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Research, standards & evidence

Trust begins by saying what is known—and what is not.

M.I.N.D. intends to connect metacognitive practice with recognized AI governance while maintaining clear boundaries among established evidence, developed methods, participant experience, and open inquiry.

Alignment language does not mean certification, regulatory approval, or verified conformance. Those claims require appropriate independent processes.

Evidence architecture

Five kinds of knowledge. Clearly distinguished.

01

Established research

Peer-reviewed and authoritative work on metacognition, learning, decision-making, organizational behavior, participatory governance, and related fields.

02

Recognized frameworks

AI governance and management sources such as the NIST AI RMF, ISO/IEC 42001, applicable law, and domain-specific duties.

03

M.I.N.D.-developed practice

Concepts, facilitation methods, reflection structures, and proposed decision records developed by M.I.N.D.; clearly labeled and open to evaluation.

04

Participant experience

What people report, observe, or learn in an engagement. Valuable as experience, but not automatically generalizable evidence.

05

Exploratory inquiry

Philosophical, cultural, or future-oriented questions presented as invitations to examine—not as settled scientific fact.

Interoperability anchors

Designed to connect with existing responsibility systems.

These sources provide important foundations. M.I.N.D. contributes a reflective decision practice around them; it does not reproduce, replace, or certify conformance to them.

NISTAI Risk Management FrameworkGovern · Map · Measure · Manage ↗NISTGenerative AI ProfileCross-sectoral companion resource ↗ISOISO/IEC 42001:2023AI management system standard ↗EUAI Act frameworkRisk-based legal obligations ↗

Proposed research agenda

The practice must be able to question itself.

  1. 01

    Does structured metacognitive review improve the quality and traceability of institutional AI decisions?

  2. 02

    Which participants, forms of dissent, and decision rights produce meaningful—not symbolic—challenge?

  3. 03

    How should affected-life and ecological considerations be represented, evidenced, and acted upon?

  4. 04

    Which parts of the practice transfer across cultures and institutions, and which must remain locally governed?

  5. 05

    What burdens, blind spots, power effects, or false assurances could the M.I.N.D. process itself create?

Research collaboration

Help test usefulness, limitations, and unintended effects.

We welcome inquiry from researchers, evaluators, standards practitioners, public-interest institutions, and funders committed to transparent learning.

Propose a research conversation