The world of storytelling is a constantly evolving landscape, as the name of this blogs eludes to. Creators seemingly won’t stop seeking out innovative ways to captivate audiences and convey their tales. Nor should they!

If readers remember, more than a decade ago, transmedia storytelling emerged on the scene as a groundbreaking approach that brought stories to life across multiple platforms and media, in turn engaging audiences in more immersive, participatory experiences. At the time, transmedia eventually got phased out by dilution of the concept (looking at you, my friends in the marketing world, why couldn’t you just leave a poor term alone!), along with many a heated discussion around what should be considered “real” transmedia and what should not.

There were some truly amazing and innovative projects launched during those years and the actual notion of transmedia storytelling – i.e. telling stories rooted in the same story world but more or less separate from each other, with each still contributing to the whole, agnostically distributed over the most suitable technical platforms – remained and remains as relevant as ever.

Now though, it might just be all those visionary thoughts could be brought to life quicker than anyone could have imagined. Yeah, I’m talking about generative artificial intelligence, about everything from AutoGPT and ChatGPT to Midjourney and Stable Diffusion. It feels like these are the tools we’ve been waiting for, even if we didn’t know we were.

But before we dive into the discussion about the role of AI in transmedia storytelling, let’s take a moment to reflect on the origins of that creative movement. The concept of transmedia storytelling captured the imagination of the entertainment industry – and many others – in the early years of the 21st century, introducing a fresh approach to narrative experiences that extended beyond the confines of traditional media.

Transmedia storytelling is, at its core, a method of weaving a single narrative, many narratives or a storyworld across multiple platforms and media formats. The central idea is to create a more immersive, engaging experience for audiences by connecting the dots between different elements of the story across various channels, such as films, books, games, and social media. This approach encourages active participation from the audience, inviting them to explore the storyworld and piece together the narrative puzzle.

There were many great creators and thinkers (and tinkers, I guess :)) within transmedia back in the day – way too many to mention here – but one of the OGs, i.e. media scholar Henry Jenkins, was instrumental in shaping the vision for transmedia storytelling with his concept of “spreadable media” playing a pivotal role in the movement. Jenkins posited that stories should be designed to “spread” across multiple platforms, with each piece of content adding value and depth to the overall narrative experience. This approach, it was argued, not only fosters audience engagement but also promotes co-creation, empowering fans to contribute their own ideas and interpretations to the storyworld.

In the age of digital media, stories should be designed for active participation rather than passive consumption. By crafting narratives that encourage audience interaction and collaboration, creators can foster a more dynamic and inclusive storytelling environment, where fans become co-creators and active agents in the storyworld.

Even though this wasn’t much more than a decade ago, the realisation of the full potential of transmedia storytelling was hampered by, among other things, technological limitations. The tools and platforms available were often fragmented and siloed, sometimes making it challenging to create a seamless, interconnected narrative experience that truly resonated with audiences. (To be fair, we haven’t gotten that much further just yet, but that might be changing).

And for sure, maintaining narrative coherence and consistency across multiple platforms was a challenge as well. With various media formats and channels at play, ensuring that every piece of content contributed meaningfully to the overall story and stayed true to the narrative vision was a complex and often daunting task. To add to this, all of these challenges brought costs with them, making true transmedia campaigns somewhat expensive affairs.

Now though, venturing into the world of AI-assisted transmedia storytelling, we are presented with what could be an exciting opportunity to overcome challenges such as the ones above and perhaps finally see the emergence of “true” transmedia storytelling. Looking at the rapid advancements in AI over the past year and months (and weeks and days!) it quickly becomes clear that these technologies are offering creators a wealth of opportunities to push the boundaries of narrative experiences.

At the forefront of AI-generated content is Natural Language Processing (NLP), a subset of the AI field that focuses on the interaction between computers and human language. Among the most advanced of these models is OpenAI’s GPT-4. Anyone who has played around with the model can attest that it boasts an incredible ability to generate coherent and contextually relevant text based on a given input. GPT-4 offers creators the opportunity to produce diverse content with remarkable speed and efficiency, from generating story ideas and dialogues to crafting entire screenplays (and perhaps finally getting those pesky NPCs in Skyrim to say anything interesting)

AI can also be used to analyse content and provide insights into audience engagement and emotional responses. Sentiment analysis and emotion recognition technologies enable creators to look at the impact of their narratives, identify areas for improvement and fine-tune storytelling strategies accordingly. By understanding how audiences connect with the story on an emotional level, transmedia storytellers can craft more resonant and impactful narratives across multiple platforms.

Beyond these kinds of analysis, AI-driven content analysis can help creators identify patterns and trends in audience engagement. This makes it possible to reveal which elements of the story resonate most with fans. By leveraging these insights, storytellers can adapt their narratives to maximise audience impact and ensure that each piece of content contributes meaningfully to the overall storyworld.

Another one of the most exciting applications of AI in transmedia storytelling is the potential it gives creators to prepare for content personalisation. AI can analyse individual audience preferences and tailor narratives accordingly, ensuring that each fan experiences the story in a way that is uniquely meaningful to them. This level of customisation should by all accords create a truly immersive and engaging experience, encouraging deeper connections between audiences and the storyworld.

AI-driven personalisation can also pave the way for adaptive storytelling and interactive narratives, where the story evolves in response to audience input and decisions. This dynamic approach to storytelling empowers audiences to become active participants in the narrative, fostering a sense of ownership and investment in the storyworld. Perhaps we can finally cross the bridge between gaming and other forms of entertainment?

Now, as mentioned earlier when talking about the challenges a decade ago, one of the key challenges faced by transmedia storytellers is maintaining narrative coherence across multiple platforms. AI-powered story bibles and world-building tools can help creators overcome this challenge by generating and organising vast amounts of narrative information, helping to ensure consistency and continuity throughout the storyworld. I’ve played around with GPT-4 to test out it’s capabilities as a co-pilot when creating narratives and these tools can assist in identifying plot holes, character inconsistencies, and other potential issues, enabling storytellers to refine their narratives and create a more cohesive and immersive experience for audiences.

In transmedia storytelling, collaboration between creators is essential to ensure a consistent and coherent narrative across platforms. AI can facilitate this process by serving as a powerful communication tool, enabling creators to collaborate more efficiently and effectively. From generating ideas and concepts to refining storylines and character arcs, AI can streamline the creative process and ensure that every piece of content contributes meaningfully to the overall narrative experience.

Looking further along the media technology tree and all its branches, AI-driven AR/VR experiences can also foster deeper audience engagement by offering more interactive and participatory storytelling opportunities. By allowing audiences to actively shape the narrative through their actions and decisions, AI-powered immersive experiences can help validate the users interactions, create a unique sense of ownership and investment in the storyworld, further blurring the lines between creator and audience, and enhancing the overall transmedia experience.

As was the case more than a decade ago (although a lot of that time was spent creating fictional Twitter characters if I’m remembering correctly) social media is a critical component of transmedia storytelling and AI-generated content can help creators craft engaging and contextually relevant campaigns that resonate with audiences. From generating captivating visuals and animations to crafting targeted posts and messages, AI should be able to help streamline the content creation process and ensure that every piece of content contributes to the overall narrative experience.

And, of course, AI can also help us understand our transmedia audiences better, By analysing social media data, AI can provide valuable insights into audience preferences, behaviors and trends, enabling creators to develop targeted engagement strategies that resonate with fans.

However, there are of course also challenges. I believe most of us have encountered arguments against the use of AI, on many different grounds. There’s a truly delicate balance between human creativity and AI-generated content to take into consideration. And, of course, there are legal and ethical implications when it comes to this approach to storytelling.

While AI offers a great many opportunities for content generation and analysis, it is crucial to recognise that human creativity remains an indispensable component of the storytelling process. The unique insights, emotions, and experiences that human creators bring to the table cannot – at least not yet! – be replicated by AI, and it is this collaboration between human and machine that will ultimately drive the most compelling and resonant narratives.

It’s also important not to get carried away. As AI-generated content becomes more advanced and accessible, we must take care not to be over-reliant on these tools at the expense of human creativity. While AI can streamline the creative process and generate impressive content, these technologies must not overshadow or diminish the value of human input. Striking the right balance between AI-generated content and human creativity will be essential to fostering a vibrant and innovative transmedia storytelling ecosystem.

As AI-generated content becomes more prevalent, questions of intellectual property and authorship are becoming increasingly complex. Establishing clear legal frameworks for AI-generated content will be critical – while hoping for such frameworks not to stifle innovation and expansions unduly.

The more data-driven and personalised storytelling gets, in the name of transmedia storytelling or any other form of storytelling, privacy concerns will become increasingly relevant. Ensuring that audience data is collected, stored, and used responsibly will be critical to maintaining trust and transparency in the storytelling process. And it needs to be budgeted for, for every project!

Despite all the challenges and potential hurdles, I’m increasingly convinced that the transmedia projects we dreamed of years ago can now actually become realities, and at a far lesser cost and at a far speedier pace than ever thought possible. Crafting interesting, immersive, personalised worlds where audiences can find their own place and their own path, where stories are rendered anew and unique, where NPCs have a soul and an own agenda independent of any user or audience member – that’s now becoming a true possibility. I can’t wait to see what the world comes up with!

2 thoughts on “Revolutionising transmedia through AI

  1. Awesome post buddy!
    Ah the halcyon days of the wild west of Transmedia, where everything was innocent and there seemed to be a universes of possibilities! (damn those marketers for spoiling things!!)

    But I whole heartedly agree with you that AI can action those dreams we had… with the caveat you state about human creativity has to be at its core.
    The 2 most exciting things for me about AI are
    1. the potential (as you state) it has to run vast experiences and adapting to an audience (that the human can then create extra content for)
    2. creating tailored niche individual experiences. This is something that we always tried to do (and sometimes had to because of the participation numbers…), but the scale of it seemed too big. If AI could have prewritten stories (by a human) that AI could uniquely adapt to an individual – then I think we will have true immersion at last (and yes bring the game world closer)

    I’ve been playing around with the original Chatgpt to create social media campaigns for a new short film I’m releasing – but they’re basically rehashes of what you can find on a how to market website… Do you think Chatgpt4 would create a more nuanced specialist campaign?

    (Out of interest me and Paul have receAntly got a grant for something, and we used chatgpt to write the basic framework of the application answers – which we then adapted! And we got the grant too!!)

    Hope you’re well my friend!

    • Rhys, hi! You bring up a couple of really good points. I agree with what you wrote about the tailored niche individual experiences which have always felt like kind of a pipe dream, basically just too big to undertake and way too complex to guarantee a quality experience. Having tried out AgentGPT and looked at other experiments people are doing I’m inclined to believe GPT4 could at least help create a much more nuanced campaign.

      (Congrats on the grant! And kudos for leveraging available resources)

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