Hybrid humor: Investigating AI's potential in cartoon caption writing

Abstract Crafting cartoon captions requires an understanding of humor, context, and the relationship between image and text. Traditionally, illustrators and writers collaborate to strengthen visual storytelling and comedic timing. With advances in natural language generation, large language models (LLMs) can assist in this process. This study examines AI's role in caption generation by testing GPT‐4o via the ChatGPT interface on IEEE Computer magazine cartoons. By removing captions and prompting AI to generate replacements, we assess its ability to produce jokes that match the depicted situation and narrative intent. Our findings show that while AI‐generated captions are often humorous and contextually relevant, they sometimes diverge from the cartoon's intended meaning, for example, by missing irony, cultural references, or contextual constraints. However, AI can also produce alternatives that broaden creative exploration and occasionally improve upon the original humor. We argue that current AI systems are best used as an assistant rather than a replacement for human creativity. By integrating AI‐generated suggestions, cartoonists can explore diverse humor styles, streamline ideation, and refine final captions while retaining creative control. This study highlights AI's potential as a practical tool for caption ideation within a hybrid human–AI workflow.

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Publication Details

Journal
AI Magazine
Published
2026-05-21
DOI
https://doi.org/10.1002/aaai.70064
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Hybrid humor: Investigating AI's potential in cartoon caption writing

Ergün Akleman, Sanem Sarıel, Metin Sezgin, Uğur Önal et al.
AI Magazine
Multimodal Machine Learning Applications
article

Hybrid humor: Investigating AI's potential in cartoon caption writing

Ergün Akleman, Sanem Sarıel, Metin Sezgin, Uğur Önal, Derya Akleman
article en

Abstract

Abstract Crafting cartoon captions requires an understanding of humor, context, and the relationship between image and text. Traditionally, illustrators and writers collaborate to strengthen visual storytelling and comedic timing. With advances in natural language generation, large language models (LLMs) can assist in this process. This study examines AI's role in caption generation by testing GPT‐4o via the ChatGPT interface on IEEE Computer magazine cartoons. By removing captions and prompting AI to generate replacements, we assess its ability to produce jokes that match the depicted situation and narrative intent. Our findings show that while AI‐generated captions are often humorous and contextually relevant, they sometimes diverge from the cartoon's intended meaning, for example, by missing irony, cultural references, or contextual constraints. However, AI can also produce alternatives that broaden creative exploration and occasionally improve upon the original humor. We argue that current AI systems are best used as an assistant rather than a replacement for human creativity. By integrating AI‐generated suggestions, cartoonists can explore diverse humor styles, streamline ideation, and refine final captions while retaining creative control. This study highlights AI's potential as a practical tool for caption ideation within a hybrid human–AI workflow.

AI MagazineVol. 47(2)
Koç University (TR), Istanbul Technical University (TR), Texas A&M University (US)
Quality Education
Openalex Percentile: Top 4%
Multimodal Machine Learning Applications
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Hybrid humor: Investigating AI's potential in cartoon caption writing — Ergün Akleman, Sanem Sarıel, et al. · AI Magazine (2026) | TGRS Research Map | TGRS