Evelyn ANG
Data Literacy Programme
Office of the President, NUS
Ang, E. (2024). Reimagining data storytelling with generative AI [Lightning talk]. In Higher Education Conference in Singapore (HECS) 2024, 3 December, National University of Singapore. https://blog.nus.edu.sg/hecs/hecs2024-eang/
SUB-THEME
Opportunities from Generative AI
KEYWORDS
Data storytelling, Generative AIs, adult learners, ChatGPT-4o, custom GPTs
CATEGORY
Lightning Talk
EXTENDED ABSTRACT
Data storytelling is a new superpower for making complex data accessible and engaging (Loewen, 2024a). Schwabish (2014) as well as Green and Brock (2000) highlight how visual and narrative elements enhance comprehension and persuasion, essential for effective data communication. Dykes (2020) demonstrates through real-world examples how compelling data stories can lead to more informed business decisions. Loewen (2024b) describes data storytelling as the art behind the science—the art of making sense out of a deluge of data, shaping it into something that sticks. The integration of generative AIs in storytelling creates more engaging narratives, akin to how bards once used music to enliven stories. Despite myths about data storytelling being just simplistic visualisation, it can be said to be a misconception. Dykes explained that effective data storytelling uses coherent narratives supported by meaningful visualisations to engage audiences deeply. Moreover, Generative AIs democratise the ability to analyse vast datasets, allowing humans to focus on creativity and emotional intelligence (Dykes, 2024). By combining AI capabilities with human adaptability, data storytellers can make data insights more compelling and actionable. Li (2024) has done a detailed scan into data storytelling tools available, and most are prototypes for research purposes. McKinsey & Company (2024) published an article reporting a surge in AI adoption in at least one business function in early 2024. Generative AI adoption is moving beyond professional setting and is much more likely to be used in both work and personal settings.
Generative AI is here to stay and beckons the question how we can purpose generative AIs in data storytelling.
In this lightning talk, I will highlight broadly what is good data storytelling as suggested by Knaflic (2015) in her book Storytelling with Data in areas (1) understanding the context, (2) choose appropriate visual display, (3) eliminate clutter, (4) focus attention where you want it, (5) think like a designer, and lastly (6) tell a story. Now to address the elephant in the room—how will Gen AI fit into this picture? Recent work by Li (2024) proposed four distinct levels of AI involvement in working with data from the data workers’ perspectives, based on the levels of human agency versus AI automation. However, today’s advancement of AI has yet to be able to only perform a singular role with simple prompt inputs effectively. Kesari (2024) proposed a matrix of how different tools with GenAI are suited for different kinds of decisions to be made.
How do we put all these together towards better data storytelling? I will broadly show how we can position fit-for-purpose use of GenAIs into the data storytelling preparatory work based on customGPTs. I will also weave in how GenAIs can be purposefully deployed so leaving us humans to do what we do best—creativity and connecting with our audience (Dyke, 2024). We will also visit how the most popular generative AI—ChatGPT—will be able to become your new companion in data storytelling through my CustomGPT—NarratEve. I will also touch on using Custom GPTs (Loewen, 2024) that can make your data storytelling and preparation even more effective.
REFERENCES
Dykes, B. (2020). Effective data storytelling: How to drive change with data, narrative, and visuals. John Wiley and Sons, Inc.
Dykes, B. (2024). The Future of Data Storytelling is Augmented, not Automated. Forbes. https://www.forbes.com/sites/brentdykes/2024/02/27/the-future-of-data-storytelling-is-augmented-not-automated
Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79(5), 701-721. https://doi.org/10.1037//0022-3514.79.5.701
Kesari, G. (2024, 17 January). The Enduring Power of Data Storytelling in the Generative AI Era. MIT.edu. https://sloanreview.mit.edu/article/the-enduring-power-of-data-storytelling-in-the-generative-ai-era/
Knaflic, C. N. (2015). Storytelling with Data: a data visualization guide for business professionals. Wiley.
Li, H. (2024). Why is AI not a Panacea for Data Workers? An Interview Study on Human- AI Collaboration in Data Storytelling. arXiv
Li, H. (2024). Where are we so far? Understanding Data Storytelling Tools from the perspective of Human-AI collaboration. arXiv
Loewen, J. (2024). Custom GPT Creation For Data Visualization: A Step-by-Step Guide. Towardsai.net. https://towardsai.net/p/data-analysis/custom-gpt-creation-for-data-visualization-a-step-by-step-guide
Loewen, J. (2024a). Why Data Storytelling is Your New Superpower. Medium https://medium.com/data-storytelling-corner/why-data-storytelling-is-your-new-superpower-9f76e62762ce
Loewen, J. (2024b). What the Heck is Data Storytelling Anyways? Here Are The Basics. Medium. https://medium.com/data-storytelling-corner/what-the-heck-is-data-storytelling-anyways-here-are-the-basics-c47c72cba44b
McKinsey & Company (2024). The state of AI in early 2024: Gen AI adoption spikes and starts to generate value. McKinsey https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
Schwabish, J. A. (2014). An economist’s guide to visualizing data. Journal of Economic Perspectives, 28(1), 209-234. https://dx.DOI.org/10.1257/jep.28.1.209