Authorship and responsibility

    About Richard

    Richard Foster-Fletcher founded MKAI in 2019 and is responsible for its editorial direction.

    MKAI stands for Morality and Knowledge in Artificial Intelligence. Founded by Richard Foster-Fletcher in 2019, it is now his public research archive on AI and organisations.

    The work examines what AI changes inside institutions: formal records, governance, accountability, language, judgement, deployment, and the allocation of responsibility.

    Overhead view of papers and notecards on a wooden desk

    The work

    Richard’s research is concerned with the gap between institutional claims about AI and the records that sit beneath those claims.

    The archive reads public material carefully: company reports, governance documents, vendor terms, regulatory material, public documentation, court records, and other inspectable sources. Each study states what was read, what was found, what the finding does not claim, and how the record should be cited.

    Why MKAI exists

    MKAI exists to keep the record clear while AI adoption is still being described through optimism, vendor language, productivity claims, and institutional self-reporting.

    The archive does not try to predict where AI will go next. It records what organisations have already said, what their documents show, and what their governance arrangements leave unresolved.

    Editorial responsibility

    Richard is the author and editor responsible for MKAI.

    The archive is written to be checked. Claims should stay close to the evidence that supports them. Limits should be visible. Corrections should be possible. A study should remain readable after the surrounding argument has moved on.

    What MKAI is for

    MKAI is built for readers who need a stable record: researchers, journalists, executives, board members, lawyers, policy professionals, and others trying to understand what AI is doing to organisations beneath the surface language of adoption.

    The archive is designed to be cited, contested, and re-read over time.

    What MKAI avoids

    • MKAI does not recommend vendors.
    • It does not publish implementation guidance.
    • It does not present adoption as progress by default.
    • It does not turn research records into sales material.

    The purpose is simple: keep the record stronger than the claims built on top of it.