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The Study

AI-Generated “Slop” in Online Biomedical Science Educational Videos: Mixed Methods Study of Prevalence, Characteristics, and Hazards to Learners and Teachers

In simple terms

This study didn't test if AI videos make people learn worse—it just watched a bunch of videos and wrote down what looked weird or wrong. So we know what slop looks like, but we don't know if it actually hurts learning.

34%

Analysis score

34/ 44

Maximum 44 for a cross-sectional study.

Where the score came from

Reporting0
Methodology25
Publication100
Statistical23
Study type (basis of the score)
Cross-Sectional Study
Level 4 - Case series
What’s the bottom line?

AI can make videos that sound like science lessons but are full of mistakes, weird analogies, and boring robot voices — and people watch them just as much as real teacher videos.

Where does this study sit?

Reviews of RCTs (Meta-analyses)

Max 100

Randomized Trials

Max 90

Reviews of Cohort Studies

Max 85

Cohort Studies

Max 72

Reviews of Case-Control Studies

Max 63

Case-Control Studies

Max 58

Cross-Sectional & Case Series

Max 50

Expert Opinion

Max 5
StrongerWeaker
Cross-Sectional & Case Series
Level 4
34

34 / 100

Quality score

Snapshots of a population at a single point in time, or descriptions of small groups. Can identify correlations and prevalence, but cannot determine cause and effect.

Cannot establish causation

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Key takeaways

Summary

Based on the study abstract and findings.

  1. 1Even though these AI videos are full of errors and confusing explanations, they're just as popular as real educational videos — meaning learners might be learning wrong things without knowing it.
  2. 2About 5 out of every 100 science videos on YouTube and TikTok were made by AI with little human care.
  3. 3These videos had the same number of views and likes as good videos.

Score breakdown, methodology, conflicts of interest, evidence analysis & raw study data

Publication

Journal

JMIR Medical Education

Year

2025

Authors

Eric M. Jones, Jane D Newman, Boyun Kim, E. Fogle

Open Access
6 citations
Analysis v5

Related Content

Claims (7)

Assertion

Speech generated by artificial intelligence often sounds unnatural because it leaves out words that connect ideas and creates abrupt shifts between sentences.

Descriptive
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Assertion

AI-generated biomedical videos labeled as 'slop' use inaccurate comparisons, such as likening cellular receptors to beehive gates or metabolic processes to orchestras, which distort the actual structure of biological systems and cause learners to form incorrect understandings.

Mechanistic
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Assertion

AI-generated biomedical videos labeled as 'slop' include inaccurate simplifications, such as describing quaternary protein structure as interactions between multiple protein molecules and treating urea cycle disorder as one uniform disease.

Descriptive
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Assertion

AI-generated biomedical videos labeled as 'slop' use too many emotionally charged words like 'amazing' and 'crucial,' which distracts viewers and causes them to misunderstand what information is most important.

Descriptive
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Assertion

A study found that 5.3% of biomedical science videos on YouTube and TikTok contain low-quality content generated by AI with little human oversight, featuring errors such as false facts, confusing analogies, mismatched audio and video, and disorganized structure.

Descriptive
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Assertion

Videos about biomedical topics created by AI and labeled as low-quality receive the same number of daily views, likes, and comments on YouTube and TikTok as videos labeled as high-quality.

Correlational
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