ArticleNature communications2026
Perceived humanness and empathy are dissociated in relationship advice generated by a large language model.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Differentiating generated and human-written content is increasingly difficult. We examine how incentives to convey humanness and task characteristics shape perceptions of textual content across five studies. In Studies 1-2, humans and GPT-4 write relationship advice or relationship descriptions with or without instructions to appear human. New participants judge each text's source. Instructions to appear human increase perceived humanness only for GPT-4, reducing the human advantage. Study 3 shows that these effects persist under instructions to avoid sounding like an AI model and replicate across GPT-4 and GPT-4o. Study 4 demonstrates that GPT models can produce empathy without humanness and humanness without empathy. Study 5 shows that GPT-4 increases perceived humanness by adopting informal, conversational language and other surface-level stylistic cues, whereas human writers show little adjustment. Together, the findings indicate that perceived humanness depends on incentives to appear human and the context in which writing is produced.
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