🛡️Trust & Ethics

Trust Decays Faster Than Speed Improves—Design Accordingly

Risk asymmetry. Understanding the math of trust in AI systems.

Quick Answer

For search, voice, and "just tell me what to do".

Trust takes many positive interactions to build but can be destroyed in one negative experience. This asymmetry means conservative AI design—erring on the side of human involvement when uncertain—is often the mathematically better choice, even if it sacrifices some efficiency.

Key Takeaways:

  • Trust accumulates slowly, collapses quickly
  • One bad interaction can undo many good ones
  • Conservative design protects accumulated trust
  • Err toward human involvement when uncertain
  • Long-term math favors trust protection

Playbook

1

Calculate the value of trust in your business

2

Design AI for trust preservation over efficiency

3

Implement conservative escalation thresholds

4

Monitor trust impact of AI decisions

5

Treat trust as a balance sheet item

Common Pitfalls

  • Optimizing for speed over trust
  • Ignoring trust impact in AI design
  • Aggressive containment at trust's expense
  • Not measuring trust alongside efficiency

Metrics to Track

Trust trend over time

Trust recovery time after incidents

Trust-adjusted efficiency metrics

Long-term value by trust segment

FAQ

How do I balance trust with speed expectations?

Fast is only valuable when accurate and trustworthy. A slightly slower response that gets it right beats a fast response that erodes trust. Design for 'fast enough and reliably trustworthy.'

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Salarsu - Consciousness, AI, & Wisdom | Randy Salars