Artificial Intelligence Technology Application and Occupational Safety in Downstream Petroleum Industries in Greater Accra

Abstract

The downstream petroleum industry in Ghana is one among many sectors characterised by the convergence of numerous hazardous exposures that can potentially cause serious catastrophe and work-related accidents. Several studies have been conducted separately on the applications of artificial intelligence technology, occupational safety, the effects of artificial intelligence on safety, and technology and occupational safety. The general objective of the study was to analyse artificial intelligence technology application and occupational safety to improve occupational safety in downstream petroleum industry. The study applied the quantitative research approach. The study relied on primary interval data obtained through questionnaire administration. The data were processed with tools from STATA 15. Data were analysed using descriptive, correlation and synthesis frameworks and descriptive statistics, regression techniques. The results of the study showed that predictive analytics of the environment was found to be the most common area of AI technology application in the downstream petroleum industry, followed by cyber security and compliance with safety rules. Technology attitudes, trust, social norms, and technology adoption culture were observed to be significant determinants of AI acceptance in the downstream petroleum sector. The primary effect of AI technology application in the downstream petroleum sector appears to be precision in decision. A novel framework for model AI technology application for improved occupational safety comprising of the following system characteristics: inputs, AI-based models, occupational safety modes, and efficiency indices. The study findings have implications for how occupational health and safety within the downstream petroleum sector is addressed