The food supply chains are also getting interlaced, and the number of ready-to-eat foods is
growing as well, which complicates the process of food safety assurance, as regards mycotoxin
contamination. The carcinogenic, immunotoxic, and neurotoxic effects of mycotoxins are a
serious concern to the population, and there is therefore a need to identify them early enough
and deal with the risk successfully. AI has been seen to become a transformative ingredient in
food safety systems with an ability to detect quickly, monitor in real time, and predict the
potential risks at the production phase, storage phase, and distribution phase. It is endeavoured
to highlight the application of AI-based mycotoxin detection in ready-to-eat food items and its
ethical parameters, and its adoption. Besides technical performance, the chapter emphasizes
the fact that the AI system is not value-neutral and it should be limited by strong ethical
principles. The primary ethical principles of beneficence, non- maleficence, fairness,
transparency, accountability, and human autonomy are touched upon in relation to AIsupported decision making, such as batch rejection, recalls, and regulatory reporting. Particular
attention is given to the problems of the algorithmic bias, quality of data, limitation of
sampling, and the threat of automation. The importance and validity of explicable AI
governance with human interface, clear and transparent dealings are emphasised for the
maintenance of regulatory compliance and trust.