Transparency: Reflections on Human-AI Collaboration
Transparency, Trust, and “Workslop”
Could transparency about AI use actually erode trust? A recently published study suggests it might. That’s a provocative claim, especially since I’m developing AI Pathfinder Foundations with transparency as a core principle.
As I continue working on the upcoming AI Pathfinder Foundation course, I want to be 100% transparent with learners about my own human-AI collaboration journey. Creating this course has been a highly rewarding process of learning, research, and practice in human-AI partnership.
I began this project with the goal of gaining a deeper understanding of the opportunities, challenges, and risks related to AI as I design, research, and teach learning experiences. To that end, I tried and used many AI tools in developing this course and have been conducting a parallel autoethnographic research project throughout the process – more details to follow on that in a future post.
My Transparency Aims
As I developed the course, I documented key aspects of my human-AI collaboration to understand what worked, what didn’t, where AI added value, and where human judgment was irreplaceable. My goal in being transparent is to:
- Model the responsible AI practices I teach,
- Provide authentic examples for your learning, and
- Contribute to our understanding of effective human-AI collaboration.
Throughout the course, I’ve given examples of my AI collaboration journey in Behind the Scenes sections of my end-of-module reflections. By sharing this process openly, I hope to demonstrate the development of my own AI skills and knowledge, including my successes, failures, and apprehensions about human-AI collaboration.
My Human-AI Takeaways
What’s my human-AI takeaway so far? While this process has shown me how humans and AI can partner to create something neither could achieve alone, it has reinforced my belief that maintaining human creativity, expertise, and ethical oversight is essential to ensure quality and authenticity. Importantly, I’ve spent countless hours trying to tease out valuable insight from workslop, the AI generated work content that “masquerades as good work, but lacks the substance to meaningfully advance a given task”. Whether that has cost or saved me time, I cannot say, but I do feel the collaboration is creating a better work product.
Overall, I’m seeing ways AI can accelerate certain tasks, but it takes my human judgment and effort to distinguish genuine insight from plausible-sounding nonsense. Perhaps we’re approaching a point where AI use becomes assumed rather than disclosed. Until then, I’ll continue documenting this journey, partly as what I see as an ethical obligation, but also to share what human-AI collaboration looks like in practice.
– Jennifer
Want to follow along as I document this journey?
I’ll be sharing Next Path Notes about building this course, my AI discoveries, and behind-the-scenes insights from launching a new venture.