Do you remember worrying that your resume made with LLM might not pass some selection in the HR system where you are applying? You can stop worrying, it's the opposite.

Do you remember worrying that your resume made with LLM might not pass some selection in the HR system where you are applying? You can stop worrying, it's the opposite. Researchers studied the scenario: a candidate writes a resume using LLM, and the company then screens this resume, also through LLM – that is, a robot writes, a robot reads, and a human somewhere in the corner drinks coffee and hopes that they hire a decent person. The article has two conclusions: 1. Resumes rewritten by LLM more often pass the automatic selection. In simulations, candidates who used the same LLM as the evaluation system ended up in the shortlist noticeably more often than similar candidates with resumes made manually – about 20-60% more often. 2. The scoring turned out to be biased. The model does not just make a conclusion like: “oh, this is better written,” it seems to recognize its style and prefer texts similar to its own – the authors call this self-preference bias: the model tends to love content that it could have written itself, a little digital narcissism. So the fear of “I won’t be invited to the interview because the resume was written with AI” may not be the main concern. The main risk is different: you may **NOT** be invited precisely because the resume does not sound like the native dialect of the evaluation model. Earlier, people tailored their CVs to the recruiter; now they need to tailor them to the model.