deepfakesCenter for News, Technology & InnovationSynthetic Media & Deepfakes6 Oct 2025 — Deepfakes are AI-generated audio, video, or images that c…

Amazon book picks

Further Reading

Books and field guides related to Can you trust what looks real?. Use these as the next step if you want deeper reading beyond the article.

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Deepfakes

By Nina Schick

Directly addresses AI-generated images, video and trust.

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The Coming Wave

By Mustafa Suleyman

Explains the societal implications of powerful AI tools.

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The art of thinking clearly

By Rolf Dobelli, Rolf Dobelli

Useful for resisting visual and emotional manipulation.

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Chaos Machine

By Max Fisher

Places synthetic media within broader platform dynamics.

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Browse more on Amazon:DeepfakesThe Coming WaveThe art of thinking clearly

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Endnotes

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Title: Docs Synthetic content and its implications for AI policy: a primer
Link:https://unesdoc.unesco.org/ark%3A/48223/pf0000392181

2. Source: unesco.org
Title: deepfakes and crisis knowing
Link:https://www.unesco.org/en/articles/deepfakes-and-crisis-knowing

3. Source: arxiv.org
Title: arXiv Testing Human Ability To Detect Deepfake Images of Human Faces
Link:https://arxiv.org/abs/2212.05056

Published: December 7, 2022

4. Source: arxiv.org
Link:https://arxiv.org/abs/2403.16760

5. Source: resolve.cambridge.org
Link:https://resolve.cambridge.org/core/services/aop-cambridge-core/content/view/224FE549F3C1D2554450C2C9C74010CF/9781783305100c9_p129-146_CBO.pdf/images-reverse-image-searching-and-deepfakes.pdf

6. Source: fotoware.com
Title: content authenticity
Link:https://www.fotoware.com/blog/content-authenticity

Published: May 2026

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Link:https://www.codecentric.de/en/knowledge-hub/blog/deepfake-detect-ai-generated-images-in-5-step

8. Source: arxiv.org
Link:https://arxiv.org/abs/2304.06470

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10. Source: unesco.org
Link:https://www.unesco.org/en

11. Source: unesco.org
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12. Source: linkedin.com
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13. Source: linkedin.com
Title: UNESC O releases guidelines for AI and digital platform
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14. Source: linkedin.com
Title: #ai #artificialintelligence #unescocourier #noexcuse #16days
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21. Source: journals.sagepub.com
Link:https://journals.sagepub.com/doi/10.1177/2056305120903408

22. Source: nypost.com
Link:https://nypost.com/2024/10/05/us-news/ai-deepfakes-of-hurricane-helene-victims-circulate-on-social-media/

23. Source: theguardian.com
Link:https://www.theguardian.com/world/2026/may/05/giorgia-meloni-ai-generated-lingerie-image-deepfake

24. Source: un.org
Title: safeguarding human rights and information integrity age generative ai
Link:https://www.un.org/en/un-chronicle/safeguarding-human-rights-and-information-integrity-age-generative-ai

25. Source: facebook.com
Link:https://www.facebook.com/unesco/posts/-stop-generating-biased-content-generative-ai-can-reproduce-bias-misleading-info/698220612353490/

26. Source: dig.watch
Link:https://dig.watch/updates/unesco-report-warns-ai-driven-abuse-threatens-women-journalists-globally

Published: May 2026

27. Source: journals.sagepub.com
Link:https://journals.sagepub.com/doi/10.1177/27523543251344971

28. Source: journals.sagepub.com
Link:https://journals.sagepub.com/doi/abs/10.1177/01655515251330605

Additional References

29. Source: contentauthenticity.org
Link:https://contentauthenticity.org/

30. Source: facebook.com
Link:https://www.facebook.com/groups/1048019523623103/posts/1524435305981520/

31. Source: techradar.com
Link:https://www.techradar.com/ai-platforms-assistants/i-think-i-can-spot-an-ai-fake-but-the-latest-expert-research-suggests-im-wrong-heres-why

32. Source: medium.com
Link:https://medium.com/%40altruistic_patriarch_fish_753/why-[content-credentials

33. Source: pmc.ncbi.nlm.nih.gov
Link:https://pmc.ncbi.nlm.nih.gov/articles/PMC12351547/

34. Source: unric.org
Title: UN Regional Info Centre Artificial intelligence: What are deepfakes?
Link:https://unric.org/en/artificial-intelligence-what-are-deepfakes/

Published: May 15, 2026

35. Source: edmo.eu
Title: prebunking ai generated disinformation ahead of eu elections
Link:https://edmo.eu/publications/prebunking-ai-generated-disinformation-ahead-of-eu-elections/

36. Source: frontiersin.org
Link:https://www.frontiersin.org/journals/political-science/articles/10.3389/fpos.2026.1834093/full

37. Source: wsj.com
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Link:https://www.unicef.org/nepal/media/24126/file/Exploring%20impacts%20of%20generative%20Ai.pdf