misinformation
In plain wordsFalse or misleading information that spreads, whether or not the people sharing it know it is wrong. AI can produce it by mistake and makes it cheaper to create.
Content that is false or misleading, whatever the intentions of those who create or share it; deliberate falsehood is usually singled out as disinformationdisinformation, n.: Deliberate falsehoods or distortions dressed up as fact, for example from a government or campaign trying to sway an election or sow distrust., and true information released in order to do harm, such as leaked private records, as malinformation. AI affects misinformation in three ways. Generative models produce it unintentionally through hallucinationhallucination, n.: When an AI states something false or made up — a fake fact, quotation or source — fluently and confidently, as if it were true., for instance in chatbot answers or AI-written search summaries; they lower the cost of plausible text, images, audio and video that can be reused misleadingly (synthetic mediasynthetic media, n.: Images, video, audio or text created or substantially altered by AI rather than recorded or written directly by people, whether for art, entertainment, business or deception., deepfakesdeepfake, n.: A fake but realistic video, photo or voice recording made with AI that puts words in a real person's mouth or shows them in a scene that never happened.); and recommender systemsrecommender system, n.: Software that guesses which songs, products, posts or jobs you are most likely to want and shows those first, as when a video app lines up the next clip or a shop suggests an add-on. tuned for engagementengagement optimization, n.: Designing apps and AI to keep people clicking, watching or chatting for as long as possible because that earns money, even when it is not what is good for them. can amplify sensational falsehoods. AI is also used against it, in fact-checking support, claim matching and content moderationcontent moderation, n.: Checking what people post, or what an AI produces, and removing, limiting or labeling whatever breaks the rules or the law — done by people, by AI, or by both together.. Research finds exposure to online misinformation concentrated in small, already receptive audiences, so how much cheaper generation adds to its effects is debated.
The chatbot's answer about polling hours was misinformation, not a deliberate lie, but voters acted on it all the same.
Origin
In English since the late 16th century. The modern taxonomy separating mis-, dis- and malinformation was set out by Claire Wardle and Hossein Derakhshan in 'Information Disorder' (Council of Europe, 2017). The World Economic Forum's Global Risks Report 2024 ranked misinformation and disinformation, amplified by AI, as the most severe global risk over the following two years.
Usage note
Applying the label is contested in practice: judgments of falsity can be mistaken or politicized, and critics warn that broad anti-misinformation policies can suppress legitimate speech. Many researchers prefer narrower terms such as false claim, manipulated media or coordinated inauthentic behavior.
Related
- disinformationdisinformation, n.: Deliberate falsehoods or distortions dressed up as fact, for example from a government or campaign trying to sway an election or sow distrust.
- deepfakedeepfake, n.: A fake but realistic video, photo or voice recording made with AI that puts words in a real person's mouth or shows them in a scene that never happened.
- synthetic mediasynthetic media, n.: Images, video, audio or text created or substantially altered by AI rather than recorded or written directly by people, whether for art, entertainment, business or deception.
- hallucinationhallucination, n.: When an AI states something false or made up — a fake fact, quotation or source — fluently and confidently, as if it were true.
- liar's dividendliar's dividend, n.: The advantage dishonest people gain once everyone knows fakes are easy to make: they can wave away real evidence against them by claiming it was made by AI.
- filter bubblefilter bubble, n.: A situation in which you see mostly news and opinions you already agree with, because apps choose what to show you based on what you clicked before.
- content moderationcontent moderation, n.: Checking what people post, or what an AI produces, and removing, limiting or labeling whatever breaks the rules or the law — done by people, by AI, or by both together.
- disinformationdisinformation, n.: Deliberate falsehoods or distortions dressed up as fact, for example from a government or campaign trying to sway an election or sow distrust.
Sources
- Wardle, C. & Derakhshan, H. (2017). Information Disorder: Toward an interdisciplinary framework for research and policymaking. Council of Europe report DGI(2017)09.
- World Economic Forum (2024). The Global Risks Report 2024, 19th edition.
Mentioned in
content moderationcontent moderation, n.: Checking what people post, or what an AI produces, and removing, limiting or labeling whatever breaks the rules or the law — done by people, by AI, or by both together., disinformationdisinformation, n.: Deliberate falsehoods or distortions dressed up as fact, for example from a government or campaign trying to sway an election or sow distrust., filter bubblefilter bubble, n.: A situation in which you see mostly news and opinions you already agree with, because apps choose what to show you based on what you clicked before., influence operationinfluence operation, n.: An organized, often secret campaign to sway public opinion — fake accounts posting propaganda, for instance — which AI can make cheaper by writing posts, translating them and inventing fake personas., liar's dividendliar's dividend, n.: The advantage dishonest people gain once everyone knows fakes are easy to make: they can wave away real evidence against them by claiming it was made by AI., LLM groomingLLM grooming, n.: Flooding the internet with propaganda written mainly for machines rather than people, hoping AI chatbots will soak it up and repeat it to their users.