Misinformation
Misinformation is false or misleading information that is presented or circulated, whether or not there is an intent to deceive.
Inside AI
Misinformation is false or misleading information disseminated without the defining intention to manipulate or deceive.
- How it is used
- Frames false AI-generated claims and their spread as risks to informed decisions and public trust.
- How deep it goes
- Defines the distinction from intentional disinformation through examples and consequences, without detailing a formal detection procedure.
- Examples
- Uses invented court cases, false biographical claims, and misleading antivaccination recommendations to make the risk concrete.
- What you can do after
- Evaluate/understand it by checking consequential AI-generated claims and citations rather than trusting confident wording.
Introduction to Generative AI, Second Edition
Misinformation is false or misleading information that is presented or circulated without necessarily implying deliberate deception.
- How it is used
- Frames false or misleading information as a governance, safety, and sociotechnical risk of generative AI.
- How deep it goes
- Explains classification difficulty, propagation mechanisms, harms, and policy tensions, but stops short of detection or mitigation procedures.
- Examples
- Uses election deepfakes, cloned-voice scams, fabricated accusations, and false chatbot-generated legal claims as concrete cases.
- What you can do after
- Evaluate/understand how generative systems can create, repeat, scale, and complicate responses to misleading information.
Read how Introduction to Generative AI, Second Edition explains misinformation →
Sutskever's List
Misinformation is false or misleading information, whether produced or distributed deliberately or unintentionally.
- How it is used
- Frames generative AI’s ability to produce credible false or misleading content as a potential social and security risk.
- How deep it goes
- Defines the category and illustrates its risk through model capabilities, but stops short of analyzing detection or mitigation methods.
- Examples
- Uses GPT-2-generated news articles, persuasive essays, and the fictional “Ovid’s Unicorn” narrative as concrete examples.
- What you can do after
- Evaluate how coherent generated text can increase the plausibility and misuse potential of misinformation.
Build a Text-to-Image Generator (from Scratch)
False or inaccurate information that is presented or circulated as factual, regardless of whether deception is intended.
- How it is used
- Frames misinformation as a societal risk arising from realistic text-to-image outputs and their potential misuse.
- How deep it goes
- Defines the misuse and names moderation, governance, collaboration, and deepfake detection, but does not detail detection implementation.
- Examples
- Uses a 2024 political robocall and proposes distinguishing real images from deepfakes with a fine-tuned ResNet.
- What you can do after
- Diagnose deepfake-related misinformation with a fine-tuned ResNet approach and apply content-moderation safeguards.
Read how Build a Text-to-Image Generator (from Scratch) explains misinformation →
Related concepts
- generative modelingproduced by · Generative modeling is a machine-learning approach that learns patterns or a data distribution to generate new samples resembling the data.
- disinformationcontrasts with · Disinformation is false or misleading information deliberately created or spread to deceive, manipulate, or influence people.
- hallucinationproduced by · A hallucination is model-generated content that is false, fabricated, or unsupported by relevant evidence but presented as plausible or factual.
- ChatGPTproduced by · ChatGPT is OpenAI’s conversational AI service, which lets users interact with generative AI models and related tools through natural-language prompts.
- language modelproduced by · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
- content policyaddressed by · A content policy is a set of rules governing which user- or model-generated content a service permits, restricts, or prohibits and how violations are handled.
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