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Large language models (LLMs) are increasingly integrated into a variety of writing tasks.
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Automatic detection of generated text is easiest when humans are fooled
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JustCorrect: Intelligent Post Hoc Text Correction Techniques on Smartphones. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology (Virtual Event, USA) (UIST ’20) . Association for Computing Machinery, New York, NY, USA, 487–499
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All That’s ‘Human’ Is Not Gold: Evaluating Human Evaluation of Generated Text. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, Online, 7282–7296
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Exciting, useful, worrying, futuristic: Public perception of artificial intelligence in 8 countries. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society . 627–637
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Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry
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Is ChatGPT a “fire of prometheus” for non-native English-speaking researchers in academic writing?
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Human heuristics for AI-generated language are flawed
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AI Art and its Impact on Artists. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (Montréal, QC, Canada) (AIES ’23) . Association for Computing Machinery, New York, NY, USA, 363–374
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One AI does not fit all: A cluster analysis of the laypeople’s perception of AI roles. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems . 1–20
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Gender and Representation Bias in GPT-3 Generated Stories. In Proceedings of the Third Workshop on Narrative Understanding , Nader Akoury, Faeze Brahman, Snigdha Chaturvedi, Elizabeth Clark, Mohit Iyyer, and Lara J. Martin (Eds.). Association for Computational Linguistics, Virtual, 48–55
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A survey on bias and fairness in machine learning
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"I don’t think these devices are very culturally sensitive." - The impact of errors on African Americans in Automated Speech Recognition
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AI-mediated communication: Language use and interpersonal effects in a referential communication task
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StereoSet: Measuring stereotypical bias in pretrained language models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, Online, 5356–5371
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Thispersondoesnotexist - random AI generated photos of fake persons
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Online Dating Meets Artificial Intelligence: How the Perception of Algorithmically Generated Profile Text Impacts Attractiveness and Trust. In Proceedings of the 32nd Australian Conference on Human-Computer Interaction (Sydney, NSW, Australia) (OzCHI ’20) . Association for Computing Machinery, New York, NY, USA, 444–453
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An empirical study on how people perceive AI-generated music. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management . 304–314
Hyeshin Chu, Joohee Kim, Seongouk Kim, Hongkyu Lim, Hyunwook Lee, Seungmin Jin, Jongeun Lee, Taehwan Kim, and Sungahn Ko. 2022 · 2022
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Is GPT-3 Text Indistinguishable from Human Text? Scarecrow: A Framework for Scrutinizing Machine Text. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, Dublin, Ireland, 7250–7274
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Gender bias and stereotypes in Large Language Models. In Proceedings of The ACM Collective Intelligence Conference (Delft, Netherlands) (CI ’23) . Association for Computing Machinery, New York, NY, USA, 12–24
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GPT detectors are biased against non-native English writers
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" Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets
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Experimental evidence on the productivity effects of generative artificial intelligence
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Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond
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New report provides reality check about freelancers in the workforce
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Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society (Montréal, QC, Canada) (AIES ’23) . Association for Computing Machinery, New York, NY, USA, 723–741
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Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence
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ChatGPT in higher education: Considerations for academic integrity and student learning
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Asian Americans in STEM are not a monolith
Zer Vue, Chia Vang, Neng Vue, Vijayvardhan Kamalumpundi, Taylor Barongan, Bryanna Shao, Sunny Huang, Larry Vang, Mein Vue, Nancy Vang, Jianqiang Shao, CoohleenAnn Coombes, Prasanna Katti, Kaihua Liu, Kailee Yoshimura, Michelle Biete, Dao-Fu Dai, Mark A. Phillips, and Richard R. Behringer. 2023 · 2023
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Sociotechnical safety evaluation of generative ai systems
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Can Voice Assistants Be Microaggressors? Cross-Race Psychological Responses to Failures of Automatic Speech Recognition. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI ’23) . Association for Computing Machinery, New York, NY, USA, Article 109, 14 pages
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AI meets AI: Artificial Intelligence and Academic Integrity - A Survey on Mitigating AI-Assisted Cheating in Computing Education. In Proceedings of the 24th Annual Conference on Information Technology Education (Marietta, GA, USA) (SIGITE ’23) . Association for Computing Machinery, New York, NY, USA, 79–83
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AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
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Designing Interactive Explainable AI Tools for Algorithmic Literacy and Transparency. In Proceedings of the 2024 ACM Designing Interactive Systems Conference (Copenhagen, Denmark) (DIS ’24) . Association for Computing Machinery, New York, NY, USA, 939–957
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