The importance of story making combining humans and AI at KMWorld 2024

While storytelling uses stories as a communication strategy, story thinking uses story structure as an operational strategy, embedding sensemaking within working and learning models and environments.

At KMWorld 2024, John Lewis, CKO, Explanation Age LLC, and, Art Murray, CEO, Applied Knowledge Sciences, Inc. and Director, Enterprise of the Future Program, International Institute for Knowledge and Innovation, presented their session, “Story Thinking: Combining Human & Artificial Intelligence.”

Examples discussed included organizational KM strategies, innovation management, leadership profiles, clinical process models within healthcare, early warnings within large projects, and an emerging AI-assisted platform designed to activate the story thinking capacity of users and induce a state of flow when making sense of information from multiple sources.

“We usually think of representation as taxonomy,” Lewis said. “I hope we can think about this as making story. We’re wired for storytelling to make sense of the world.”

Story patterns consist of a beginning, middle, and end. Or there’s a challenge, choice, and then outcome, Lewis explained. Story patterns can also be cyclic when emotional states are the key things you are communicating.

“We settle into a way of working without even thinking about it,” Lewis said.

The classic story pattern consists of “The Hero’s Journey,” he noted. Story thinking is seeing story as communication and operational strategy.

The pattern of story thinking at work consists of the following workflow processes:

• Automation
• Disruption
• Investigation
• Ideation
• Expectation
• Affirmation
• Automation

“GenAI has some limitations,” Murray said. “It’s almost limited our thinking.”

The number one question asked of GenAI is: Here is my problem, what should I do?

KM/AI toolkit consists of inputs which are from documents and data sources, unstructured data, and more, Murray explained. The technology to interpret these things include GenAI/LLMs, AI-based text/data analytics, layered reference ontology, extractive/explainable AI, or human sensemaking.

“We want to add human experts, teams of them, to make sure everything is correct,” Murray said.

Applying this to a story structure model comprises of the following thought processes:

• I come up with ideas
• I build things
• I test and remember what works
• I know how things work
• I can see things that can go wrong 
• I dig into the data and discover new trends

“In KM we collect a rich body of knowledge and if you build this ontology, it’s even more enriched,” Murray said.

KMWorld returned to the J.W. Marriott in Washington D.C. on November 19-21, with pre-conference workshops held on November 18.

KMWorld 2024 is a part of a unique program of five co-located conferences, which also includes Enterprise Search & Discovery, Enterprise AI World, Taxonomy Boot Camp, and Text Analytics Forum.