What is the Grey Jacket Problem?



Is your team using generic GPT models to make content? You might be suffering from the Grey Jacket Problem, meaning your content will look like everyone else’s average grey jacket very soon…

We believe teams need both customized tools and training to understand how to become the prompt architects that will improve your organization.

In the world of artificial intelligence (AI), there’s a challenge emerging that could be pivotal for social impact organizations: the “Gray Jacket” problem. It’s a term coined to describe the uniformity of output when AI tools like GPT-3, GPT-4, and others are used without specialized input or guidance. These large language models, trained on vast internet data, are prone to generating average, indistinct content — metaphorically putting everyone in the same gray jacket and blue pants.

This issue comes into sharp focus when considering the use of AI in sectors where uniqueness and customization are not just beneficial but necessary. Without a keen understanding of prompt architecture — the skill of designing AI prompts to produce specific, tailored responses — organizations might find themselves blending in rather than standing out, echoing the anecdote of two individuals unintentionally dressing identically at an event.

For social impact entities, the stakes are high. The “Gray Jacket” problem signifies the risk of their messages getting lost in a sea of generic AI-generated content. To prevent this, there is an urgent need to develop expertise in prompt architecture, akin to the way social media savvy became crucial in the previous decade. This capability will empower organizations to guide AI tools to generate distinctive, impactful content that resonates with their unique mission and audience.

The call to action is clear: social impact organizations must invest in learning how to effectively harness AI, making the technology an asset for creating original content that captures the essence of their work and avoids the pitfall of averageness.

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