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AI Defamation & Hallucination Liability: Legal Guide

Table of Contents

When AI Makes Up Lies About You
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Artificial intelligence systems are generating false, defamatory statements about real people at an unprecedented scale. ChatGPT has accused innocent people of embezzlement and fraud. Bing’s AI has confused professionals with convicted terrorists. Google’s AI Overviews have made false claims about public figures. When AI fabricates accusations of crimes, sexual misconduct, professional incompetence, or other reputation-destroying falsehoods, victims face a novel legal question: Can you sue an AI company for defamation?

The answer is evolving—and the first major cases are now working through the courts.

May 2025
Walters Dismissed
First ChatGPT defamation case
$25M
Battle v. Microsoft
Terrorist name confusion
Unsettled
Section 230
No appellate AI ruling yet
4 States
Contributory Negligence
May bar AI victim claims

How AI Defamation Happens
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Hallucination: Fabricating False Facts
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Hallucination occurs when an AI system generates information that is completely fabricated—events that never happened, accusations never made, credentials never earned.

Example — Walters v. OpenAI: A journalist asked ChatGPT to summarize a real federal lawsuit. ChatGPT fabricated a legal complaint accusing radio host Mark Walters of embezzling funds from the Second Amendment Foundation. None of it was true:

  • Walters was never named in the actual lawsuit
  • He had never worked for the organization
  • The embezzlement allegation was entirely invented by ChatGPT

Juxtaposition: Confusing Identities
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Juxtaposition (or identity conflation) occurs when AI merges information about different people, applying true facts about one person to another with a similar name.

Example — Battle v. Microsoft: When users searched for aerospace educator Jeffery Battle, Bing’s AI provided information about Jeffrey Leon Battle—a convicted terrorist. The crimes were real. The terrorist was real. But applying those facts to the professor created devastating false accusations.

TypeWhat AI DoesExample
HallucinationFabricates facts entirelyChatGPT invents embezzlement allegation
JuxtapositionConfuses similar namesBing confuses professor with terrorist
MisattributionAttributes quotes/actions to wrong personAI credits statement to wrong expert
Context collapsePresents true facts misleadinglyAI presents acquittal as conviction

Why AI Defamation Is Different

Traditional defamation involves a human making a false statement. AI defamation raises novel questions: Did the AI “publish” the statement? Is the AI company the “speaker”? Can algorithms have the “fault” required for defamation? Does Section 230 protect AI-generated content? Courts are just beginning to answer these questions—and the answers will shape liability for years to come.

Landmark Cases
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Walters v. OpenAI (Georgia, 2025)
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The first ChatGPT defamation case—and the first dismissal.

AI Hallucination Defamation

Walters v. OpenAI

Dismissed
Summary Judgment for OpenAI

Radio host Mark Walters sued after ChatGPT fabricated a legal complaint accusing him of embezzling from a gun rights organization. Court granted summary judgment to OpenAI, finding the journalist who received the output could not have reasonably believed the fabricated accusation was true given ChatGPT's warnings about potential inaccuracies.

Ga. Superior Ct. May 2025

What Happened: On May 3, 2023, an editor at AmmoLand.com asked ChatGPT to summarize a real federal lawsuit. ChatGPT generated a false summary claiming Walters had embezzled funds—an accusation entirely invented by the AI.

Why OpenAI Won:

The Georgia Superior Court granted summary judgment to OpenAI on May 19, 2025, finding:

  1. No “reasonable reader” would believe: The editor received multiple warnings that ChatGPT could not access the internet, could not view the linked complaint, and that the lawsuit was filed after ChatGPT’s knowledge cutoff date.

  2. Red flags ignored: These warnings should have alerted a reasonable person that the AI’s output might be inaccurate.

  3. No reputational damage: The editor who received the false statement didn’t think less of Walters as a result—he recognized something was wrong.

  4. Fault not proven: Under defamation law, plaintiffs must prove the defendant acted with fault (negligence for private figures, actual malice for public figures). The court found insufficient evidence of fault given OpenAI’s warnings.

What Walters Does NOT Mean:

  • AI hallucinations can still be defamatory — The case didn’t hold that AI outputs can never be defamatory
  • Different facts could win — If the recipient had believed and republished the false statement, the outcome might differ
  • Section 230 not decided — The court ruled on traditional defamation grounds, not Section 230 immunity

Key Takeaway from Walters

The Walters ruling hinged on who received the output and what they believed. A journalist who ignored obvious warning signs couldn’t prove reputational harm. But if a less sophisticated user had received and believed the output—or if the false statement had been widely republished—the calculus could change entirely.

Battle v. Microsoft (Maryland, 2023-Present)
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The $25 million identity confusion case—now in arbitration.

AI Identity Conflation

Battle v. Microsoft

$25 Million
Moved to Arbitration

Aerospace educator Jeffery Battle sued Microsoft after Bing's AI confused him with convicted terrorist Jeffrey Leon Battle. When users searched Battle's name, the AI returned information about the terrorist's crimes. Microsoft moved to compel arbitration; the court granted the motion in October 2024. The case will be resolved privately.

D. Maryland 2023-Present

What Happened: In July 2023, Professor Jeffery Battle discovered that searching his name in Bing returned AI-generated content conflating him with Jeffrey Leon Battle, a member of the “Portland Seven” convicted of terrorism-related charges in 2003.

Legal Theory: Unlike Walters (pure fabrication), Battle involves misattribution of true facts. The terrorist’s crimes were real—but attributing them to an innocent professor with a similar name is defamatory.

Current Status: On October 23, 2024, the court granted Microsoft’s motion to compel arbitration. The case has been stayed pending private arbitration, meaning:

  • No public trial
  • No published court opinion
  • No precedent set for AI identity confusion cases
  • Resolution will be confidential

The Legal Framework for AI Defamation#

Elements of Defamation
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To win a defamation claim against an AI company, you must prove:

ElementWhat You Must ShowAI-Specific Challenges
PublicationStatement communicated to third partyDid AI “publish” or did user?
False Statement of FactNot opinion, not trueAI may present fabrications as facts
About the PlaintiffIdentifies you specificallyAI may use your name but mean someone else
FaultNegligence (private) or actual malice (public)Can algorithms have “fault”?
DamagesHarm to reputationMust show actual reputational injury

The Fault Requirement
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Defamation requires proving the defendant acted with fault—the level depends on who you are:

Private Figures: Must prove negligence—that the defendant failed to exercise reasonable care.

Public Figures: Must prove actual malice—that the defendant knew the statement was false or acted with reckless disregard for the truth. (From New York Times v. Sullivan, 1964)

For AI Companies:

  • Did warnings about inaccuracy constitute “reasonable care”?
  • Does knowing AI hallucinates constitute “reckless disregard”?
  • Can algorithms have the mental state required for “actual malice”?

These questions remain unsettled.

Section 230: The Uncertain Shield
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Section 230 of the Communications Decency Act (47 U.S.C. § 230) generally immunizes online platforms from liability for content provided by users. But does it protect AI-generated content?

Arguments Against Section 230 Protection:

ArgumentExplanation
AI creates contentSection 230 protects platforms for “information provided by another”—AI content is provided by the AI, not users
Not “neutral conduit”AI doesn’t just host content; it generates it
Developer responsibilityTraining data, architecture, and deployment choices make AI companies “information content providers”

Arguments For Section 230 Protection:

ArgumentExplanation
User-initiatedOutput depends on user prompts; AI is a tool
Training dataAI reflects patterns in third-party data, not original creation
Tool, not publisherAI is more like a search engine than an author

Current Status:

  • No appellate court has definitively ruled on Section 230 for generative AI
  • Walters avoided Section 230 entirely, ruling on traditional defamation grounds
  • OpenAI has not invoked Section 230 in defamation cases—likely recognizing it’s weak for AI-generated content
  • Legal consensus emerging: Section 230 probably doesn’t protect pure AI hallucinations

Section 230 Is NOT a Guarantee

AI companies and platforms should not assume Section 230 immunizes them from defamation claims. Most legal analysts believe Section 230 was designed for user-generated content, not AI-generated content. Courts may well find that AI companies are “information content providers” responsible for their systems’ outputs.

State Law Variations
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Contributory Negligence States
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Four states follow pure contributory negligence—if you’re even 1% at fault, you recover nothing:

StateRuleImpact on AI Defamation
North CarolinaPure contributoryUser who didn’t verify AI output may be barred
VirginiaPure contributorySame
MarylandPure contributoryBattle case jurisdiction
AlabamaPure contributorySame
District of ColumbiaPure contributorySame

In these jurisdictions, if a court finds you contributed to your own harm by not fact-checking AI output (as a publisher), you may recover nothing.

Comparative Negligence States
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Most states use comparative negligence—your recovery is reduced by your percentage of fault but not eliminated unless you’re 50%+ at fault (modified) or any percentage (pure).

State Defamation Statutes
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Some states have specific defamation protections:

  • California: Anti-SLAPP statute may apply to AI company defense motions
  • New York: Plaintiff-friendly defamation standards
  • Texas: New AI liability provisions under Texas Responsible AI Governance Act (June 2025)

Building a Case Against AI Companies
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Evidence to Preserve
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Evidence TypeWhy It Matters
Screenshots of AI outputProves the defamatory statement existed
TimestampsEstablishes when statement was generated
Prompts usedShows what user asked for vs. what AI provided
Warning messages (or lack)Relevant to fault analysis
Publication evidenceShows third parties saw the content
Reputational harmLost business, social consequences, emotional distress

Immediate Steps
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  1. Screenshot everything — Capture the exact AI output before it changes
  2. Document the prompt — Record exactly what was asked
  3. Note the platform/model — ChatGPT, Bing AI, Google AI, Claude, etc.
  4. Preserve context — Were warnings displayed? What was the user interface?
  5. Track republication — Did others share or rely on the false information?
  6. Document harm — Lost opportunities, damaged relationships, emotional impact

Challenges in AI Defamation Cases
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Identifying the Defendant:

  • Is it the AI model developer (OpenAI, Google)?
  • The platform deploying it (Microsoft Bing)?
  • The user who prompted it?
  • All of the above?

Proving Fault:

  • AI companies argue their warnings constitute reasonable care
  • Proving “actual malice” for public figures is extremely difficult
  • Algorithmic decision-making doesn’t fit traditional fault frameworks

Forced Arbitration:

  • Many AI platforms require arbitration in terms of service
  • Battle v. Microsoft was moved to private arbitration
  • Class actions may be precluded

Legislative Developments
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Federal Activity
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No Section 230 Immunity for AI Act (2023):

  • Introduced by Senators Hawley (R-MO) and Blumenthal (D-CT)
  • Would have waived Section 230 immunity for AI-generated content
  • Did not pass due to concerns about chilling AI innovation

Artificial Intelligence Risk Evaluation Act (2025):

  • Introduced by Senator Hawley
  • Addresses AI risks but doesn’t specifically cover defamation

State Legislation
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Texas Responsible AI Governance Act (June 2025):

  • Establishes liability with fines up to $200,000 per violation
  • Covers intentional abuses: facilitating crimes, creating deepfakes, unlawful discrimination
  • Does not explicitly cover defamation but signals regulatory attention

California AI Legislation:

  • Various AI bills passed, primarily focused on transparency and discrimination
  • Defamation not specifically addressed

Legislative Gap

No federal or state law specifically addresses AI-generated defamation. Victims must rely on traditional defamation law—which wasn’t designed for algorithmic speech. This legislative gap creates uncertainty for both plaintiffs and AI companies.

Frequently Asked Questions
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Related Practice Areas#

Related Resources#


Has AI Defamed You?

When ChatGPT, Bing, or other AI systems generate false accusations about you—fabricating crimes you didn't commit, confusing you with criminals, or inventing professional misconduct—you may have legal recourse. While AI defamation law is still evolving, the first cases are establishing important precedents. Connect with attorneys who understand both defamation law and AI technology.

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