Annotated Bibiography Legaspi, Christian Dr. Ruskin, D. EN111-19 Part A: Peer-Reviewed Sources: Illia, L., Colleoni, E., & Zyglidopoulos, S. (2023). Ethical implications of text generation in the age of artificial intelligence. Business Ethics, the Environment & Responsibility, 32(1), 201-210. Article poses questions on the ethical implications of GLM’s. “How should we regulate its use to ensure responsible deployment in public discourse?” Article refers to what we call GLMS as Automated Text Generation (ATG’s). Hosseini, M., Rasmussen, L. M., & Resnik, D. B. (2023). Using AI to write scholarly publications. Accountability in Research, 1-9. Article includes background on how GLM’s function. “While NLP systems are likely to become better at minimizing bias, doing math, making relevant connections between concepts, and avoiding plagiarism, they are likely to continue to make factual and commonsense reasoning mistakes because they do not (yet) have the type of cognition or perception needed to understand language and its relationship to the external physical, biological, and social world.” The journal cited also aims to adopt a policy on the inclusion of GLM’s in their Journal, aiming to maintain transparency and practicality.\ Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89-100. ` The article explores the positive aspects of AI text generation. The article refers to message autocomplete in services like Gmail as “AI Mediated Communication” or AI-MC. AI-MC predicts the response a user may have to a received message. The article addresses many areas of concern such as transparency but also the right to the first amendment. Part B: Other Notable Sources: Anderson, N., Belavy, D. L., Perle, D. M., Hendricks, S., Hespanhol, L., Verhagen, E., & Memon, A. R. (2023). AI did not write this manuscript, or did it? Can we trick the AI text detector into generated texts? The potential future of ChatGPT and AI in sports and exercise medicine manuscript generation. BMJ Open Sport & Exercise Medicine, 9(1), e001568. This article cites AI text detection tools such as GPTZero, GPT-2 Output Detector, and AI Detector to test their question of if AI generated text is distinguishable from human written text in the context of a sports medicine manuscript. Authors conclude that the generated papers would be rejected by BMJ journals due to inaccurate references. Article references Nolan B., who used AI to write and illustrate a childrend’s book in one weekend. Yang, D., Zhou, Y., Zhang, Z., Li, T. J., & LC, R. (2022, March). AI as an active writer: interaction strategies with generated text in human-AI collaborative fiction writing. In Joint Proceedings of the ACM IUI Workshops (Vol. 10). Author utilizes machine learning to enhance their writing. Article uses ChatGPT-2, but ChatGPT-3 may be utilized in the same way. The tool is given a research question, and the following sections talk about what strategies can be used for interaction with AI-generated Text.
