The acceptance of genetically modified (GM) crops is still a controversial topic that presents major obstacles to their general use. Few studies, nevertheless, have emphasized the use of artificial intelligence (AI) in forecasting the dangers of GM crops. This review delves into the emerging field of applying AI to forecast the hazards linked to GM crops and examines how it could increase public acceptance of GM products. AI algorithms and predictive modeling approaches examine enormous datasets that include genetic, environmental, and agronomic factors. Utilizing AI, researchers may accelerate risk assessment procedures on the safety and effectiveness of GM crops.
In addressing public concerns and skepticism, AI-generated risk assessments foster transparency and confidence among consumers, regulators, and stakeholders, thereby … fostering greater acceptance of GM products. Although the lack of available data on genetic modifications or developing crop varieties, the amount of training and validation needed for AI algorithms before they can be trusted, the complexity of AI models, and ethical issues about AI, like data privacy and algorithm bias, may present difficulties for precise AI-driven risk assessment. This review outlines recent developments and future directions in utilizing AI as a promising strategy to enhance the acceptability of GM products.
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