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Adapting Nielsen's heuristics and new AI-specific heuristics for AI interfaces.
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Based on SOC occupation classification
Proactively identifying failure modes, misuse, and unintended consequences.
Managing shared context, memory, and state across multiple agents.
Coordinating text, image, voice, and tool-use modalities in a single interaction.
Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.
Reading user emotional state from text signals — caps, punctuation density, repetition, latency — and adapting before the user disengages.
Designing review workflows to surface and mitigate bias in AI outputs.
| name | heuristic-evaluation-ai |
| description | Adapting Nielsen's heuristics and new AI-specific heuristics for AI interfaces. |
Nielsen's 10 usability heuristics were designed for traditional software. AI products need adapted heuristics that address the unique challenges of probabilistic, generative, and conversational systems.
1. Visibility of system status AI adaptation: The user should always know what the AI is doing, what it's working with, and how confident it is. Progress indicators for generation. Transparency about data sources. 2. Match between system and real world AI adaptation: The AI should use language and concepts the user understands. Don't expose model internals. Frame capabilities in terms of user tasks, not technical features. 3. User control and freedom AI adaptation: Users must be able to stop generation, undo AI actions, edit outputs, and override suggestions. AI autonomy should always have an exit. 4. Consistency and standards AI adaptation: The AI should behave consistently across similar requests. Same input type should produce same output format. Persona should be stable. 5. Error prevention AI adaptation: Design prompts and interfaces that guide users toward effective interactions. Suggest clarifications before producing low-quality output. 6. Recognition rather than recall AI adaptation: Show users what the AI can do rather than requiring them to discover commands. Surface relevant capabilities contextually. 7. Flexibility and efficiency of use AI adaptation: Support both novice (guided) and expert (shortcut) interaction modes. Power users should be able to customise AI behavior. 8. Aesthetic and minimalist design AI adaptation: AI outputs should be concise and well-structured. Don't pad responses with unnecessary caveats or filler. 9. Help users recognise, diagnose, and recover from errors AI adaptation: When the AI fails, explain what went wrong in user terms, not technical terms. Offer clear recovery paths. 10. Help and documentation AI adaptation: Provide contextual guidance on how to interact with the AI effectively. Teach prompting skills through the interface.
Beyond the classic 10, AI products need evaluation against:
