Organizations racing to deploy AI lack structured ways to balance speed with safety, risking backlash or harm. A toolkit could offer validation checklists, risk assessment templates, and benchmarks to guide responsible development.
Target AI labs and enterprise teams who need to demonstrate due diligence to stakeholders and regulators.
Start with a simple checklist of safety considerations based on emerging best practices. Later add automated risk scoring based on model characteristics.
The biggest risk is that safety processes might slow development too much, making the tool unpopular with growth-focused teams.