Peter A. Cotton, Debby R. E. Cotton
Artificial intelligence (AI) is increasingly shaping biological research, yet its adoption within biological education has been much slower, partly due to concerns surrounding generative AI (GAI) tools such as ChatGPT. Despite this, AI-driven applications including iNaturalist and Google Lens are being used to support teaching and learning in biology. This review examines the potential benefits of AI in biological education, including enhanced student engagement and subject knowledge, support for coding skills, assistive technologies for students with disabilities, and the use of predictive modelling to identify at-risk students. It also reviews emerging literature on the integration of specialised machine learning tools for bioimaging and species identification in biology teaching. Evidence suggests that tools such as iNaturalist can improve learning outcomes, promote engagement, and foster environmental stewardship. However, challenges associated with GAI are also discussed, including academic integrity, assessment design, misinformation, and the potential erosion of critical thinking and independent research skills. To maximise benefits while minimising risks, appropriate professional development for educators and clear guidance for students are essential. The review highlights the need for further rigorous research, particularly regarding impacts on critical thinking and the integration of AI into laboratory and field-based activities.