Safety-Performance Tradeoff Model Web App
This interactive tool explores competitive dynamics in AI development, specifically examining whether safety innovations necessarily produce safer systems in practice.
The resource addresses a paradox: even after the AI safety community achieves breakthroughs enabling alignment with human values at modest performance costs, and when this knowledge is widely communicated to companies and governments, deployed AI systems may remain equally risky years later. The authors examine why safety advances don't automatically translate into safer deployed systems.
"the safety-performance tradeoff model (SPT Model) of AI competition" provides a framework for understanding this phenomenon. The web app allows interactive exploration of how competitive pressures between organizations might incentivize performance gains over safety improvements, even when safer approaches are available and known.
The core question investigates whether capability breakthroughs in AI safety necessarily lead to implementation of those safety measures across the industry, or whether market dynamics and competitive advantage create conditions discouraging their adoption.