Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
131 tokens/sec
GPT-4o
10 tokens/sec
Gemini 2.5 Pro Pro
47 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

AI Does Not Alter Perceptions of Text Messages (2402.01726v2)

Published 27 Jan 2024 in cs.CL, cs.AI, and cs.HC

Abstract: For many people, anxiety, depression, and other social and mental factors can make composing text messages an active challenge. To remedy this problem, LLMs may yet prove to be the perfect tool to assist users that would otherwise find texting difficult or stressful. However, despite rapid uptake in LLM usage, considerations for their assistive usage in text message composition have not been explored. A primary concern regarding LLM usage is that poor public sentiment regarding AI introduces the possibility that its usage may harm perceptions of AI-assisted text messages, making usage counter-productive. To (in)validate this possibility, we explore how the belief that a text message did or did not receive AI assistance in composition alters its perceived tone, clarity, and ability to convey intent. In this study, we survey the perceptions of 26 participants on 18 randomly labeled pre-composed text messages. In analyzing the participants' ratings of message tone, clarity, and ability to convey intent, we find that there is no statistically significant evidence that the belief that AI is utilized alters recipient perceptions. This provides hopeful evidence that LLM-based text message composition assistance can be implemented without the risk of counter-productive outcomes.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (16)
  1. Ž. Bašić, A. Banovac, I. Kružić, and I. Jerković, “ChatGPT-3.5 as writing assistance in students’ essays,” Humanities and Social Sciences Communications, vol. 10, no. 1, pp. 1–5, Oct. 2023.
  2. T.-J. Chen, “ChatGPT and other artificial intelligence applications speed up scientific writing,” Journal of the Chinese Medical Association, vol. 86, no. 4, p. 351, Apr. 2023.
  3. M. A. AlAfnan, S. Dishari, M. Jovic, and K. Lomidze, “ChatGPT as an Educational Tool: Opportunities, Challenges, and Recommendations for Communication, Business Writing, and Composition Courses,” Journal of Artificial Intelligence and Technology, vol. 3, no. 2, pp. 60–68, Mar. 2023.
  4. P. Carlbring, H. Hadjistavropoulos, A. Kleiboer, and G. Andersson, “A new era in Internet interventions: The advent of Chat-GPT and AI-assisted therapist guidance,” Internet Interventions, vol. 32, p. 100621, Apr. 2023.
  5. F. Farhat, “ChatGPT as a Complementary Mental Health Resource: A Boon or a Bane,” Annals of Biomedical Engineering, Jul. 2023.
  6. M. B. Garcia, “Can ChatGPT Substitute Human Companionship for Coping with Loss and Trauma?” Journal of Loss and Trauma, vol. 28, no. 8, pp. 784–786, Nov. 2023.
  7. A. Alessa and H. Al-Khalifa, “Towards Designing a ChatGPT Conversational Companion for Elderly People,” Apr. 2023.
  8. J. Hohenstein, R. F. Kizilcec, D. DiFranzo, Z. Aghajari, H. Mieczkowski, K. Levy, M. Naaman, J. Hancock, and M. F. Jung, “Artificial intelligence in communication impacts language and social relationships,” Scientific Reports, vol. 13, no. 1, p. 5487, Apr. 2023.
  9. J. Kim, K. Merrill Jr., and C. Collins, “AI as a friend or assistant: The mediating role of perceived usefulness in social AI vs. functional AI,” Telematics and Informatics, vol. 64, p. 101694, Nov. 2021.
  10. Y. Liu, A. Mittal, D. Yang, and A. Bruckman, “Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email Writing,” in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, ser. CHI ’22.   New York, NY, USA: Association for Computing Machinery, Apr. 2022, pp. 1–13.
  11. M. Jakesch, M. French, X. Ma, J. T. Hancock, and M. Naaman, “AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness,” in Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, ser. CHI ’19.   New York, NY, USA: Association for Computing Machinery, May 2019, pp. 1–13.
  12. S. Valencia, R. Cave, K. Kallarackal, K. Seaver, M. Terry, and S. K. Kane, ““The less I type, the better”: How AI Language Models can Enhance or Impede Communication for AAC Users,” in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, ser. CHI ’23.   New York, NY, USA: Association for Computing Machinery, Apr. 2023, pp. 1–14.
  13. Y. Fu, S. Foell, X. Xu, and A. Hiniker, “From Text to Self: Users’ Perceptions of Potential of AI on Interpersonal Communication and Self,” Oct. 2023.
  14. H. Mieczkowski, J. T. Hancock, M. Naaman, M. Jung, and J. Hohenstein, “AI-Mediated Communication: Language Use and Interpersonal Effects in a Referential Communication Task,” Proceedings of the ACM on Human-Computer Interaction, vol. 5, no. CSCW1, pp. 17:1–17:14, Apr. 2021.
  15. J. T. Hancock, M. Naaman, and K. Levy, “AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations,” Journal of Computer-Mediated Communication, vol. 25, no. 1, pp. 89–100, Mar. 2020.
  16. A. Shoufan, “Exploring students’ perceptions of chatgpt: Thematic analysis and follow-up survey,” IEEE Access, vol. 11, pp. 38 805–38 818, 2023.
Citations (1)

Summary

We haven't generated a summary for this paper yet.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets