Principles do not field themselves: why I am writing RAIDops
I did not set out to write a book.
RAIDops began during my Master of Science studies in Columbia University's Information & Knowledge Strategy program. An independent study, guided by Blake M. DiCosola III and strengthened by the advice and input of Edward J. Hoffman, started as a literature review of trustworthy artificial intelligence in national defense. Blake and Ed are both IKNS faculty; Ed previously served as NASA's first Chief Knowledge Officer.
The review grew into a long paper. The paper kept returning to an unresolved organizational problem. Eventually, the problem outgrew the paper.
I invented RAIDops and coined the name Responsible AI Development Operations for the framework that emerged from that work. The working monograph is coauthored with Blake and Ed, whose substantive intellectual contributions, guidance, editing, and mentorship have materially shaped it.1 Their collaboration has made the work substantially better.
I have hesitated to write publicly about RAIDops because the research program is active and the manuscript is unfinished. I am not going to reproduce the complete pattern catalog, assessment instruments, or the book's full analytical machinery here. But a framework concerned with reviewability should itself be open to review. This essay offers the public argument: enough to explain and defend RAIDops, while preserving the monograph as the place where the complete derivation, architecture, patterns, evidence controls, and limitations belong.
The thesis is straightforward: trustworthy AI is not merely a property to test in a model. It is an operating achievement that an organization must repeatedly produce, challenge, bound, preserve, and sometimes revoke.
That problem is not abstract to me. It recurs across my work in enterprise AI engineering, knowledge systems, and public-sector technology: building a capable system is only part of the job. The institution must also keep the purpose, evidence, authority, and means of intervention intact as the system crosses teams, contracts, environments, and time.