Exploring the Implementation of AI in Early Onset Interviews to Help Mitigate Bias
It addresses bias in hiring processes for companies, aiming to improve equity and diversity, but is incremental as it builds on existing AI interventions in recruitment.
This paper tackles bias in early-stage recruitment interviews by implementing an AI system that transcribes and analyzes interviews to emphasize skills over emotional sentiments, resulting in a 41.2% reduction in sentiment-driven biases.
This paper investigates the application of artificial intelligence (AI) in early-stage recruitment interviews in order to reduce inherent bias, specifically sentiment bias. Traditional interviewers are often subject to several biases, including interviewer bias, social desirability effects, and even confirmation bias. In turn, this leads to non-inclusive hiring practices, and a less diverse workforce. This study further analyzes various AI interventions that are present in the marketplace today such as multimodal platforms and interactive candidate assessment tools in order to gauge the current market usage of AI in early-stage recruitment. However, this paper aims to use a unique AI system that was developed to transcribe and analyze interview dynamics, which emphasize skill and knowledge over emotional sentiments. Results indicate that AI effectively minimizes sentiment-driven biases by 41.2%, suggesting its revolutionizing power in companies' recruitment processes for improved equity and efficiency.