What Does AI Do for Cultural Interpretation? A Randomized Experiment on Close Reading Poems with Exposure to AI Interpretation
Jiayin Zhi, Hoyt Long, Richard Jean So, Mina Lee
摘要
AI demonstrates unprecedented reasoning capabilities, but its increasing integration into human reasoning via automated reading and summarization has provoked debate about its use for cultural interpretation. Close reading-the practice of understanding, analyzing, and critiquing cultural texts for pleasure-is a skill at the core of such interpretation, traditionally being seen as exclusive to humans. To test AI's impact on close reading, both in terms of interpretative performance and pleasure, we conducted a preregistered randomized experiment (𝑛 = 400) investigating the impact of AI assistance by presenting single or multiple AI interpretations, on close reading poems, compared to no AI assistance. We found that single AI interpretation boosted both performance and pleasure, while multiple AI interpretations only improved performance. Further exploration revealed a trade-off: participants who heavily relied on AI showed better performance on the task but lower pleasure. Our results contribute to discussion on whether and how to calibrate AI assistance for cultural interpretation: "less is more. "
• Human-centered computing → Empirical studies in HCI; • Applied computing → Arts and humanities.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper7
- The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge WorkersHao-Ping (Hank) Lee, Advait Sarkar, Lev Tankelevitch, Ian Drosos 等CHI 2025 · 被引用 690 次
- Does Writing with Language Models Reduce Content Diversity?Vishakh Padmakumar, He HeICLR 2024 · 被引用 173 次
- IMPLI: Investigating NLI Models' Performance on Figurative LanguageKevin Stowe, Prasetya Ajie Utama, Iryna GurevychACL 2022 · 被引用 52 次
- Inform the Uninformed: Improving Online Informed Consent Reading with an AI-Powered ChatbotZiang Xiao, Tiffany Wenting Li, Karrie Karahalios, Hari SundaramCHI 2023 · 被引用 48 次
- Timing Matters: How Using LLMs at Different Timings Influences Writers' Perceptions and Ideation Outcomes in AI-Assisted IdeationPeinuan Qin, Chi-Lan Yang, Jingshu Li, Jing Wen 等CHI 2025 · 被引用 19 次
相关 Paper
- KRISTEVA: Close Reading as a Novel Task for Benchmarking Interpretive ReasoningPeiqi Sui, Juan Diego Rodriguez, Philippe Laban, Dean Murphy 等ACL 2025 · 被引用 6 次
- Impact of Model Interpretability and Outcome Feedback on Trust in AIDaehwan Ahn, Abdullah Almaatouq, Monisha Gulabani, Kartik HosanagarCHI 2024 · 被引用 33 次
- Soliloquy: Fostering Poetry Comprehension Using an Interactive Think-aloud VisualizationZak Risha, Deniz Sonmez Unal, Erin WalkerCHI 2023 · 被引用 2 次
- Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team PerformanceGagan Bansal, Tongshuang Wu, Joyce Zhou, Raymond Fok 等CHI 2021 · 被引用 713 次
- Understanding and Supporting Peer Review Using AI-reframed Positive SummaryChi-Lan Yang, Alarith Uhde, Naomi Yamashita, Hideaki KuzuokaCHI 2025 · 被引用 8 次
