2/1/2024

Working with AI: The Invisible Information

Recognize and articulate the hidden information we take for granted in human work.

Picture yourself explaining a task to a new colleague. Now imagine doing the same with an AI assistant. Notice how differently you need to communicate? When working with humans, we rely on shared context, unstated assumptions, and cultural understanding. With AI, we’re discovering that this invisible information needs to be made explicit.

The Hidden Layer of Human Work

Every workplace has its unwritten rules and implicit knowledge:

• “Ramu from Sales likes data in his presentations, Pari prefers stories”
• “We always double-check numbers during quarter-end”
• “That client prefers brief emails over detailed ones”
• “The marketing team gets sensitive about brand colors”

These invisible rules shape how work gets done. Humans absorb this knowledge naturally through observation and interaction. But when working with AI, this tacit knowledge becomes a crucial missing piece.

Why This Matters Now

As AI tools become more integrated into our daily work, the gap between what’s explicitly stated and what’s implicitly understood becomes more apparent. An AI assistant might write a perfect email in isolation, but miss crucial context about the recipient’s preferences or past interactions.

This isn’t just about better prompting or instruction-giving. It’s about recognizing that effective human-AI collaboration requires us to surface and articulate knowledge we’ve never had to verbalize before.

Starting to See the Invisible

The first step is becoming aware of this hidden information layer. Context is everything. Start noticing moments when you automatically adjust your work based on unwritten rules or context. Some questions to consider:

• What background information do you naturally consider when making decisions?
• What contextual knowledge helps you interpret communications correctly?
• What unstated rules guide your interactions with different team members?

By making these invisible elements visible, we can begin to bridge the gap between human and AI ways of working.