JMIR Publications

ABSTRACT

Background:

Video-sharing sites such as YouTube and TikTok have become indispensable resources for learners and educators. The recent growth in generative artificial intelligence (genAI) tools, however, has resulted in low-quality, AI-generated material (commonly called “slop”) cluttering these platforms and competing with authoritative educational materials. The extent to which slop has polluted science education video content is unknown, as are the specific hazards to learning from purportedly educational videos made by unsupervised artificial intelligence (AI).

Objective:

Our objectives are to advance a formal definition of slop (based on the recent theoretical construct of “careless speech”), to identify its qualitative characteristics that may be problematic for biomedical science learners, and to gauge its prevalence among basic sciences videos on YouTube and TikTok.

Methods:

An automated search of publicly-available YouTube and TikTok videos related to ten search terms was conducted in February and March, 2025. After exclusion of duplicate, off-topic, and non-English results, videos were screened and those suggestive of AI were flagged. The flagged videos were subject to a qualitative analysis to identify and code problematic features before an assignment of “slop” was made. Quantitative viewership data on all videos in the study were scraped using automated tools (Apify and SerpAPI).

Results:

We define “slop” according to the degree of human care in production. Of 1,082 videos screened (814 YouTube, 268 TikTok), 57 (5.3%) were deemed probably AI-generated and low-quality. From qualitative analysis of these and six additional AI-generated videos, we identified 16 codes for problematic aspects of the videos as related to their format or contents. These codes were then mapped to the seven characteristics of careless speech identified earlier. Analysis of view, like, and comment rates revealed no significant difference between slop videos and the overall population.

Conclusions:

We find slop to be not especially prevalent on YouTube and TikTok at this time. From slop videos that were identified, several features inconsistent with best practices in multimedia instruction were defined. Our findings should inform learners seeking to avoid low-quality material on video-sharing sites, and suggest pitfalls for instructors to avoid when making high-quality educational materials with generative AI.