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Generative AI in the Wild: Prospects, Challenges, and Strategies (2404.04101v1)

Published 3 Apr 2024 in cs.HC

Abstract: Propelled by their remarkable capabilities to generate novel and engaging content, Generative Artificial Intelligence (GenAI) technologies are disrupting traditional workflows in many industries. While prior research has examined GenAI from a techno-centric perspective, there is still a lack of understanding about how users perceive and utilize GenAI in real-world scenarios. To bridge this gap, we conducted semi-structured interviews with (N=18) GenAI users in creative industries, investigating the human-GenAI co-creation process within a holistic LUA (Learning, Using and Assessing) framework. Our study uncovered an intriguingly complex landscape: Prospects-GenAI greatly fosters the co-creation between human expertise and GenAI capabilities, profoundly transforming creative workflows; Challenges-Meanwhile, users face substantial uncertainties and complexities arising from resource availability, tool usability, and regulatory compliance; Strategies-In response, users actively devise various strategies to overcome many of such challenges. Our study reveals key implications for the design of future GenAI tools.

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References (83)
  1. AIContentfy. 2023. The ethics of ChatGPT: Navigating the gray area. https://aicontentfy.com/en/blog/ethics-of-chatgpt-navigating-gray-area
  2. Hussam Alkaissi and Samy I McFarlane. 2023. Artificial hallucinations in ChatGPT: Implications in scientific writing. Cureus 15, 2 (2023).
  3. Robert B Allen. 1997. Mental models and user models. In Handbook of Human-Computer Interaction. Elsevier, 49–63.
  4. Nantheera Anantrasirichai and David Bull. 2022. Artificial intelligence in the creative industries: a review. Artificial intelligence review (2022), 1–68.
  5. Developing a research agenda for human-centered data science. In Proceedings of the ACM Conference on Computer Supported Cooperative Work and Social Computing.
  6. On the importance and implications of studying technology non-use. interactions 22, 2 (2015), 52–56.
  7. Prompting is programming: A query language for large language models. In Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation.
  8. Susanne Bodker. 1989. A human activity approach to user interfaces. Human-Computer Interaction 4, 3 (1989), 171–195.
  9. Aras Bozkurt and Ramesh C Sharma. 2023. Challenging the status quo and exploring the new boundaries in the age of algorithms: Reimagining the role of generative AI in distance education and online learning. Asian Journal of Distance Education 18, 1 (2023).
  10. Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative Research in Psychology 3, 2 (2006), 77–101.
  11. Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health 11, 4 (2019), 589–597.
  12. Language models are few-shot learners. In Proceedings of the Advances in Neural Information Processing Systems.
  13. Generative AI at work. National Bureau of Economic Research (2023).
  14. Jacques Bughin and Nicolas Van Zeebroeck. 2018. Artificial intelligence: Why a digital base is critical. The McKinsey Quarterly (2018).
  15. John M Carroll and Judith Reitman Olson. 1988. Mental models in human-computer interaction. Handbook of Human-Computer Interaction (1988), 45–65.
  16. Research in the wild: Understanding ‘in the wild’ approaches to design and development. In Proceedings of the Designing Interactive Systems Conference.
  17. Exploring the design space of user-system communication for smart-home routine assistants. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–14.
  18. Ways of qualitative coding: A case study of four strategies for resolving disagreements. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems.
  19. Simple and controllable music generation. ArXiv e-prints (2023).
  20. Anamaria Crisan and Brittany Fiore-Gartland. 2021. Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  21. Choice over control: How users write with large language models using diegetic and non-diegetic prompting. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  22. “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management 71 (2023), 102642.
  23. How Generative AI Can Augment Human Creativity. Harvard Business Review (July 2023). https://hbr.org/2023/07/how-generative-ai-can-augment-human-creativity
  24. Editorial. 2023. Generating ‘smarter’ biotechnology. Nature Biotechnology 41, 2 (2023), 157–157.
  25. Art and the science of generative AI. Science 380, 6650 (2023), 1110–1111.
  26. Ziv Epstein, Aaron Hertzmann, the Investigators of Human Creativity, Memo Akten, Hany Farid, Jessica Fjeld, Morgan R. Frank, Matthew Groh, Laura Herman, Neil Leach, Robert Mahari, Alex “Sandy” Pentland, Olga Russakovsky, Hope Schroeder, and Amy Smith. 2023b. Art and the science of generative AI. Science 380, 6650 (2023), 1110–1111.
  27. Jo Foord. 2009. Strategies for creative industries: An international review. Creative Industries Journal 1, 2 (2009), 91–113.
  28. Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences 116, 14 (2019), 6531–6539.
  29. Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration. Journal of Information Technology Case and Application Research 25, 3 (2023), 277–304.
  30. Predictability and surprise in large generative models. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency.
  31. Social dynamics of AI support in creative writing. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  32. Barney G Glaser and Anselm L Strauss. 2017. The discovery of grounded theory: Strategies for qualitative research. Routledge.
  33. Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management 49 (2019), 157–169.
  34. Regulating ChatGPT and other large generative AI models. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. 1112–1123.
  35. The three paradigms of HCI. In Alt. Chi. Session at the SIGCHI Conference on human factors in computing systems San Jose, California, USA. 1–18.
  36. Generative adversarial networks–enabled human–artificial intelligence collaborative applications for creative and design industries: A systematic review of current approaches and trends. Frontiers in artificial intelligence 4 (2021), 604234.
  37. Design for intuitive use-testing image schema theory for user interface design. In Proceedings of the International Conference on Engineering Design.
  38. Sana Ijaz. 2023. 15 countries that banned CHATGPT. https://finance.yahoo.com/news/15-countries-banned-chatgpt-204342617.html
  39. Anna K Jordanous. 2009. Evaluating machine creativity. In Proceedings of the seventh ACM conference on creativity and cognition. 331–332.
  40. Celeste Kidd and Abeba Birhane. 2023. How AI can distort human beliefs. Science 380, 6651 (2023), 1222–1223.
  41. Will you accept an imperfect AI? Exploring designs for adjusting end-user expectations of ai systems. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  42. Kari Kuutti and Liam J Bannon. 2014. The turn to practice in HCI: Towards a research agenda. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  43. Generating scholarly content with ChatGPT: Ethical challenges for medical publishing. The Lancet Digital Health 5, 3 (2023), e105–e106.
  44. The experience of agency in human-computer interactions: a review. Frontiers in Human Neuroscience 8 (2014), 643.
  45. Xiaoyue Ma and Yudi Huo. 2023. Are users willing to embrace ChatGPT? Exploring the factors on the acceptance of chatbots from the perspective of AIDUA framework. Technology in Society 75 (2023), 102362.
  46. Reliability and inter-rater reliability in qualitative research: Norms and guidelines for CSCW and HCI practice. Proc. ACM Hum.-Comput. Interact. 3, CSCW (2019), 1–23.
  47. GenAICHI 2023: Generative AI and HCI at CHI 2023. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems.
  48. Jonas Oppenlaender. 2022. The creativity of text-to-image generation. In Proceedings of the 25th International Academic Mindtrek Conference. ACM.
  49. Customer acceptance of AI in service encounters: understanding antecedents and consequences. Handbook of Service Science, Volume II (2019), 77–103.
  50. Training language models to follow instructions with human feedback. In Proceedings of the Advances in Neural Information Processing Systems.
  51. Samir Passi and Steven J Jackson. 2018. Trust in data science: Collaboration, translation, and accountability in corporate data science projects. Proc. ACM Hum.-Comput. Interact. 2, CSCW (2018), 1–28.
  52. Michael Quinn Patton. 1990. Qualitative Evaluation and Research Methods. SAGE.
  53. Creativity in the age of generative AI. Nature Human Behaviour (2023), 1–3.
  54. Jeba Rezwana and Mary Lou Maher. 2023. User perspectives on ethical challenges in Human-AI co-creativity: A design fiction study. In Proceedings of the ACM Conference on Creativity and Cognition.
  55. Oliver C Robinson. 2014. Sampling in interview-based qualitative research: A theoretical and practical guide. Qualitative Research in Psychology 11, 1 (2014), 25–41.
  56. Yvonne Rogers. 2011. Interaction design gone wild: Striving for wild theory. Interactions 18, 4 (2011), 58–62.
  57. Research in the Wild. Springer.
  58. John Rooksby. 2013. Wild in the laboratory: A discussion of plans and situated actions. ACM Transactions on Computer-Human Interaction 20, 3 (2013), 1–17.
  59. Anne L Russell. 1995. Stages in learning new technology: Naive adult email users. Computers & Education 25, 4 (1995), 173–178.
  60. Daniel Russo. 2023. Navigating the Complexity of Generative AI Adoption in Software Engineering. ArXiv e-prints (2023).
  61. Tam Sakirin and Rachid Ben Said. 2023. User preferences for ChatGPT-powered conversational interfaces versus traditional methods. Mesopotamian Journal of Computer Science 2023 (2023), 24–31.
  62. Samy. 2023. Why are companies and other organizations banning CHATGPT (and Bard next?). https://medium.com/@samyme/why-are-companies-and-other-organizations-banning-chatgpt-and-bard-next-7770ab8c171b
  63. Christine Satchell and Paul Dourish. 2009. Beyond the user: Use and non-use in HCI. In Proceedings of the Annual Conference of the Australian Computer-Human Interaction Special Interest Group: Design.
  64. Keng Siau and Weiyu Wang. 2020. Artificial intelligence (AI) ethics: Ethics of AI and ethical AI. Journal of Database Management 31, 2 (2020), 74–87.
  65. Perceived and objective usability and visual appeal in a website domain with a less developed mental model. In Proceedings of the Australian Computer-Human Interaction Conference on Designing Futures: The Future of Design.
  66. Lucille Alice Suchman. 1987. Plans and situated actions: The problem of human-machine communication. Cambridge University Press.
  67. AutoML in the wild: Obstacles, workarounds, and expectations. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  68. Yuan Sun and S Shyam Sundar. 2022. Exploring the effects of interactive dialogue in improving user control for explainable online symptom checkers. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  69. S Shyam Sundar. 2020. Rise of machine agency: A framework for studying the psychology of human–AI interaction (HAII). Journal of Computer-Mediated Communication 25, 1 (2020), 74–88.
  70. S Shyam Sundar and Mengqi Liao. 2023. Calling BS on ChatGPT: Reflections on AI as a Communication Source. Journalism & Communication Monographs 25, 2 (2023), 165–180.
  71. The White House. 2023. Fact Sheet: Biden-Harris Administration Secures Voluntary Commitments from Leading Artificial Intelligence Companies to Manage the Risks Posed by AI. https://www.whitehouse.gov/briefing-room/statements-releases/2023/07/21/fact-sheet-biden-harris-administration-secures-voluntary-commitments-from-leading-artificial-intelligence-companies-to-manage-the-risks-posed-by-ai/. Accessed: December 8, 2023.
  72. Who am AI?: Mapping Generative AI Impact and Transformative Potential in Creative Ecosystem. In Proceedings of the 26th International Academic Mindtrek Conference. 344–349.
  73. David R Thomas. 2006. A general inductive approach for qualitative data analysis. American Journal of Evaluation 27, 2 (2006), 237–246.
  74. H. Holden Thorp. 2023. ChatGPT is fun, but not an author. Science 379, 6630 (2023), 313–313.
  75. Jan AGM Van Dijk. 2006. Digital divide research, achievements and shortcomings. Poetics 34, 4-5 (2006), 221–235.
  76. RePrompt: Automatic prompt editing to refine AI-generative art towards precise expressions. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  77. AI chains: Transparent and controllable human-AI interaction by chaining large language model prompts. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  78. Re-examining whether, why, and how human-AI interaction is uniquely difficult to design. In Proceedings of the 2020 Chi Conference on Human Factors in Computing Systems. 1–13.
  79. Beyond Self-Diagnosis: How a Chatbot-Based Symptom Checker Should Respond. ACM Trans. Comput.-Hum. Interact. 30, 4, Article 64 (2023), 44 pages.
  80. Wordcraft: Story writing with large language models. In Proceedings of the ACM Conference on Intelligent User Interfaces.
  81. Why Johnny can’t prompt: how non-AI experts try (and fail) to design LLM prompts. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
  82. Lvmin Zhang and Maneesh Agrawala. 2023. Adding conditional control to text-to-image diffusion models. ArXiv e-prints (2023).
  83. Synthetic lies: Understanding Ai-generated misinformation and evaluating algorithmic and human solutions. In Proceedings of the CHI Conference on Human Factors in Computing Systems.
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Authors (4)
  1. Yuan Sun (117 papers)
  2. Eunchae Jang (2 papers)
  3. Fenglong Ma (66 papers)
  4. Ting Wang (213 papers)
Citations (3)
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