Sabah Rasheed

As Goodhart's Law states: "When a measure becomes a target, it ceases to be a good measure." Job applicants have one primary goal during pre-employment assessment: to get the job. The problem is that most selection tools are designed and validated in relatively low-stakes contexts, where respondents have little reason to be anything other than honest. In hiring contexts, that assumption breaks down. Rasheed's research examines what happens when applicants misrepresent themselves on selection tools and what organizations can do to protect the validity and fairness of their hiring processes. She is increasingly interested in how artificial intelligence is complicating this further. How are candidates using AI to game assessments? How can HR leverage AI during hiring? These questions are reshaping personnel selection and remote measurement, and she believes they deserve scientific investigation. In the classroom, she is drawn to the same tension between science and practice. Good HR is not just about knowing the research' it is about knowing when and how to apply it. She aims to help students develop the critical thinking skills to navigate that gap. | Personnel selection, applicant faking, psychometrics, cognitive load, forced-choice measurement, employment interviews, virtual selection, AI in hiring, gamified assessment, workplace technology, organizational behaviour, human resource management

Sabah Rasheed is Assistant Professor at MacEwan University. Their stated interests include As Goodhart's Law states: "When a measure becomes a target, it ceases to be a good measure." Job applicants have one primary goal during pre-employment assessment: to get the job. The problem is that most selection tools are designed and validated in relatively low-stakes contexts, where respondents have little reason to be anything other than honest. In hiring contexts, that assumption breaks down. Rasheed's research examines what happens when applicants misrepresent themselves on selection tools and what organizations can do to protect the validity and fairness of their hiring processes. She is increasingly interested in how artificial intelligence is complicating this further. How are can. This summary considered all 2 collected sources.