ArticleArchives of sexual behavior2025
Anti-AI Bias Toward Couple Images and Couple Counseling: Findings from Two Experiments.
Article in Archives of sexual behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Generative artificial intelligence (AI) systems can produce text, images, videos, and audio in response to prompts. They are increasingly applied across various domains, including intimacy and sexuality-ranging from AI-generated pornography to sexual counseling via AI chatbots. While AI-generated content holds significant potential, it is also met with skepticism. Anti-AI bias is defined as a systematic tendency to evaluate AI-produced outputs more negatively than equivalent human-created content, regardless of actual quality. Following the experimental labeling paradigm, this study examined whether identical couple images (H
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.