This week’s readings got me thinking: How much is AI not just in our classrooms, but also in our future careers? It feels like we’re navigating a brand-new world, and the lines haven’t been drawn yet.
One area that stood out from the paper “Augmenting the Author” is the issue of transparency. The authors highlight the “depth of transparency in researchers’ access and utilization of AI” and the concerns this raises about the “reliability and credibility of AI-generated text.” This really resonates when we think about assignments or professional reports. How do we know if the work is truly our own or mostly AI-generated?
A key grey area lies in defining authentic authorship and intellectual contribution when AI is involved. For example, in one of my previous classes, an alumnus from Pfizer told us that they sometimes use AI to generate mock drug syntheses, which they then refine and test. I found this interesting in relation to this week’s discussion, but I didn’t get a chance to ask about it at the time AI’s usage and credited contributions can be a touchy subject.
As the researchers point out, there’s a concern that reviewers (or instructors) might end up “validating AI’s work” instead of the author’s. Moving forward, clear guidelines emphasizing transparency about AI use will be crucial. We need to foster a culture where acknowledging AI assistance isn’t seen as a weakness but as a step toward ethical and responsible innovation.