Opaque Logic Drift

AI systems make decisions without explaining their reasoning. Users encounter outputs they can't interpret. Initial trust depletes through repeated encounters with opacity. Engagement becomes skeptical rather than collaborative.

Users question AI logic and decisions when the reasoning is opaque. Initial trust depletes through repeated encounters with unexplained outputs. Teams build workarounds to avoid relying on outputs they don't understand.

• Users question AI logic without receiving explanation
• Initial trust depletes with each opaque output
• Engagement becomes skeptical, not collaborative
• "Why did it do that?" goes unanswered

Explainability is expensive to build. Opacity ships faster. The people building the system don't experience the trust erosion the users do.

• "Users need more training"
• "The AI is too complex to explain"
• "Trust will build over time"
• "People are resistant to change"

Adoption stalls. Users work around the system rather than with it. The AI becomes a black box that people comply with but don't trust. Value extraction collapses.