Design Challenges for AI Products
In this lesson, we will discuss the challenges and opportunities in the space of AI design patterns. While the AI industry has advanced, there are several unresolved problems and areas for innovation.
Summary
As a designer, being aware of these gaps positions you to be a stronger designer in the industry, ensuring you are solving problems beyond the current state of what has already been defined by the industry.
Clutter and Decision Fatigue: The overwhelming number of options in AI products can lead to user fatigue. Solutions like progressive disclosure and simplification are needed.
Complexity in AI Experiences: New and unfamiliar elements complicate interactions. There’s a need to simplify feedback mechanisms, buttons, and hierarchical structures in UI.
Context Windows and Memory: Educating users on AI's context limits (e.g., memory) and handling errors and model updates transparently remain major challenges.
Handling Errors Gracefully: AI needs better ways to communicate errors and provide alternative suggestions instead of vague responses like "something went wrong."
Text Formatting: Understanding use-cases and ensuring the text format outputted supports your current need.
Safety, Privacy, and Transparency: There’s confusion over privacy and safety, and a need for better communication and controls around what data is stored and shared.
Loading States and Delighting Users: Current loading experiences lack creativity and engagement, and there’s a need to make these moments more delightful and informative.
Relying on Prompt Engineering: There's an over-reliance on text input, and AI could benefit from more user-friendly UI to guide interactions.
Lack of Standardization: Terms like "regenerate" or "retry" vary across platforms, causing confusion. A standardized language could improve user understanding.
Content Design and Branding Issues: AI branding and naming conventions (e.g., "AI Studio") often confuse users. More clarity and innovation in AI branding are needed.
Marketing to Non-AI Enthusiasts: Marketing campaigns are often targeted at a niche audience. There's a gap in appealing to a broader, less tech-savvy user base.