How generative AI can augment the creative process (Part 1)
How generative AI can augment the creative process (Part 1)
January 4, 2024
“ChatGPT is one of those rare moments in technology where you see a glimmer of how everything is going to be different going forward,” noted the American tech entrepreneur Aaron Levie.
Have you already heard of ChatGPT? Played around with it? Or even began using it to amplify your business? Following its launch on November 30, 2022, this large language model-based chatbot developed by OpenAI has taken the tech world by storm. And over the past months, we have witnessed the advent of many more new generative artificial intelligence (AI) tools that promise to enhance productivity, effectiveness, and speed in business massively.
While there has been a wide consensus that AI will replace many analytical, knowledge-based tasks, professional roles, and business functions, most experts predicted that this would not apply to work related to human creativity. Well, that was before the emergence of the latest generative AI tools.
So, over the past months, I wondered: How will generative AI affect creativity in the workplace? And more specifically, how can we use it in workable, meaningful ways in the creative process? Based on my preliminary experimental experiences, I share my thoughts on how generative AI tools can be used to augment a creative process method.
What are creative process methods?
Creative process methods (aka Innovation methods) are structured process flows that outline the steps and cognitive activities an individual or a team needs to follow while solving a problem creatively or working through an innovation project case. In short, such an innovation method provides you with an order of working or thinking steps to follow. These models have been around for more than 70 years, and some methods rose to prominence for some time before being superseded by a new approach. Examples are, the Creative Problem-Solving Model (CPS, in the 1960s-1970s) or, more recently, Design Thinking (previously known as the IDEO method).
How generative AI can augment X-IDEA: Preliminary musings
X-IDEA is the innovation method and toolbox I created for thinkergy and fine-tuned in more than 150 innovation projects involving most of the spectrum of modern innovation types over the past two decades. X-IDEA comprises five distinct process stages (each with three subordinated work steps and cognitive activities): Xploration, Ideation, Development, Evaluation, and Action. So, how do I envision using generative AI in the five stages of X-IDEA?
Stage X-Xploration: AI as a secondary research assistant
The initial stage of X-IDEA, Xploration, aims to help an innovation team gain insights based on a deeper understanding of the innovation project case to frame the real challenge (which is almost always different from what the members of an innovation team initially perceive it to be). In the Xploration stage, generative AI fulfills primarily the role of a (secondary) research assistant to support an innovation team working on the case:
During the first step (Xpress your understanding of your innovation case), generative AI can add additional knowledge to the team's knowledge base and the initial project brief.
In the second step, the team CALMly Xplores its case by CHECKING (facts, assumptions, and rules), ASKING (great questions), LOOKING (differently at the challenge by embracing different viewpoints and perspectives), and MAPPING (out information visually). Here, we treat a generative AI tool like ChatGPT as a separate Xploration team by giving it the same work instructions as the team for some of the X Tools (such as doing Walk a Mile in the shoes of key stakeholders or creating archetypical Customer Profiles).
Finally, when we Xtract the main stage outputs in the third and final step of the Xploration stage, generative AI can help to quickly close any remaining knowledge gaps (Infosourcing). Moreover, it can synthesize all identified Aha insights into a meta-insight description that supports the human innovation team members' effective framing of the Final Challenge.
While the generative AI outputs are often on a more general level and sometimes lack specificity, they can augment and broaden the more case-specific, profound human outputs. As such, these AI tools can help an innovation team uncover perceptual blind spots and knowledge gaps, thus limiting the danger that team members fail to notice some essential aspects related to a particular innovation challenge.
Stage I-Ideation: AI as an additional source of raw ideas
The purpose of the Ideation stage in X-IDEA is to generate a large pool of raw ideas (several hundred to more than a thousand) with the help of creativity techniques. Here, as creative process facilitators, we can use generative AI tools to generate additional ideas that we later add to the “human-generated raw idea pool.
Apart from ChatGPT and its key competitors (such as Google’s Bard, Microsoft’s Bing Chat, and Claude.ai), there are also special AI Ideation tools such as Seenapse.ai where you can enter an innovation challenge and ask it to give you a specified number of ideas.
When gauging the AI-generated ideas, many are on relatively high levels of abstraction, meaning that they often do not deeply cater to the nuances of a specific innovation case of a particular company. However, some ideas contain interesting aspects that we can use in the subsequent X-IDEA stage.
As such, generative AI can help push up the idea quantity, thus contributing to achieving the Ideation stage’s aim. And because X-IDEA is one of the few creative process methods with TWO distinct creative stages, Ideation and Development, we can also confidently add these AI-generated ideas into the raw idea pool with the peace of mind that in the third stage of X-IDEA, we will have solely humans take care of transforming idea quantity into quality. More on this in the next part of X-IDEA.
Interim conclusion and outlook:
Generative AI tools can support an innovation team well at the front end of the creative process. ChatGPT and other generative AI bots can help innovation team members broaden their perspectives during Xploration and boost the team’s idea quantity during Ideation. How can we best use generative AI in the later stages of the creative process? In part 2, I will discuss how we can include —and choose to exclude— generative AI in the final three stages of X-IDEA (Development, Evaluation, and Action).
Have you become curious to see how we use generative AI to support our work as we go through the creative process? Book an X-IDEA innovation project with us, and we show you how to solve a real-life innovation challenge your business currently faces. Contact us to learn more.
Nota bene: The title image is an AI-generated representation of how ChatGPT described itself as follows:
"Picture a shimmering, translucent sphere made of ever-changing, glowing patterns and colors, representing the vast amount of knowledge and information I have access to. Within the sphere, you might see intricate, flowing patterns of data streams, resembling a neural network or a web of interconnected ideas. These patterns are constantly shifting and evolving, symbolizing my ability to generate text and assist with various tasks."
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