Type of Presentation
Individual paper/presentation
Conference Strand
Ethics in Information
Target Audience
Higher Education
Second Target Audience
Other
AI enthusiasts and AI critics
Relevance
With so much hype and halo around GenAI, it makes sense to pay heed to my presentation in that it alerts AI enthusiast and gullible AI enthusiasts to how GenAI has put so many things on the line.
Proposal
If an AI system like ChatGPT generates text used in a research paper, proper attribution, and delineation of human-written vs. AI-generated text is essential. Research has suggested that many readers cannot reliably distinguish between human and AI writing. Failing to attribute AI writing could constitute plagiarism (Dobrin, 2023). Guidelines need to be established. Similarly, if ChatGPT is used to analyze sensitive interviews or user data from research study participants, appropriate consent, privacy protections, and data security controls must be implemented. Researchers should be transparent about any AI analysis or exposure of protected participant data. On the heels of this comes the possibility that making assumptions in research based on AI texts could perpetuate harm (Cercone & McCalla, 1984). To that end, researchers have an ethical duty to consider bias in AI tools.
Moreover, it is incumbent on us to report when and how Generative AI was used throughout the research study takes on paramount importance. Researchers can uphold strong ethical principles even as AI collaboration changes the research landscape by considering these issues of authorship, privacy, bias, and transparency. Both human and technical aspects require ongoing thoughtful evaluation.
Goal: The goal of this presentation is cautionary. It aims to alert users of Generative AI to the potential ramifications of using AI for research and writing.
Audience: Anyone interested in hearing about some repercussions of AI in the realm of ethics can be my audience member.
Sources:
Cercone, N., & McCalla, G. (1984). Artificial intelligence: Underlying assumptions and basic
objectives. Journal of the American Society for Information Science, 35(5), 280-290.
Dobrin, S. I. (2023). Talking about Generative AI: A Guide for Educators. Broadview Press.
Presentation Description
If an AI system like ChatGPT generates text used in a research paper, proper attribution, and delineation of human-written vs. AI-generated text is essential. Research has suggested that many readers cannot reliably distinguish between human and AI writing. Failing to attribute AI writing could constitute plagiarism (Dobrin, 2023). Guidelines need to be established. Similarly, if ChatGPT is used to analyze sensitive interviews or user data from research study participants, appropriate consent, privacy protections, and data security controls must be implemented. Researchers should be transparent about any AI analysis or exposure of protected participant data. On the heels of this comes the possibility that making assumptions in research based on AI texts could perpetuate harm (Cercone & McCalla, 1984). To that end, researchers have an ethical duty to consider bias in AI tools. Moreover, it is incumbent on us to report when and how Generative AI was used throughout the research study takes on paramount importance. Researchers can uphold strong ethical principles even as AI collaboration changes the research landscape by considering these issues of authorship, privacy, bias, and transparency. Both human and technical aspects require ongoing thoughtful evaluation.
Keywords
Alpha persuasion, AI dilemma, ethical dilemma of AI, AI in research, AI pedagogy
Publication Type and Release Option
Presentation (Open Access)
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mainaly, Shiva, "Ethical Considerations in Using Generative AI in Writing Studies Research" (2024). Georgia International Conference on Information Literacy. 28.
https://digitalcommons.georgiasouthern.edu/gaintlit/2024/2024/28
Included in
Arts and Humanities Commons, Curriculum and Instruction Commons, Information Literacy Commons
Ethical Considerations in Using Generative AI in Writing Studies Research
If an AI system like ChatGPT generates text used in a research paper, proper attribution, and delineation of human-written vs. AI-generated text is essential. Research has suggested that many readers cannot reliably distinguish between human and AI writing. Failing to attribute AI writing could constitute plagiarism (Dobrin, 2023). Guidelines need to be established. Similarly, if ChatGPT is used to analyze sensitive interviews or user data from research study participants, appropriate consent, privacy protections, and data security controls must be implemented. Researchers should be transparent about any AI analysis or exposure of protected participant data. On the heels of this comes the possibility that making assumptions in research based on AI texts could perpetuate harm (Cercone & McCalla, 1984). To that end, researchers have an ethical duty to consider bias in AI tools.
Moreover, it is incumbent on us to report when and how Generative AI was used throughout the research study takes on paramount importance. Researchers can uphold strong ethical principles even as AI collaboration changes the research landscape by considering these issues of authorship, privacy, bias, and transparency. Both human and technical aspects require ongoing thoughtful evaluation.
Goal: The goal of this presentation is cautionary. It aims to alert users of Generative AI to the potential ramifications of using AI for research and writing.
Audience: Anyone interested in hearing about some repercussions of AI in the realm of ethics can be my audience member.
Sources:
Cercone, N., & McCalla, G. (1984). Artificial intelligence: Underlying assumptions and basic
objectives. Journal of the American Society for Information Science, 35(5), 280-290.
Dobrin, S. I. (2023). Talking about Generative AI: A Guide for Educators. Broadview Press.
