AI Design Principles
In this lesson, we will discuss AI design principles, which act as guidelines to help designers and teams make informed decisions when building AI-powered products. Pulling insights from lesson #2 - #5, these principles are grounded in value systems that represent the product, company, or team, and they are meant to evolve over time.
Summary
We covered four key AI design principles:
Design for Transparency and Clarity: Ensure that users understand what the AI system is doing at all times. Use clear labeling, such as watermarking or indicating when AI is involved, to build trust and reduce confusion.
Design to Inspire and Guide: AI is often a new experience for users, so products should provide inspiration and guidance through elements like suggested prompts and activities to help users engage effectively.
Design for Co-Creation: Balance human and AI inputs, allowing humans to remain in control while AI enhances the experience. Multimodal interactions, such as combining text and image inputs, are great examples of co-creation.
Design for Imperfection: Anticipate AI errors, such as hallucinations or system failures, and build experiences that account for them. For example, providing thoughtful error messages or asking follow-up questions when AI doesn't understand the input.
These principles are essential to guide designers in creating responsible and effective AI-powered products. By applying them, teams can create experiences that are transparent, empowering, and resilient to failure.