Definition
Human-AI interaction is the study and design of how people and AI systems communicate, collaborate, and build trust, so the AI feels helpful and predictable rather than confusing or frustrating.[1]
At a glance
- It is a branch of human-computer interaction (HCI) focused on AI, which acts more like a collaborator than a passive tool.[1]
- AI is probabilistic: it makes educated guesses and sometimes gets things wrong, so the experience must handle mistakes gracefully.
- Microsoft’s widely-cited 18 Guidelines for Human-AI Interaction (CHI 2019) group good practices into four moments: at the start, during use, when the AI is wrong, and over time.[2]
- For a business, this is about adoption: employees and customers only keep using AI tools they understand and trust.
Why it is different from normal software
A normal button does the same thing every time. AI predicts, so it can be confidently wrong, change behavior, or surprise users. That unpredictability means the interface must set clear expectations about what the AI can do, show why it suggested something, and make it easy to undo or correct.[3]
What good design looks like in practice
Tell users up front what the tool does well and badly. Let people accept, edit, or dismiss AI suggestions instead of forcing them. When the AI errs, offer an easy fix and explain briefly. Learn from corrections and respect user data. These habits drive trust, and trust drives real adoption.[4]
Bottom line
Treat AI as a helpful but fallible teammate: design the experience so people understand it, can correct it, and come to trust it, because trust is what turns an AI tool into one your team and customers actually use.