The Guardian picked up on this discussion with an article entitled “‘Full-on robot writing’: the artificial intelligence challenge facing universities.” The article provided background links on specific developments in AI writing and describes how universities are responding to new technological developments, noting how some institutions (this article was focused on Australia) are considering such works as plagiarism in their policy statements. It poses the question of how educators should view current developments:

“To put the argument another way, AI raises issues for the education sector that extend beyond whatever immediate measures might be taken to govern student use of such systems. One could, for instance, imagine the technology facilitating a “boring dystopia”, further degrading those aspects of the university already most eroded by corporate imperatives. Higher education has, after all, invested heavily in AI systems for grading, so that, in theory, algorithms might mark the output of other algorithms, in an infinite process in which nothing whatsoever ever gets learned.

But maybe, just maybe, the challenge of AI might encourage something else. Perhaps it might foster a conversation about what education is and, most importantly, what we want it to be. AI might spur us to recognise genuine knowledge, so that, as the university of the future embraces technology, it appreciates anew what makes us human.”

Despite all the hand-wringing, an Inside Higher Education piece written by a professor of a class (“Rhetoric and Algorithms”) outlines the results of an in-class experiment with AI tools, in which the professor encouraged undergraduate students to use as many AI tools as possible to create an essay. The professor found the overall quality of the results to be poor, but perhaps more importantly for an overarching discussion of this topic, students did not like the process using such tools:

“I asked my students to write short reflections on their AI essays’ quality and difficulty. Almost every student reported hating this assignment. They were quick to recognize that their AI-generated essays were substandard, and those used to earning top grades were loath to turn in their results. The students overwhelmingly reported that using AI required far more time than simply writing their essays the old-fashioned way would have. To get a little extra insight on the ‘writing’ process, I also asked students to hand in all the collected outputs from the AI text generation ‘pre-writing.’ The students were regularly producing 5,000 to 10,000 words (sometimes as many as 25,000 words) of outputs in order to cobble together essays that barely met the 1,800-word floor.”

The professor argues that good writers produce better AI output, noting also that can, with such assignments, be effectively used to illustrate to students about the writing submission and feedback process, with the tools providing immediate feedback to students, which motivated students could use to learn. He argues that others worried about plagiarism in their assigned essays can mitigate the risk of AI-generated work by making assignments very specific, and notes also that educators and university policymakers must take developments in this area into account:

I am deeply skeptical that even the best models will ever really allow students to produce writing that far exceeds their current ability. Effective prompt generation and revision are dependent on high-level writing skills. Even as artificial intelligence gets better, I question the extent to which novice writers will be able to direct text generators skillfully enough to produce impressive results.

I would tend to agree with this author, with the current state of technological affairs. I do wonder how current plagiarism tools would be able to track AI-written content, if it’s not in the corpus of comparative texts for a tool, and possible burdens imposed on writing instructors in determining if work is original or not.

And the more I deal with written texts, I feel more than ever that written assignments are crucial to quality higher education. The academic writing process, in my opinion, sharpens students’ skills in many areas, particularly if work is carefully reviewed by instructors with appropriate and constructive feedback. And I agree with the author of the second article, that AI tools can be helpful learning tools (I myself use AI grammar and language tools for this purpose).

I do, however, worry about a world, as alluded to in the first article, in which journalistic content is written by AI. Rather than question of the role of writing in higher education, perhaps we should question where and how AI (not just written output) interacts with the real world, perhaps skewing perceptions.

Graham, S. S. (October 24, 2022). AI-Generated Essays Are Nothing to Worry About. Inside Higher Ed. https://www.insidehighered.com/views/2022/10/24/ai-generated-essays-are-nothing-worry-about-opinion

Sparrow, J. (November 18, 2022). ‘Full-on robot writing’: the artificial intelligence challenge facing universities. The Guardian. https://www.theguardian.com/australia-news/2022/nov/19/full-on-robot-writing-the-artificial-intelligence-challenge-facing-universities

• One encouraging pulling items off the shelves
• The other advocating keeping the items, perhaps in a special section, together with the letter from the publisher about the content, as a learning tool.

Participants in this discussion acknowledged such situations do not arise very often, but it did remind me of a teaching situation this past semester in which I, in a one-off instructional session, showed students an example of research misconduct (an official U.S. Department of Health & Human Services Office of Research Integrity case) using an article flagged as “retracted” in its host database. The case study was an extremely compelling learning tool and provided students with an example of short-term decision making which had long-term implications. Because of this, I really like the idea of keeping items with integrity issues on the shelves, clearly noting the academic integrity issue, as a way to show students “real world” examples of ethical issues in practice.

The discussion also spurred my contemplation about the realm of thought our research group is currently investigating, which I’ve christened in my own mind as “The Wild West of Individual Science Communications Decision Making.” As I write this, it seems to me there are three broad, greatly simplified conceptual areas in which individual (science-related) decisions are made:

• Decisions about research areas formalized in content (often peer-reviewed) made by scientists for other scientists.
• Representations of this content written by scientists or journalists for the general public, varying in level of trueness to original content and in format (e.g., press release, blog, social media post). Decisions are made here by scientists or journalists in crafting the secondary representation(s).
• Individual representations/interpretations within the minds (note: I’m undecided at present about a better way to say this) of those reading or interacting with secondary communications about topics, themselves discovered and read in a variety of settings within a communication environment (or multiple environments). These individual “frames” are then – potentially – used or modified whenever future decisions (career, personal) touching upon a topical area are required.

At each of these places, there is room for “pollution,” as Kahan (2017) puts it, leading to an erosion of the power of “free, reasoning citizens to recognize valid science, and hence to fully realize its benefits” (preprint version, 11). Sometimes, the scientific and environmental “certifiers of truth” (researchers, journalists, publishers, libraries) fail – and when this happens, individual decision makers are left to their own devices in interpreting truth. This is the frontier, the Individual Decision Making Wild West.

Turning back to the collib-l discussion, it seems to me as I write this that it’s important to keep items with academic integrity issues on the shelves, in the databases – but to highlight any problematic areas. It’s maybe one small way to help students develop their thinking in relation to ethical issues by exposing them to complexity and failure points of scientific research and publishing in order to, perhaps, help them when they reach  decision making frontiers in the course of their careers and personal life journeys.

Additional Reading

Kahan, Dan M., On the Sources of Ordinary Science Knowledge and Extraordinary Science Ignorance (June 13, 2016). Oxford Handbook of the Science of Science Communication (Forthcoming); Yale Law & Economics Research Paper No. 548. Available at SSRN: https://ssrn.com/abstract=2794799