AI incident reporting
Mandatory disclosure of system failures so that others can learn from them.
What it commits you to
Incident reporting turns private, dispersed failures into a shared dataset, which is the only mechanism by which a field learns at collective rather than individual speed. Its benefits are real and its current state is thin: most serious AI failures are disclosed under voluntary arrangements. Disclosure rules also cut against red-teaming, which depends on not publishing what worked.
Which realms lean on this
Procedure, not conviction. This is the vocabulary of constitutions, audits and the people who have to sign.
governance · 2 realms — The Contractual Court, The Ubuntu Weave.
Canon that discusses this
declaration · 1986
The Asilomar AI Principles
Drafted over a few hours on the final day of a four-day 1986 conference on future technologies, and the first written set of research principles for advanced AI agreed by the researchers themselves. Its structure — general principles plus separately stated capability thresholds — is the structure of every frontier safety framework since. The excerpt below paraphrases the principles rather than reproducing the agreed wording.
primary · 300 BCE
Mozi
The one ancient Chinese text that argues for impartial care as a principle rather than as a sentiment: regard others' parents as your own, reject aggressive war and defensive hierarchy, and justify both by an explicit standard. The excerpt below paraphrases the jian xiang ai chapters rather than quoting a translation.
modern · 2019
Human Compatible: Artificial Intelligence and the Problem of Control
Russell argues that perfect value alignment is the wrong goal: systems are built by imperfect people, for imperfect objectives, and certainty about human values would be dangerous if it were achieved. The alternative is enough uncertainty about human preferences to keep a human in the loop as a genuine check. The excerpt below paraphrases the argument rather than quoting the 2019 book.
See also
External auditing
governanceIndependent verification of a developer's claims by an accredited third party.
AI safety case
governanceA structured, auditable argument that a system's residual risk is acceptable.
Red teaming
technicalSystematically attacking a model before users do, to find its failure modes.
Regulatory capture
governanceA regulator becoming aligned with the interests it is meant to constrain.