Identification and Appraisal of AI-Generated vs. Human-Created Artworks (2024 Survey Dataset)

This dataset supports the doctoral dissertation The AI of the Beholder: A Quantitative Study on Human Perception and Appraisal of AI-Generated Images by Joshua Cunningham (Robert Morris University, 2025). The study investigates how individuals perceive and appraise artwork generated by artificial intelligence (AI) in comparison to human-created pieces. Specifically, it examines: (1) whether participants can accurately distinguish AI-generated from human-created artwork, (2) how age and exposure to AI art influence this ability and related appraisals, and (3) how digital versus traditional visual styles of AI art are perceived.
The dataset includes anonymized survey responses collected from a diverse group of adult participants. Respondents were asked to evaluate a series of visual artworks—some created by humans, others by AI—across a range of styles, including both digital and traditional aesthetics. Additional demographic information such as age and prior exposure to AI tools was collected to assess moderating effects. The data were analyzed using SPSS to evaluate participant accuracy, preferences, and perceptions.
This dataset can support further research into the psychological, aesthetic, and cultural dynamics of AI-generated content, as well as human-machine interaction in the creative arts.