Bad AI-generated images can be good for teaching visual literacy in biology

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Authors: Crystal Uminski
Cited by: 1
References: 56

Abstract

Artificial intelligence (AI) has rapidly improved in its ability to produce polished and realistic visual representations of biological structures and processes, yet most AI-generated images still contain factual inaccuracies, inconsistencies, or errors. These types of errors that often make AI images "bad" representations of biology can make AI images powerful pedagogical tools for teaching visual literacy. As biology education relies on diagrams to model structures, processes, and systems that cannot be directly observed, students need to develop skills interpreting, evaluating, and critiquing the visual representations of the unobservable phenomena they encounter in their biology courses. The error-prone and uncanny qualities of AI-generated images can provide rich opportunities for active learning in which students identify inaccuracies, articulate why AI images are incorrect, and refine their understanding of the visual conventions in biology diagrams. The flaws and inaccuracies that make AI-generated biology diagrams "bad" can make them quite good for fostering critical thinking and deep conceptual understanding in biology learners. This perspective outlines practical strategies for incorporating AI images into active learning and assessments in biology courses and offers guidance for generating AI images to use as teaching tools.

Fields of Study & Subjects

Genetics Bioinformatics and Biomedical Research Science Education and Pedagogy Visual and Cognitive Learning Processes

Publication details

Journal / source
Journal of Microbiology and Biology Education
Publisher
American Society for Microbiology
Volume
27
Issue
2
Pages
e0032125–e0032125
Publication date
29 April 2026
Language
EN