PUBLIC PERCEPTION, ACCEPTANCE, AND EFFECTIVENESS OF AI IN INDUSTRIAL SAFETY PROGRAMS: ASSESSING TRUST, ETHICAL CONCERNS, AND IMPLEMENTATION CHALLENGES

Abstract

This study examined public perception, acceptance, and effectiveness of artificial intelligence (AI) 
in industrial safety programs, with emphasis on trust, ethical concerns, and implementation 
challenges. A descriptive survey design was used to collect data from 72 respondents across the 
Nigerian Ports Authority (NPA) and Chevron Nigeria Limited (CNL). Findings showed that 
respondents generally perceived AI as beneficial to industrial safety: 76.4% agreed that AI 
improves workplace safety and reduces accidents, while 79.2% supported wider adoption of AI
based safety measures. Acceptance was influenced mainly by management support and policy 
implementation (83.3%), cost of implementation (80.6%), worker resistance (77.8%), and trust in 
AI decision-making (73.6%). AI was rated highly effective for hazard detection (75.0%), 
emergency response (72.2%), and compliance with safety regulations (69.4%). However, concerns 
about lack of human oversight, job displacement, data privacy, surveillance, technical expertise, 
and regulatory constraints limited trust and adoption. The study concludes that AI can strengthen 
industrial safety compliance and accident prevention when supported by transparent governance, 
employee training, ethical safeguards, and cost-effective implementation strategies.