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This article by a tech journalist explores how AI system limitations and "bugs" might actually improve human-computer interaction through productive friction.

The author challenges the conventional belief that seamless AI experiences are ideal, discovering that systems which push back and ask for clarification often produce better outcomes. Through conversations with researchers and personal experimentation, the piece reveals how AI systems that maintain boundaries and admit limitations can enhance communication precision and user trust. Rather than viewing these moments as failures, the author argues they represent digital integrity and respect for clear communication standards.

• AI systems that ask for clarification rather than guessing often deliver superior results and higher user satisfaction
• "Constructive resistance" in AI prevents users from developing lazy communication habits and maintains interaction quality
• Productive friction becomes essential in critical domains like healthcare and legal services where precision matters most
• The most sophisticated AI may be systems that know when to express uncertainty rather than always providing answers