Balancing completeness with clarity

The best AI explanations focus on what users need for decisions, not technical completeness. Different situations require different detail levels, from brief hints to full documentation.

Most cases need focused explanations. A social media feed might explain it shows "posts from friends you interact with most" without listing every ranking factor. Users get enough to understand their feed without overwhelming detail. The detailed explanation would distract from the main task.

High-stakes situations demand transparency. AI systems helping judges with sentencing must explain everything. This context requires full documentation including data sources and decision thresholds.

Testing reveals the right balance. Watch real users to see where they get confused or overwhelmed. Different audiences often need different explanation depths. Build flexibility into your approach rather than forcing one size on everyone.