Generative AI as a Collaborative Tool for Transforming Digital Storytelling Projects

Last modified date

Recently, a group of design minded folks in the NY6 gathered for some conversation around generative AI, and the potential impacts that it can have on teaching and learning.  One of the outcomes of this gathering for me has been a renewed interest in thinking about how we can transform the digital narrative project into a more robust and engaging project for students while keeping the importance of digital storytelling at the forefront.  Digital storytelling, at the core, is about being able to communicate an impactful message in a concise but relatable way.  Humans, after all, are storytellers.  

In thinking about digital storytelling with ‘an AI component’ I’ve landed on a couple of different useful ways that I can see the current generation of generative tools might be integrated into an assignment workflow.  These ideas aim to keep the student centered in the learning process, while using AI as a tool to expedite some of the more mundane elements and leverage the tool as a thought partner in much the same way one might collaborate with a larger team if they were to produce such work in a production environment.  

First, AI as a collaborator.  Generative AI tools have a fantastic ability to take on personas and are designed for interactions that mimic a conversational nature.  AI tools could easily be used by students to help prompt new ideas, critique arguments, and provide a lens through which a student might receive feedback in a way that is both useful to them, highly personalized, and most importantly, delivered in an almost 1:1 fashion that breeds a certain feeling of safety and comfort.  I’ve found this last point to be especially useful, even as a more outgoing individual, as there are times that the AI can critique my work such that I find obvious holes in logic, and I think to myself ‘yeah, not sure anyone in the meeting would point that out, for risk of sounding offensive.’  

Beyond the human-machine interaction there’s an element of personalization that AI brings that I think can be helpful to the process.  Because these tools are trained on such large datasets they have the ability to craft metaphors and analogies that are highly personalized to the user.  While this has obvious implications when it comes to learning, I think it has further applications when it comes to creative endeavors.  If a student is trying to craft a narrative that is targeted to a specific demographic, AI can assist greatly with providing context, criticism, and a voice by which one can query against or bounce ideas off.  While not perfectly representative (and in need of a discussion about bias, for sure), this may be a helpful exercise for students to engage in, if only to instruct them that this type of questioning is an important element in their creative process.  

I think the last thing that I’ve come to realize is that the content generation of AI can be a real asset to storytelling projects.  Not because the tools can, of themselves, create stories (of varying levels of usefulness and interest), but because they can allow students to explore things that may require resourcing or technical prowess that the student simply doesn’t have.  Current image generation, and soon, video generation tools, have the ability to create scenes that you can textually describe without any real understanding of things like composition, lighting and rigging, equipment, etc.  While that might be scary and daunting for many creatives, there is a potential here for students to really leverage these tools to create things that would just be impractical for a myriad of reasons.  An example of this would be a student that wants to shoot a scene ‘in’ Paris.  One might not have the means, time, etc. to fly to Paris for a shoot – but with some creative editing and a set of AI tools it’s possible that a student can create a representation of Paris  in B-roll like shots that would withstand audience scrutiny.  It removes a limiting factor that might otherwise prevent that project from being made. 

And this is where I think there is real value in exploring creative AI tool sets for students’ digital stories.  Storytelling can be tremendously impactful, and impart on students many useful transversal skills that will last a lifetime while helping to solidify their learning by linking it to a context they will recall later.  Generative AI, for its part, can be seen as a threat to this type of learning, or viewed as an opportunity to engage students in a way that will push them into learning in new ways while producing a work product that stretches beyond a static document.  

If you’re interested in digital storytelling or working on a project related to generative AI in your courses, please let me know! We’d be happy to collaborate.  Email us at  

Andrew Smith