Short abstract:

This presentation explores the impact of AI on worker hiring and recruitment processes, focusing on the sociotechnical changes that AI brings. It emphasizes AI's role in contemporary recruitment and discusses "HR ghost work," and its ethical implications, especially for hiring practices.

Long abstract:

This presentation explores the realm of ghost work within the context of worker hiring processes and HR, where artificial intelligence (AI) is increasingly used to make recommendations and potentially decisions regarding job recruitment and hiring. The primary objective is to shed light on the profound sociotechnical transformations that AI brings to bear on contemporary recruitment practices. I look at the interplay between human decision-making and algorithmic systems in the recruitment landscape, emphasizing that even when AI systems take the spotlight in recruitment, humans remain as "ghosts-in-the-machine." The project provides a comprehensive examination of how algorithmic technologies, driven by artificial intelligence and machine learning, have radically transformed the recruitment domain. I explore how these technological advancements have given rise to 'AI ghost work in hiring processes,' a phenomenon where hidden human labor and prevalent machine intelligence converge to streamline and enhance the hiring process, albeit at times obscuring and concealing human tacit knowledge and expertise. My analysis reveals the multifaceted nature of ghost work, which significantly impacts the recruitment landscape. I look at the ethical implications of these sociotechnical transformations, including questions surrounding fairness, bias, and transparency in algorithmic decision-making. My focus centers on how Human Resource Management staff (HRM) are affected by AI utilization in this field, offering insights into the evolving dynamics of worker hiring processes, emphasizing the pivotal role played by sociotechnical transformations where AI intersects with HR practices.