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Fabricated content

As explained in Inside AI

Fabricated content is media or information that has been artificially created or altered to appear authentic despite not representing genuine events or facts.

Fabricated content is information or media created or altered to appear authentic even though it does not represent genuine facts or events. Generative AI can produce fluent, convincing material that is factually inaccurate or entirely fictional, making confident output unsafe to trust without verification. section 5.10 section 1.3

Invented legal cases

A lawyer submitted a brief containing six fictitious court cases, complete with fabricated quotations and citations, after ChatGPT affirmed that one nonexistent case was genuine and available in legal databases. The incident shows how plausible fabrication can become consequential when users trust an AI system without checking its claims. section 5.10

Repeatedly changing personal facts

When asked who Akli Adjaoute was, ChatGPT produced several different incorrect biographies, including an invented company, awards, education, and employment history. It returned an accurate response only after five attempts, demonstrating that fluent answers can vary while remaining false. section 5.3.2

Figure 5.1 ChatGPT prompt, which resulted in incorrectly identifying the author as the founder and CEO of a company he was not affiliated with.
figure

The figure shows a prompt that caused ChatGPT to assign a person to an unrelated company, making the mechanism of fabricated identity claims concrete. section 5.3.2

Fabricated content creates practical risks when it is:

  • Presented as legal, medical, or other authoritative guidance without independent review. section 5.10
  • Spread through social media, deepfakes, or realistic recordings to deceive or manipulate people. section 1.3
  • Accepted blindly because the output sounds coherent, especially by nontechnical users. section 1.3

How Inside AI covers it

How deep it goes
Demonstrates fabrication through contradictory biographies and fictitious legal cases, without explaining the underlying generation process.
Examples
Uses invented biographies, nonexistent court cases, harmful chatbot advice, and realistic deepfake video or audio as examples.
What you can do after
Diagnose unreliable output by comparing repeated answers with established information before relying on it.
How it connects
Connects fabricated content with generative AI, large language models, hallucination, misinformation, and deepfake technology.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Inside AI. The section links point to the parts of the book it draws on.