Exploring the Impacts of Automation on Employment: A Qualitative Study on Machine Learning and the Future of Work

Abstract

Rapid advancements in automation and machine learning technologies are transforming labor, posing advantages and challenges for jobs across all industries. In light of increased concerns about job displacement and the need for worker adaptation, this study aims to understand the multifaceted consequences of automation on employment dynamics. The purpose of this study is to investigate the qualitative effects of automation on employment, with an emphasis on how companies and workers respond to these changes. The study aims to shed light on the perspectives of those affected by automation by investigating productivity, job displacement, transformation, and governmental responses. To ensure that the benefits of automation are distributed equitably, the study addresses the critical question of how to safeguard those who face job loss. The theoretical framework of the study anaphases the interaction between labor market dynamics and technological innovation. A qualitative research methodology based on secondary data gathering is used in this study to investigate recent literature on automation and employment. The collection encompasses a diverse range of sources offering varying perspectives on automation's consequences. Key findings demonstrate that while automation poses a significant risk of job displacement, it also brings opportunities for work transformation and productivity increases. However, disparities in upskilling and support networks for workers could exacerbate inequality. Reliance on secondary data, which may not accurately reflect regional differences or individual experiences, is one of the shortcomings of the study. To completely understand worker experiences in automated systems, additional qualitative research is required, according to theoretical implications. The findings highlight the importance of targeted legislative initiatives and collaborative efforts between stakeholders to create a more equitable labor market that supports all workers' adaptation to technology innovations from a practical perspective.