Leveraging AI for a Mock Interview Platform: ...

Leveraging AI for a Mock Interview Platform: A Case Study for STEM Graduates

Author Name : Samuel Johnson

ABSTRACT AI has impacted STEM education and expanded employment by implementing new approaches to standard problems. Pre-interview assessment sites employing artificial intelligence enable candidates to prepare for STEM job interviews while saving cost and time. These platforms incorporate tools, including NLP and machine learning algorithms, to estimate technical and behavioral performance constructively and objectively in real-time. In contrast to conventional mock interviews that are generally subjective, available in limited numbers, and expensive to administer, AI platforms result in more effective interview simulations based on the candidate's skills and the requirements for the specific job. These call for coding excellence, system design questions, and soft skills whereby applicants are tested and allowed to demonstrate problem-solving, communication, and leadership. Utilizing interview questions and answers based on a candidate's performance provides flexibility that the market has yet to embrace fully. The extensibility and availability of the platforms also do well in fulfilling the shortage of mock interviews for candidates, especially where they are in regions or have limited access to such services. However, some key challenges still exist, including bias in the AI systems and data privacy issues. Adjusting the machine learning model's data sets, including interview data and user feedback, is crucial for enhancing precision and pertinence. When applied and adopted, AI can enhance the production of interview preparation content for STEM graduates across the globe, thereby equalizing chances for talented and deserving candidates while reinventing the recruitment process.