“Writing with generative AI and human-machine teaming: Insights and recommendations from faculty and students” discusses the experiences and insights gained from using large-language model generative AI in a professional writing course. The authors share their perspectives on integrating AI into the writing process, highlighting issues such as balancing AI integration, maintaining authorial agency, negotiating grading and evaluation, and the benefits and drawbacks of AI. They also explore the evolving role of AI in writing and its implications for writers, teachers, and students.
Key takeaways from the paper include:
- AI adoption: Large-language model AI, such as OpenAI’s ChatGPT, is being widely used, with significant rates of adoption across various professional fields. It is rapidly evolving and becoming an integral part of the writing landscape.
- Ethical and effective use: Faculty and students need to engage with and explore AI writing technologies in an ethically responsible and rhetorically effective manner. They should adapt to, reflect on, and critique generative AI technologies for their own writing work and as part of their roles as citizens and scholars.
- Adaptation and collaboration: Writers can adapt and assert agency in the process of human-machine collaboration. The experiences shared by the authors demonstrate how individuals can navigate their relationships with AI, from initial apprehension to collaborative partnership.
- Considerations for faculty and students: The paper concludes with specific recommendations for faculty and students. These recommendations include addressing the challenges of AI integration, defining expectations for AI usage, fostering open communication between faculty and students, and exploring the potential benefits and limitations of AI in writing and teaching.
The paper highlights the transformative potential of generative AI in writing while emphasizing the importance of responsible and critical engagement with these technologies. It encourages ongoing exploration and adaptation to maximize the benefits of AI while maintaining authorial agency and ethical considerations.
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