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Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →No—available reporting does not show that ChatGPT wrote the recommendation letter submitted to Cambridge. University of Victoria academic Matt Huculak said he asked ChatGPT to generate an example of an excellent reference letter, then wrote his own letter using that output as a template and a foil against formulaic academic language. He later said the student received a University of Cambridge scholarship, but the reports do not establish that the letter caused the award.
What Huculak reportedly did
In an account published in April 2023, Matt Huculak—identified in the coverage as head of advanced research services at the University of Victoria—described an unusual drafting process. He prompted ChatGPT for an “excellent” reference-letter example. Rather than submit the generated text, he used it to help write a new letter himself.
Huculak said the exercise helped him move away from standardized recommendation-letter conventions. He described the finished letter as more personal and emotionally direct than the formulaic letters he was accustomed to seeing. Futurism, reporting on The Atlantic’s account, attributed to him the observation: “A dirty secret of academe is that most professors have a cache of letters separated into different categories,” and his description of the result as “the most ‘human’ and heartfelt letter I’ve written in a long time.”
Did ChatGPT write the letter that won the scholarship?
The evidence supports a narrower answer: ChatGPT generated an example, while Huculak wrote the recommendation that he says was ultimately used. The available reports do not say that the student submitted an AI-generated letter, and they do not identify ChatGPT as the author of the final document.
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India Today quoted Huculak calling the letter “among some of the best letters I’ve read” and praising its concise style, concrete examples and discussion of the candidate’s ability to collaborate. Those are Huculak’s assessments, not an evaluation from a Cambridge selector.
What is known about the Cambridge outcome
Huculak said the student later received a University of Cambridge scholarship. The reports do not name the student, the scholarship, its value, the selection criteria or any committee member who could explain the decision.
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That missing information matters. A scholarship result can reflect many parts of an application—academic records, research, references, interviews, personal statements and institutional priorities. The reported sequence shows that Huculak wrote a letter after consulting a generated example and that the student later received an award; it does not demonstrate that the letter caused the selection.
Why the distinction matters for recommendation letters
An example is not authorship
Using a language model to expose clichés or suggest an outline is different from outsourcing a recommender’s judgment. A credible reference must reflect the writer’s firsthand knowledge of the applicant, with details the writer can stand behind.
Specific evidence carries the letter
Huculak’s comments emphasized concrete examples and collaboration. Those qualities are valuable because they show what the applicant did, in what setting and with what result, rather than relying on interchangeable praise such as “hardworking” or “exceptional.” ChatGPT can produce polished generalities, but it cannot supply authentic observations that the recommender did not provide.
The recommender remains accountable
Even when software helps with brainstorming, the faculty member or supervisor signs their name to the final recommendation. They must verify every fact, remove invented details, protect confidential information and ensure the letter complies with the institution’s rules. This episode does not establish a current University of Cambridge or University of Victoria policy on generative AI.
What the 2023 reports do—and do not—prove
| Question | What the reporting supports |
|---|---|
| Who used ChatGPT? | Matt Huculak, of the University of Victoria, said he did. |
| What did ChatGPT produce? | An example of an “excellent” reference letter. |
| Was the submitted letter generated by ChatGPT? | Not according to the detailed account; Huculak said he wrote his own letter. |
| Did the student receive a Cambridge scholarship? | Huculak said the student later did. |
| Which scholarship or student? | Not identified in the available reports. |
| Did the letter cause the award? | Not established. |
A practical standard for responsible AI-assisted drafting
- Start with firsthand evidence. List the projects, decisions, skills and outcomes you personally observed.
- Use any generated draft only as a critique tool. Ask whether the structure exposes missing evidence or repetitive wording, rather than treating fluent prose as proof.
- Rewrite in your own voice. Replace generic claims with verifiable incidents and explain why they show readiness for the specific course, grant or scholarship.
- Check accuracy and confidentiality. Confirm names, dates, roles and achievements; do not paste private student records into a service without authorization.
- Follow the recipient’s rules. If an institution or scholarship body requires disclosure or prohibits generative-AI assistance, comply with that requirement.
Bottom line on the Cambridge scholarship story
The striking part of the story is not that an AI supposedly won a scholarship. It is that Huculak used a generated model to recognize and reject formulaic writing before composing a more personal recommendation himself. His account links that letter to a student’s later Cambridge scholarship, but the public reporting identifies neither the award nor evidence that the letter determined the result.
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