Should I design for humans or machines?

Design for people relies on intuition, context, and flexible interpretation, using signifiers and visual hierarchy to guide understanding. When systems become collaborators or sole contributors, human-centered assumptions break down because machines cannot infer meaning or fill in gaps. Machines execute based on explicit structure, rules, and consistency, so vagueness that helps humans can fail for systems. Design therefore needs to focus on how intent is translated into system-understandable representations, ensuring clarity and precision in interfaces and flows. The shift requires aligning design with machine interpretation rather than only human cognition.

"Human-centered design has been built around the idea that design should adapt to the way people think...not the way a system is structured. So designers created interfaces and flows that relied on intuition and context, while leaving room for human interpretation. But this approach breaks down when "user" also includes machines. Unlike our human users, machines can't infer meaning or fill in gaps; they need clarity and precision."

"When people were the sole focus of design, we needed to create signifiers to cue our users and help them understand the possible actions. Like making a digital button look clickable or visual hierarchy guiding the user's attention down a webpage. Now that design is beginning to serve people and systems, can we still depend on human-centered design thinking?"

"But machines don't work like people. Machines need explicit structure, rules, and consistency. The typical user we have designed for can infer meaning from vagueness and flexibility of ideas, but a machine can't. So we can no longer just design screens or user flows for human intuition; we now need to focus on how intent is translated by systems that don't think as people do."

Read at Medium