AI work

The résumé is dying, and AI is holding the smoking gun

Beyond volume, fraud poses an increasing threat. In January, the Justice Department announced indictments in a scheme to place North Korean nationals in remote IT roles at US companies. Research firm Gartner says that fake identity cases are growing rapidly, with the company estimating that by 2028, about 1 in 4 job applicants could be fraudulent. And as we have previously reported, security researchers have also discovered that AI systems can hide invisible text in applications, potentially allowing candidates to game screening systems using prompt injections in ways human reviewers can’t detect.

Illustration of a robot generating endless text, controlled by a scientist.

And that’s not all. Even when AI screening tools work as intended, they exhibit similar biases to human recruiters, preferring white male names on résumés—raising legal concerns about discrimination. The European Union’s AI Act already classifies hiring under its high-risk category with stringent restrictions. Although no US federal law specifically addresses AI use in hiring, general anti-discrimination laws still apply.

So perhaps résumés as a meaningful signal of candidate interest and qualification are becoming obsolete. And maybe that’s OK. When anyone can generate hundreds of tailored applications with a few prompts, the document that once demonstrated effort and genuine interest in a position has devolved into noise.

Instead, the future of hiring may require abandoning the résumé altogether in favor of methods that AI can’t easily replicate—live problem-solving sessions, portfolio reviews, or trial work periods, just to name a few ideas people sometimes consider (whether they are good ideas or not is beyond the scope of this piece). For now, employers and job seekers remain locked in an escalating technological arms race where machines screen the output of other machines, while the humans they’re meant to serve struggle to make authentic connections in an increasingly inauthentic world.

Perhaps the endgame is robots interviewing other robots for jobs performed by robots, while humans sit on the beach drinking daiquiris and playing vintage video games. Well, one can dream.

AI use damages professional reputation, study suggests

AI, AI assistants, AI study, AI work, Biz & IT, chatgpt, chatgtp, Duke University, large language models, machine learning / Mike M. / May 10, 2025

Using AI can be a double-edged sword, according to new research from Duke University. While generative AI tools may boost productivity for some, they might also secretly damage your professional reputation.

On Thursday, the Proceedings of the National Academy of Sciences (PNAS) published a study showing that employees who use AI tools like ChatGPT, Claude, and Gemini at work face negative judgments about their competence and motivation from colleagues and managers.

“Our findings reveal a dilemma for people considering adopting AI tools: Although AI can enhance productivity, its use carries social costs,” write researchers Jessica A. Reif, Richard P. Larrick, and Jack B. Soll of Duke’s Fuqua School of Business.

The Duke team conducted four experiments with over 4,400 participants to examine both anticipated and actual evaluations of AI tool users. Their findings, presented in a paper titled “Evidence of a social evaluation penalty for using AI,” reveal a consistent pattern of bias against those who receive help from AI.

What made this penalty particularly concerning for the researchers was its consistency across demographics. They found that the social stigma against AI use wasn’t limited to specific groups.

Fig. 1. Effect sizes for differences in expected perceptions and disclosure to others (Study 1). Note: Positive d values indicate higher values in the AI Tool condition, while negative d values indicate lower values in the AI Tool condition. N = 497. Error bars represent 95% CI. Correlations among variables range from | r |= 0.53 to 0.88. — Fig. 1 from the paper “Evidence of a social evaluation penalty for using AI.” Credit: Reif et al.

“Testing a broad range of stimuli enabled us to examine whether the target’s age, gender, or occupation qualifies the effect of receiving help from Al on these evaluations,” the authors wrote in the paper. “We found that none of these target demographic attributes influences the effect of receiving Al help on perceptions of laziness, diligence, competence, independence, or self-assuredness. This suggests that the social stigmatization of AI use is not limited to its use among particular demographic groups. The result appears to be a general one.”

The hidden social cost of AI adoption

In the first experiment conducted by the team from Duke, participants imagined using either an AI tool or a dashboard creation tool at work. It revealed that those in the AI group expected to be judged as lazier, less competent, less diligent, and more replaceable than those using conventional technology. They also reported less willingness to disclose their AI use to colleagues and managers.

The second experiment confirmed these fears were justified. When evaluating descriptions of employees, participants consistently rated those receiving AI help as lazier, less competent, less diligent, less independent, and less self-assured than those receiving similar help from non-AI sources or no help at all.

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