Harnessing Gen-AI for Enhanced Public Engagement and Participatory Research: A Business and Management Perspective

Abstract

This manuscript explores the transformative potential of Generative Artificial Intelligence (Gen-AI) in enhancing public engagement and participatory research within the realm of business and management. It examines how Gen-AI technologies, including natural language processing, machine learning, and data analytics, can overcome traditional barriers to effective communication and collaboration between engineers, stakeholders, and the general public. The study investigates various applications of Gen-AI, such as NLP-powered chatbots for improved communication, AI-driven crowdsourcing platforms for data collection and analysis, and collaborative design tools for inclusive engineering solutions. Through case studies in smart city planning, renewable energy infrastructure, and transportation system redesign, the manuscript demonstrates the practical benefits of integrating Gen-AI into public engagement processes. While highlighting the potential for more inclusive, efficient, and impactful engineering projects, the research also addresses critical challenges and ethical considerations, including data privacy, algorithmic bias, and the need for transparency in AI decision-making. The manuscript concludes by proposing future directions for research and development in this rapidly evolving field, emphasizing the importance of responsible adoption and continuous refinement of Gen-AI technologies to foster more collaborative and socially relevant engineering outcomes.