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Grammarly did offer an “Expert Review” feature in early March 2026, but it did not connect writers with real professors or authors. The feature generated AI feedback framed through named intellectual personas, including deceased historian David Abulafia and figures such as William Zinsser and Carl Sagan. The result was controversy over consent, implied endorsement, posthumous identity, and whether plausible AI suggestions can borrow the authority of a real scholar.
What Grammarly’s Expert Review feature actually did
Expert Review appeared inside Grammarly’s writing environment as an option for requesting feedback on submitted text. Users could select a named “expert” and receive AI-generated suggestions associated with that person’s published work or recognizable intellectual approach.
Reports described a mix of stylistic suggestions, line-level recommendations, and broader comments about a manuscript’s clarity, organization, argument, or audience. “Manuscript review” was the product’s framing and media shorthand, but the feature was not a formal editorial review. It was better understood as AI-generated writing feedback presented through named expert personas.
That distinction matters. Grammar correction fixes or flags language mechanics. Editorial feedback can address structure and clarity. Writing coaching may help an author revise. Expert emulation adds a persona or intellectual frame. None of those is automatically equivalent to academic peer review.
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Why David Abulafia’s appearance caused backlash
The controversy intensified after historian Verena Krebs, a professor at Ruhr University Bochum, shared a screenshot showing David Abulafia as an available expert for manuscript feedback. Abulafia had died in January 2026. Vanessa Heggie, an associate professor at the University of Birmingham, then publicly criticized the apparent use of living and deceased academics as simulated reviewers.
These reports identify the widely discussed starting points of the backlash, not necessarily the first time anyone encountered the feature. The discovery was especially striking because a user could apparently select a recently deceased historian as though requesting his advice were an ordinary product action.
Which people were represented?
Coverage identified examples from several different categories rather than one clearly documented, fixed roster. Reported names included:
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- David Abulafia, the historian who died in January 2026;
- William Zinsser, author and editor;
- Carl Sagan, astronomer and science communicator;
- Stephen King and Neil deGrasse Tyson;
- Steven Pinker and Gary Marcus;
- Kara Swisher; and
- Isaac Newton, reportedly found among available or generated personas in later coverage.
WIRED also reported testing feedback associated with figures including William Strunk Jr., Pierre Bourdieu, Margaret Mitchell, and Virginia Tufte. The exact selection could have varied by account, plan, country, platform, rollout stage, or date, so these examples should not be treated as a complete universal catalog.
Were the real experts involved?
There is no evidence in the reviewed reporting that the named experts had authorized or participated in the reviews. WIRED reported that Stephen King and Neil deGrasse Tyson did not respond to requests for comment. Philosopher John Kaag, quoted by Times Higher Education, said the presentation could imply participation or endorsement that had not been agreed to.
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That is more precise than saying categorically that every person was unauthorized. Permission, representation, and legal rights can differ from one individual, estate, or jurisdiction to another.
Grammarly CEO Shishir Mehrotra reportedly said the system used publicly available information and third-party large-language models to provide suggestions “inspired by” the published work of influential voices. Grammarly’s position was that the feature did not claim that the actual people had reviewed a user’s writing.
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Why deceased scholars raised a separate concern
Consent and posthumous identity
A deceased person cannot personally approve a new use of their name or persona. But the legal consequences are not simple. Possible issues include publicity-rights law, estate arrangements, copyright, trademark, unfair competition, and the distinction between commercial, expressive, educational, and transformative uses. Those rules vary by jurisdiction.
The reporting establishes public criticism and a reported lawsuit; it does not establish a final legal ruling that Grammarly violated any particular law. Times Higher Education reported on the lawsuit and the company’s explanation.
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Authority laundering
Attaching a famous scholar’s name to generic or uncertain advice can make that advice appear more credible. A user may infer that the scholar would have approved an argument, held the position expressed by the AI, or personally endorsed the revision.
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A simulated historical figure may respond using present-day assumptions, later data, or language that does not fit the person’s era. The output can then look like an authentic continuation of the scholar’s thinking even when it is anachronistic.
False intimacy
The appeal of the product is understandable: writers want to know what a celebrated author, historian, or scientist might say about their work. But the experience can replace genuine scholarly engagement with a persuasive fiction, especially for students or inexperienced writers.
This was not peer review
Expert Review was not equivalent to:
- journal peer review;
- an editorial-board assessment;
- a dissertation adviser’s critique;
- subject-matter consultation;
- fact-checking or source verification;
- methodological review;
- legal review; or
- an authenticated opinion from the named person.
An AI model can generate plausible comments without establishing that an argument is novel, evidence is interpreted correctly, citations support the claims, methods are valid, data are reproducible, or a manuscript is suitable for publication. The most accurate description is AI-generated feedback framed through named intellectual personas.
What independent testing showed
WIRED reported that it tested the tool and reproduced recommendations attributed to several named experts, including David Abulafia, Steven Pinker, and Gary Marcus. Its reporting also found the system describing suggestions as drawing on ideas associated with multiple living and deceased figures.
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That testing demonstrates that the feature could produce persona-associated recommendations. It does not prove that the output contained distinctive expert knowledge or accurately represented any individual’s views. The key questions are whether the advice was traceable to the person’s actual publications, whether the system cited those sources, whether it invented positions or quotations, and whether the persona changed the substance of the critique or merely its tone.
A useful test for any similar product is simple: Would the feedback still be useful and appropriately qualified if the famous name were removed? If the name supplies most of the authority, the product is selling reputation as much as editorial assistance.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Legal and ethical questions are not identical
Critics described the practice using terms such as “impersonation” and “necromancy.” Those labels capture the ethical discomfort, but they do not settle the legal analysis. A legal claim may depend on where the user, company, individual, or estate is located; how the name and likeness were used; whether the use was commercial; and whether the material was protected by copyright or other rights.
Copyright also does not automatically give someone ownership of every idea associated with them. At the same time, using a recognizable person’s identity to market a service can raise concerns beyond copyright, including publicity rights, misleading endorsement, reputation, and unfair competition.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsThe strongest general criticism is therefore not “the feature was proven illegal.” It is that the product could turn a person’s identity and intellectual reputation into a commercial interface without making the limits of the simulation sufficiently clear.
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What happened to Expert Review?
After the backlash, Futurism reported that Grammarly was pulling down the controversial feature. “Pulled down” should be read as a reported product change rather than a precise official description of whether the feature was disabled everywhere, renamed, restricted, or removed only from some accounts or regions.
As of the research date, Grammarly’s official public materials emphasize its broader Superhuman product direction, including AI writing assistance, Docs, AI Rewriter, education-oriented features, and Authorship. Its current support information does not present Expert Review as an ongoing public offering. See Grammarly’s current product overview.
Grammarly also says that its generative AI features are optional and can be controlled through feature customization. It warns that AI detectors cannot conclusively determine whether AI was used. Those controls and warnings do not turn AI feedback into peer review, but they are relevant to writers deciding whether to use current writing tools. More information is available in Grammarly’s support guidance on AI controls and detection.
What writers should use instead
- Self-edit the argument and structure. Identify the thesis, evidence, assumptions, gaps, and intended audience before asking software to polish sentences.
- Ask a qualified human reviewer. A supervisor, coauthor, departmental writing center, disciplinary society, or subject-matter consultant can evaluate questions that an AI persona cannot authenticate.
- Use an editor for the right job. Copyediting, substantive editing, language polishing, and developmental editing are different services. Define the scope before sharing a manuscript.
- Verify every citation and quotation manually. AI feedback can produce confident but unsupported interpretations or invented references.
- Check the target journal or institution’s AI policy. Disclosure, authorship, confidentiality, and permitted-use rules differ.
- Protect unpublished work. Do not upload confidential, embargoed, proprietary, or unpublished material without checking the service’s data terms and your institution’s requirements.
- Treat AI feedback as brainstorming or copyediting support. It may help expose clarity or organization problems, but it is not scholarly validation.
Academic-focused tools such as Paperpal, Writefull, and ProWritingAid may offer language or editorial assistance, but they remain AI systems and should be evaluated for privacy, citation accuracy, institutional acceptance, and disclosure requirements. Human editing services such as Scribendi, Enago, Editage, and American Journal Experts can provide defined editing services, but pricing, expertise, confidentiality, and scope must be checked directly.
The practical rule is straightforward: if you need an actual expert’s judgment, ask a real expert who has agreed to review the work. No writing assistant should be presented as equivalent to that relationship.
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