Designing for Explainability: From Interrogability to Intent Alignment
📰 Medium · UX Design
Learn to design for explainability in AI agents to build trust through transparency and intent alignment
Action Steps
- Apply explainability principles to AI agent design
- Configure interrogability features to show the work
- Test intent alignment in AI decision-making processes
- Build transparency into AI systems to foster trust
- Evaluate the effectiveness of explainability features in AI agents
Who Needs to Know This
UX designers and AI engineers benefit from this knowledge to create more trustworthy and transparent AI systems
Key Insight
💡 Explainability is key to building trust in AI agents
Share This
🤖 Design for explainability in AI to build trust!
Full Article
When agents act on our behalf, trust depends on more than answers. It depends on explainability so that the agent “show the work”. Continue reading on Bootcamp »
DeepCamp AI