Social Dynamics of AI Support in Creative Writing | Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (2024)

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1. MarkS. Ackerman. 2000. The Intellectual Challenge of CSCW: The Gap Between Social Requirements and Technical Feasibility. Human–Computer Interaction 15, 2-3 (Sept. 2000), 179–203. https://doi.org/10.1207/S15327051HCI1523_5Google ScholarDigital Library
2. StephenH. Bach, Victor Sanh, Zheng-Xin Yong, Albert Webson, Colin Raffel, NihalV. Nayak, Abheesht Sharma, Taewoon Kim, M.Saiful Bari, Thibault Fevry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, JasonAlan Fries, MagedS. Al-shaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Xiangru Tang, Mike Tian-Jian Jiang, and AlexanderM. Rush. 2022. PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. arXiv:2202.01279 [cs] (Feb. 2022). http://arxiv.org/abs/2202.01279 arXiv:2202.01279.Google Scholar
3. Gagan Bansal, Besmira Nushi, Ece Kamar, WalterS. Lasecki, DanielS. Weld, and Eric Horvitz. 2019. Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 7 (Oct. 2019), 2–11. https://doi.org/10.1609/hcomp.v7i1.5285Google ScholarCross Ref
4. EmilyM. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. ACM, Virtual Event Canada, 610–623. https://doi.org/10.1145/3442188.3445922Google ScholarDigital Library
5. MargaretA Boden. 2009. Computer Models of Creativity. AI Magazine (2009), 12. https://doi.org/10.1609/aimag.v30i3.2254Google ScholarDigital Library
6. Kyle Booten and KatyIlonka Gero. 2021. Poetry Machines: Eliciting Designs for Interactive Writing Tools from Poets. In Creativity and Cognition. ACM, Virtual Event Italy, 1–5. https://doi.org/10.1145/3450741.3466813Google ScholarDigital Library
7. TomB. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, DanielM. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. arXiv:2005.14165 [cs] (July 2020). http://arxiv.org/abs/2005.14165 arXiv:2005.14165.Google Scholar
8. John JoonYoung Chung, Shiqing He, and Eytan Adar. 2022. Artist Support Networks: Implications for Future Creativity Support Tools. In Designing Interactive Systems Conference. ACM, Virtual Event Australia, 232–246. https://doi.org/10.1145/3532106.3533505Google ScholarDigital Library
9. John JoonYoung Chung, Wooseok Kim, KangMin Yoo, Hwaran Lee, Eytan Adar, and Minsuk Chang. 2022. TaleBrush: Sketching Stories with Generative Pretrained Language Models. (2022), 19.Google Scholar
10. Linda Flower and JohnR. Hayes. 1981. A Cognitive Process Theory of Writing. College Composition and Communication 32, 4 (Dec. 1981), 365. https://doi.org/10.2307/356600Google ScholarCross Ref
11. Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and NoahA. Smith. 2020. RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models. arXiv:2009.11462 [cs] (Sept. 2020). http://arxiv.org/abs/2009.11462 arXiv:2009.11462.Google Scholar
12. Katy Gero, Alex Calderwood, Charlotte Li, and Lydia Chilton. 2022. A Design Space for Writing Support Tools Using a Cognitive Process Model of Writing. In Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022). Association for Computational Linguistics, Dublin, Ireland, 11–24. https://doi.org/10.18653/v1/2022.in2writing-1.2Google ScholarCross Ref
13. KatyIlonka Gero, Zahra Ashktorab, Casey Dugan, Qian Pan, James Johnson, Werner Geyer, Maria Ruiz, Sarah Miller, DavidR. Millen, Murray Campbell, Sadhana Kumaravel, and Wei Zhang. 2020. Mental Models of AI Agents in a Cooperative Game Setting. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, Honolulu HI USA, 1–12. https://doi.org/10.1145/3313831.3376316Google ScholarDigital Library
14. KatyIlonka Gero and LydiaB. Chilton. 2019. How a Stylistic, Machine-Generated Thesaurus Impacts a Writer’s Process. In Proceedings of the 2019 on Creativity and Cognition. ACM, San Diego CA USA, 597–603. https://doi.org/10.1145/3325480.3326573Google ScholarDigital Library
15. KatyIlonka Gero and LydiaB. Chilton. 2019. Metaphoria: An Algorithmic Companion for Metaphor Creation. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, Glasgow Scotland Uk, 1–12. https://doi.org/10.1145/3290605.3300526Google ScholarDigital Library
16. KatyIlonka Gero, Vivian Liu, and Lydia Chilton. 2022. Sparks: Inspiration for Science Writing using Language Models. In Designing Interactive Systems Conference. ACM, Virtual Event Australia, 1002–1019. https://doi.org/10.1145/3532106.3533533Google ScholarDigital Library
17. JohnR. Hayes. 1996. A new framework for understanding cognition and affect in writing. In The Science of Writing: Theories, Methods, Individual Differences, and Applications. Lawrence Erbaum Associates.Google Scholar
18. JulieS. Hui, Darren Gergle, and ElizabethM. Gerber. 2018. IntroAssist: A Tool to Support Writing Introductory Help Requests. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. ACM, Montreal QC Canada, 1–13. https://doi.org/10.1145/3173574.3173596Google ScholarDigital Library
19. Zhengbao Jiang, FrankF. Xu, Jun Araki, and Graham Neubig. 2020. How Can We Know What Language Models Know?Transactions of the Association for Computational Linguistics 8 (07 2020), 423–438. https://doi.org/10.1162/tacl_a_00324 arXiv:https://direct.mit.edu/tacl/article-pdf/doi/10.1162/tacl_a_00324/1923867/tacl_a_00324.pdfGoogle ScholarCross Ref
20. R.T. Kellogg. 2008. Training writing skills: A cognitive developmental perspective. Journal of Writing Research 1, 1 (June 2008), 1–26. https://doi.org/10.17239/jowr-2008.01.01.1Google ScholarCross Ref
21. Pranav Khadpe, Ranjay Krishna, Li Fei-Fei, Jeffrey Hanco*ck, and Michael Bernstein. 2020. Conceptual Metaphors Impact Perceptions of Human-AI Collaboration. Proceedings of the ACM on Human-Computer Interaction 4, CSCW2 (Oct. 2020), 1–26. https://doi.org/10.1145/3415234 arXiv:2008.02311 [cs].Google ScholarDigital Library
22. Mina Lee, Percy Liang, and Qian Yang. 2022. CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities. In CHI Conference on Human Factors in Computing Systems. ACM, New Orleans LA USA, 1–19. https://doi.org/10.1145/3491102.3502030Google ScholarDigital Library
23. Ming Liu, RafaelA Calvo, and Vasile Rus. 2020. Automatic Generation and Ranking of Questions for Critical Review. (2020), 15.Google Scholar
24. Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing. arXiv:2107.13586 [cs] (July 2021). http://arxiv.org/abs/2107.13586 arXiv:2107.13586.Google Scholar
25. MaryLou Maher. 2012. Computational and Collective Creativity: Who’s Being Creative?(2012), 5.Google Scholar
26. Raphaël Millière. 2022. AI Art Is Challenging the Boundaries of Curation. Wired (July 2022). https://www.wired.com/story/dalle-art-curation-artificial-intelligence/Google Scholar
27. Meghan O’Gieblyn. 2021. Babel: Could a machine have an unconscious? (July 2021). https://www.nplusonemag.com/issue-40/essays/babel-4/Google Scholar
28. MichaelQuinn Patton. 2002. Qualitative Research and Evaluation Methods (Chapter 5) (3 ed.). Sage Publications.Google Scholar
29. Zhenhui Peng, Qingyu Guo, KaWing Tsang, and Xiaojuan Ma. 2020. Exploring the Effects of Technological Writing Assistance for Support Providers in Online Mental Health Community. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, Honolulu HI USA, 1–15. https://doi.org/10.1145/3313831.3376695Google ScholarDigital Library
30. Ethan Perez, Saffron Huang, Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, and Geoffrey Irving. 2022. Red Teaming Language Models with Language Models. arXiv preprint arXiv:2202.03286(2022), 31.Google Scholar
31. JamesL. Peterson. 1980. Computer programs for detecting and correcting spelling errors. Commun. ACM 23, 12 (Dec. 1980), 676–687. https://doi.org/10.1145/359038.359041Google ScholarDigital Library
32. Philip Quinn and Shumin Zhai. 2016. A Cost-Benefit Study of Text Entry Suggestion Interaction. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). Association for Computing Machinery, New York, NY, USA, 83–88. https://doi.org/10.1145/2858036.2858305Google ScholarDigital Library
33. JackW. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George vanden Driessche, LisaAnne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, XiangLorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien deMasson d’Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego deLas Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew Johnson, Blake Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Ed Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, and Geoffrey Irving. 2022. Scaling Language Models: Methods, Analysis & Insights from Training Gopher. http://arxiv.org/abs/2112.11446 arXiv:2112.11446 [cs].Google Scholar
34. Nikhil Singh, Guillermo Bernal, Daria Savchenko, and ElenaL. Glassman. 2022. Where to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence. ACM Transactions on Computer-Human Interaction (Feb. 2022), 3511599. https://doi.org/10.1145/3511599Google ScholarDigital Library
35. Robin Sloan. 2016. Writing with the machine. (May 2016). https://www.robinsloan.com/notes/writing-with-the-machine/Google Scholar
36. RichardJean So and Andrew Piper. 2016. How Has the MFA Changed the Contemporary Novel?The Atlantic (March 2016). https://www.theatlantic.com/entertainment/archive/2016/03/mfa-creative-writing/462483/Google Scholar
37. RichardJean So and Gus Wezerek. 2020. Just How White Is the Book Industry?The New York Times (Dec. 2020). https://www.nytimes.com/interactive/2020/12/11/opinion/culture/diversity-publishing-industry.htmlGoogle Scholar
38. DavidR. Thomas. 2006. A General Inductive Approach for Analyzing Qualitative Evaluation Data. American Journal of Evaluation 27, 2 (June 2006), 237–246. https://doi.org/10.1177/1098214005283748Google ScholarCross Ref
39. Qiaosi Wang, Koustuv Saha, Eric Gregori, David Joyner, and Ashok Goel. 2021. Towards Mutual Theory of Mind in Human-AI Interaction: How Language Reflects What Students Perceive About a Virtual Teaching Assistant. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI ’21). Association for Computing Machinery, New York, NY, USA, Article 384, 14pages. https://doi.org/10.1145/3411764.3445645Google ScholarDigital Library
40. Tongshuang Wu, Michael Terry, and CarrieJ. Cai. 2021. AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts. arXiv:2110.01691 [cs] (Oct. 2021). http://arxiv.org/abs/2110.01691 arXiv:2110.01691.Google Scholar
41. Feiyu Xu, Hans Uszkoreit, Yangzhou Du, Wei Fan, Dongyan Zhao, and Jun Zhu. 2019. Explainable AI: A Brief Survey on History, Research Areas, Approaches and Challenges. In Natural Language Processing and Chinese Computing, Jie Tang, Min-Yen Kan, Dongyan Zhao, Sujian Li, and Hongying Zan (Eds.). Springer International Publishing, Cham, 563–574.Google Scholar
42. Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, XiVictoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, PunitSingh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer. 2022. OPT: Open Pre-trained Transformer Language Models. http://arxiv.org/abs/2205.01068 arXiv:2205.01068 [cs].Google Scholar

Index Terms

1. Social Dynamics of AI Support in Creative Writing

   1. Computing methodologies

      1. Artificial intelligence

         1. Natural language processing

   2. Human-centered computing

      1. Human computer interaction (HCI)

         1. Empirical studies in HCI

         2. HCI theory, concepts and models

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