Evaluating Textual And Visual Artificial Intelligence Responses For Sanitization Scheduling

Sanitization process planning is a crucial activity in the food industry for consumer health and safety reasons. However, Artificial Intelligence (AI) can improve the performance of these processes, although there are many uncertainties associated with black-box systems. To overcome these limitations, this study evaluated different AI response formats for decision-making through a simulation conducted with 120 industrial engineering students, comparing four different scenarios: no AI, black-box, a more detailed textual AI response, and a graphical AI response. For each scenario, performance times, cognitive load, and trust in the response were recorded, according to the ABI model. The results show superior performance among students with a graphical AI response, reducing decision- making time compared to the other scenarios. These findings highlight the importance of adapting the AI response format to the nature of operations to reduce mental effort and safely integrate AI into high-risk industrial environments.