Yang Cheng-Xian, Baker Lauri, Irani Tracy, Telg Ricky, Bunch James, Watson Jonathan
Center for Public Issues Education in Agriculture and Natural Resources, University of Florida, 1408 Sabal Palm Drive, Gainesville, FL, 32611, USA.
Department of Agricultural Education and Communication, University of Florida, 307A Rolfs Hall, Gainesville, FL, 32611, USA.
Curr Res Food Sci. 2025 Jun 17;11:101119. doi: 10.1016/j.crfs.2025.101119. eCollection 2025.
This study investigated consumer attitudes and intentions toward adopting artificial intelligence (AI) in food traceability systems, an emerging technology aimed at enhancing food safety and transparency. Data collected from an online survey of 1013 United States consumers, the study applies structural equation modeling (SEM) to examine the factors influencing consumer acceptance. Results showed that attitudes and perceived behavioral control are positively associated with decisions to accept AI-assisted food traceability, with trust in science, food safety concerns, fear of food technology, and risk information-seeking behavior also important factors. The model explained 80.2 % of the variance in intention and 18.0 % in attitude. Perceived behavioral control had a stronger impact on intention than attitude, suggesting that consumers who feel they have control over their food choices are more likely to support AI-enhanced traceability. Additionally, trust in scientific institutions emerged as a key predictor of acceptance, underscoring the importance of transparent and science-backed communication strategies. The study also highlights how concerns about foodborne illnesses and proactive risk information-seeking behaviors are positively associated with attitudes toward AI-assisted traceability. In contrast, food technology neophobia is negatively associated with acceptance, indicating the need for targeted educational campaigns to reduce skepticism. These findings provide valuable insights for policymakers, food industry stakeholders, and science communicators in designing effective strategies to enhance consumer confidence in AI-driven food safety initiatives. By addressing consumer concerns and fostering trust, AI-assisted traceability can be more successfully integrated into food systems, ultimately reducing foodborne illness risks and improving public health.
本研究调查了消费者对在食品可追溯系统中采用人工智能（AI）的态度和意愿，该新兴技术旨在提高食品安全和透明度。通过对1013名美国消费者进行在线调查收集数据，本研究应用结构方程模型（SEM）来检验影响消费者接受度的因素。结果表明，态度和感知行为控制与接受人工智能辅助食品可追溯性的决定呈正相关，对科学的信任、食品安全担忧、对食品技术的恐惧以及风险信息寻求行为也是重要因素。该模型解释了意愿方差的80.2%和态度方差的18.0%。感知行为控制对意愿的影响比对态度的影响更强，这表明认为自己能够控制食品选择的消费者更有可能支持人工智能增强的可追溯性。此外，对科学机构的信任成为接受度的关键预测因素，凸显了透明且有科学依据的沟通策略的重要性。该研究还强调了对食源性疾病的担忧和积极的风险信息寻求行为与对人工智能辅助可追溯性的态度呈正相关。相比之下，食品技术新恐惧症与接受度呈负相关，这表明需要开展有针对性的教育活动以减少怀疑态度。这些发现为政策制定者、食品行业利益相关者和科学传播者设计有效策略以增强消费者对人工智能驱动的食品安全举措的信心提供了宝贵见解。通过解决消费者的担忧并建立信任，人工智能辅助可追溯性可以更成功地融入食品系统，最终降低食源性疾病风险并改善公众健康。
