Navigating and Addressing Public Concerns in AI: Insights From Social Media Analytics and Delphi

Abstract

The rapid advancement and integration of artificial intelligence (AI) in various domains of society have given rise to a complex landscape of public concerns. This research endeavors to systematically explore these concerns by employing a multi-stage methodology that combines large-scale social media data collection from Twitter and advanced text analytics. The study identifies seven distinct clusters of concerns, encompassing privacy and security, workforce displacement, existential risks, social and ethical implications, dependency on AI, misuse of AI, and lack of transparency. To further contextualize these findings, the Delphi method was employed to gather insights from AI ethics experts, providing a deeper understanding of the public’s apprehensions. The results underscore the critical need for addressing these concerns to foster public trust and acceptance of AI technologies. This comprehensive analysis offers valuable guidance for policymakers, AI developers, and stakeholders to navigate and mitigate the multifaceted issues associated with AI, ultimately contributing to more informed and responsible AI deployment. By addressing these public concerns, the study aims to pave the way for a more ethically sound and socially acceptable integration of AI into society, ensuring that the benefits of AI can be realized while minimizing potential risks and negative impacts. Through this systematic approach, the research highlights the importance of continuous monitoring and proactive management of AI-related concerns to sustain public confidence and promote beneficial AI innovation.

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