A Multimoded Square to Evaluate Interviews

Abstract Job recruitment and preparation processes are being simplified by the introduction of Artificial Intelligence (AI). An AI-enabled interview assistant has been developed within this extremely AI-focused world. The goal is to make interviews better for the interviewers and candidates in all aspects including efficiency and fairness. Functions like natural language processing, machine learning, and speech recognition allow for the creation of mock interviews wherein candidates are given personalized feedback and their responses are analysed against pre-set metrics like relevance, tone, and behaviour. Interviewers, on the other hand are provided with pre-screening, candidate grading, and interview summarization tools that help to lower bias and scope of human effort. The assistant further supports video interviews, question prep based on the candidate’s CV, multiple languages, and several other functions. Such extensive automation helps candidates with adequate preparation to secure optimal positions in the increasingly competitive workforce. Advancing technology, especially artificial intelligence is shaping the world at an unprecedented pace as the world adjusts to the new normal. AI focused technology has led to the development of automated interview tools. These tools promise to provide a solution to the issues of inefficient, biased, and unnecessarily long interviews like the traditional ones.