AI Trust Glossary · Canonical Definition
Trustworthy AI
AI systems that reliably behave within defined boundaries, communicate their reasoning clearly, demonstrate consistent decision-making, and operate with observable accountability.
Explanation
Trustworthy AI is about behavioral reliability, not capability. A trustworthy agent may be less capable than an untrustworthy one. What distinguishes it is predictability, transparency, accountability, and consistent constraint adherence even under pressure. Trustworthiness is measurable, not assumed.
Why it matters
The AI industry's default assumption is that trustworthiness can be inferred from capability, benchmarks, or developer reputation. This assumption fails in production. Trustworthy AI requires explicit measurement against specific behavioral dimensions, independent of developer claims.
How Borealis uses it
The BM Score is the Borealis operationalization of trustworthy AI. A BM Score above 800 (A tier or higher) represents a meaningfully trustworthy agent. A Flagged score represents an agent whose behavior is not trustworthy regardless of other qualities. The five dimensions together define what 'trustworthy' means in measurable terms.
See also