"Cheating has long been an unwelcome but expected risk in the hiring process. While most people are honest and well-intentioned, there are always a handful of candidates who attempt to game the system. Today, however, the problem is evolving at an unprecedented speed. Generative AI has made new, more sophisticated types of cheating possible for any position, from software development to finance to design."
"So, why are candidates resorting to these methods? Sometimes, candidates are attempting to secure a position they're underqualified for, or otherwise gain a leg up in the hiring process. Other times, candidates pursue multiple full-time roles at once-a trend known as " overemployment "-which increases the likelihood that they'll cheat. Here are the four most common approaches candidates use to cheat, and what employers across all industries can do to detect and prevent dishonesty in their hiring processes."
"THE FOUR CHEATING TYPES 1. Copy-paste plagiarism This is the most widespread and fundamental form of cheating. A candidate is given a task-it could be a coding challenge, a writing sample, or a case study-and they simply copy or heavily borrow from existing resources found online. In some cases, candidates even use answer keys for standardized assessments, which are often sold or shared in online forums."
Generative AI has enabled more sophisticated cheating across roles such as software development, finance, and design. Candidates may cheat to secure positions they are underqualified for or to hold multiple full-time jobs simultaneously (overemployment). Four common cheating approaches are identified, including copy-paste plagiarism where candidates submit work taken from online sources or shared answer keys. Prevention strategies include creating many calibrated, rotated question versions so candidates do not see identical prompts, using assessment platforms that crawl the web to detect matches with public content, and designing individualized or proctored tasks to reduce copied submissions.
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