Generative artificial intelligence and creativity in photography education: innovations for artistic and critical development

Abstract

This article presents a teaching innovation that integrates the use of generative artificial intelligence (GenAI) and its implications in courses of the Bachelor’s Degree in Photography and Audiovisual Creation at the TAI University School of Arts (an affiliated center of the Rey Juan Carlos University). We propose an action‑research design structured in three phases—technological exploration and image generation (DALL·E 3, Midjourney, Runway ML Gen‑4), critical editing and post‑production (Adobe Photoshop, Lightroom, DaVinci Resolve, After Effects), and ethical‑ecological reflection with a final individual report (Prezi). Data were collected through students’ reflective journals, classroom forums, and end‑of‑module critical memos. Results, organized thematically, indicate: (a) increased visual production (15–40 images per student) and enhanced ideation; (b) development of algorithmic bias awareness—almost 100% of participants explicitly addressed bias and proposed inclusive strategies; (c) greater attention to the environmental footprint of generative artificial intelligence; and (d) a shift in the teacher’s role toward critical mediation. We discuss implications for curriculum design in arts education, limitations related to measurement instruments, and future lines for evaluation using validated scales.