Hello World is a special edition newsletter that goes deep into our original reporting, our own interactions with technology and the questions we put to big thinkers in the field.
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we → go → field
Hello world,
My name is Andrew Losowsky, and I’m Product Director & Editor at The Markup and CalMatters.
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I → ’m → Markup
A few months ago, we wanted to hire a new engineer.
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we → want → engineer
Hiring is always a lengthy process, but this time I had to wade through what felt like an ocean of generative AI slop.
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what → have → slop
Fake and exaggerated resumes have always existed, but now, thanks to the rise of AI tools, it’s incredibly hard to know who is even real.
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who → exist → tools
I get why people use AI tools to find work.
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people → get → work
Every employer wants to feel special, but applying takes so long that, according to a recent report, 65% of jobseekers use AI automation tools to find work, including some that promise to “tailor your resume for each role.”
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that → want → role
And why not, if employers are using AI to screen resumes anyway?
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employers → use → resumes
(We don’t do this.)
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We → do → this
Within 12 hours of posting the role, we received more than 400 applications.
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we → post → applications
At first, most of these candidates seemed to be genuine.
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most → seem → candidates
However, as the person who had to read them all, I quickly saw some red flags, which were all clear indicators of inauthenticity:
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which → have → inauthenticity
- Contact information, such as email addresses and phone numbers, was repeated across multiple applicants, although their names didn’t always match the names in the email addresses.
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names → repeat → addresses
In at least one case, two totally different resumes were submitted under the same name, mailing address, and phone number.
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resumes → submit → name
- Some email addresses were formatted in a particular way, with a full name and a seemingly random number, often followed by
.dev@gmail.com
.
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addresses → format → .dev@gmail.com
- Mailing addresses were located in commercial-only areas but weren’t post office boxes.
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addresses → locate → areas
- Resumes had identical design patterns, including bolding certain phrases connected to skills and experiences.
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Resumes → have → skills
- LinkedIn addresses were either broken, led to near-empty profiles, or contained profiles listing different employers from the resume.
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addresses → break → resume
These suspicions were reinforced by the answers that these inauthentic candidates gave to questions on our application form.
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candidates → reinforce → form
As part of our hiring process, we asked applicants why they wanted to work with us and which projects they were most proud of.
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they → ask → projects
We didn’t prohibit using AI to help write applications, but what we received went a lot further than using it for guidance around phrasing or language.
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received → prohibit → phrasing
- Responses to “Why do you want to work with us?” followed a near-identical four-sentence pattern with minor variations:
“I want to work with you because…” with a summary of the first section of our About page
“As an engineer, I enjoy…” with a summary of the top of the job posting
“I’m particularly interested in…” with a summary of the second section of our About page
“While I haven’t worked in journalism before…” with a summary of the rest of the job posting -
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I → want → posting
A few applications even included “ChatGPT says” in their answers, without acknowledging why or how they’d used ChatGPT.
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they → include → ChatGPT
Most obviously suspect: In several resumes, the work didn’t correspond with that of the stated employer but almost perfectly matched our job description.
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work → correspond → description
One applicant reported working for a trucking company, and, as part of their job, they “often worked closely with journalists to create data dashboards and visualizations.”
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they → report → dashboards
In the most extreme case, one person claimed they had built our website and Blacklight tool (they hadn’t).
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they → claim → website
After less than a day, we removed our ad from ZipRecruiter, Glassdoor and Indeed.com, and relied on our own outreach to get applicants.
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we → remove → applicants
Following this, the flood of probable inauthenticity slowed to a trickle.
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flood → follow → trickle
I was curious about our probably fake applicants, so I followed up with some of them.
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I → follow → them
His students suddenly started getting A’s.
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students → start → ’s
Did a Google AI tool go too far?
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tool → go → ?
Some teachers say that AI tools, particularly Google Lens, have made it impossible to enforce academic integrity in the classroom — with potentially harmful long-term effects on students’ learning.
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it → say → learning
Several candidates said they had worked for PixelFyre Code Labs, “an information business helping all businesses succeed,” whose web address goes nowhere and seems only to exist on LinkedIn.
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address → say → LinkedIn
One of them said he couldn’t discuss his past journalism work because “most of the work was under NDAs or white-label partnerships.”
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most → say → NDAs
I tried to set up a phone call anyway, but he never responded to multiple emails.
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he → try → emails
One person’s resume showed relevant experience but contained several of the red flags I mentioned earlier.
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I → show → flags
By chance, I happened to have a professional contact at a company listed on his application – and, to my surprise, my contact not only confirmed the candidate’s past employment but also highly recommended him, so I set up a video interview.
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I → happen → interview
When asked why he wanted to work for us, he said, “I want to work for you because you’re doing cutting-edge technologies…
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you → ask → technologies
You’re a fast company growing ‘fastly’, and I’m looking for new experiences.”
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I → ’re → experiences
He said he lived in Morrisville, N.C., and when I asked what he liked about the town, he said “The temperature — the weather is amazing.”
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weather → say → town
…and 12 more, not listed.
