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Grammarly's AI Expert Review Allegedly Used Journalists' and Authors' Names Without Consent

5 news reports Snapshot 7 Sep 2026

In brief

An AI system built and deployed by Grammarly and Superhuman allegedly harmed Julia Angwin, Journalists and 5 others.

Risk domain
Malicious Actors & Misuse Fraud, scams, and targeted manipulation
Occurred
Coverage
5 reportsMar 2026

What happened

Grammarly's Expert Review feature allegedly used a large language model to generate editing suggestions presented under the names of journalists, authors, and academics without their consent. A federal class action filed by Julia Angwin claimed the feature misappropriated identities for commercial gain and attributed advice the named individuals never gave.

Laws that address this harm

Policy angle: Classified under Malicious Actors & Misuse (Fraud, scams, and targeted manipulation) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (5)

Titles link to the original publisher; report text is not reproduced here.

  1. Grammarly Is Facing a Class Action Lawsuit Over Its AI ‘Expert Review’ Feature
    wired.com · Miles Klee
  2. Class Action Alleges That Grammarly Misappropriated the Names of Journalists and Authors Through its “Expert Review” That Lets Users Get Feedback on Writing From Experts
    prf-law.com · Peter Romer-Friedman, PRF Law
  3. Grammarly pulls AI author-impersonation tool after backlash
    bbc.com · James W Kelly
  4. Grammarly removes AI Expert Review feature mimicking writers after backlash
    theguardian.com · Emma Loffhagen
  5. Why I’m Suing Grammarly
    nytimes.com · Julia Angwin

Who was involved

Alleged deployer
Grammarly, Superhuman
Alleged developer
Grammarly, Superhuman
Alleged harmed party
Julia Angwin, Journalists, Academics, Authors, Writers, Grammarly Users, Epistemic Integrity

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
—
Sectors
—
Countries
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Risk entries describing this failure mode

Entries from the MIT AI Risk Repository coded to subdomain 4.3.

  • Cheating/plagiarism

    "Cheating/plagiarism - Use of another person’s or group’s words or ideas without consent and/or acknowledgement."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • IP/copyright loss

    "IP/copyright loss - Misuse or abuse of an individual or organisation’s intellectual property, including copyright, trademarks, and patents."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Financial and business

    "Financial and Business - Use or misuse of a technology system in a manner that damages the financial interests of an individual or group, or which causes strategic, operational, legal or financial harm to a business or...

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Impersonation/identity theft

    "Impersonation/identity theft - Theft of an individual, group or organisation’s identity by a third-party in order to defraud, mock or otherwise harm them."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Dehumanisation/objectification

    "Dehumanisation/objectification - Use or misuse of a technology system to depict and/or treat people as not human, less than human, or as objects."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Defamation/libel/slander

    "Defamation/libel/slander - Use of a technology system to create, facilitate or amplify false perception(s) about an individual, group, or organisation."

    A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)

  • Misinformation and Manipulation

    "Recent studies have demonstrated that LLMs can be exploited to craft deceptive narratives with levels of persuasiveness similar to human-generated content (Pan et al., 2023b; Spitale et al., 2023), to fabri- cate fake n...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

  • Cybersecurity

    "LLMs may exacerbate cybersecurity risks in various ways (Newman, 2024). Firstly, LLMs may significantly amplify the effectiveness of deceptive operations aimed at tricking people into disclosing sensitive information or...

    Foundational Challenges in Assuring Alignment and Safety of Large Language Models (Anwar2024)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #1407 on the AI Incident Database · all 5 reports