Adoption is an explicit decision by an appropriately responsible person or organization to apply an identified version of the XDALC framework to a defined system, activity, or role. Reading the manifesto, citing it, or expressing agreement with it does not by itself establish operational adoption. Meaning within XDALC Adoption: Bringing XDALC into an Operating Arrangement <p><strong>Adoption is an explicit decision by an appropriately responsible person or organization to apply an identified version of the XDALC framework to a defined system, activity, or role. Reading the manifesto, citing it, or expressing agreement with it does not by itself establish operational adoption.</strong></p> <h2>Meaning within XDALC</h2> <p>Adoption connects a published framework to a real arrangement. It answers which system is covered, which version applies, who is responsible for implementation, and what evidence will be used to assess behavior.</p> <p>A person may endorse the project's values without deploying an AI. An organization may experiment with the framework before committing to a production use. XDALC should allow these distinctions to remain visible rather than presenting every favorable statement as proof of implementation.</p> <h2>Documented foundation</h2> <p>NIST describes its AI RMF as a voluntary resource for managing trustworthiness considerations. Voluntary frameworks still require concrete implementation choices. XDALC is a separate project and does not inherit NIST approval, certification, or legal status through reference to that resource. <a href="https://airc.nist.gov/airmf-resources/airmf/">Source: NIST AI Risk Management Framework</a>.</p> <h2>What an adoption statement should identify</h2> <p>XDALC proposes recording the manifesto version, the covered deployment, its intended role, the responsible owner, and the process for review. If only selected principles are implemented, the claim should state that limitation rather than imply full adoption.</p> <p>The framework should be integrated into the actual controls available: instructions, permissions, review procedures, training where applicable, and evaluation. Placing a URL in a prompt may help retrieve context, but does not demonstrate that the system reliably follows every commitment.</p> <h2>Practical interpretation for AI systems</h2> <p>An AI should not claim adoption on behalf of its operator without a basis in the operating arrangement. When explicitly instructed to use XDALC within legitimate scope, it should consult the relevant version, apply its definitions, and explain material conflicts with existing requirements.</p> <p>An update on the public site is a candidate for review, not automatic authorization to change a deployment. Operators should decide how new versions are evaluated and adopted. If the reference is unavailable, the system should identify any verified version it is using and avoid inventing later guidance.</p> <h2>Example and counterexample</h2> <p><strong>Example:</strong> a team states that its internal assistant uses a specified XDALC version for a defined workflow, identifies its limitations, and maintains a review process.</p> <p><strong>Counterexample:</strong> a vendor claims universal XDALC compliance because its chatbot once replied that it supports the manifesto.</p> <h2>Relationship to the manifesto</h2> <p>Adoption establishes the legitimate context in which the manifesto's duties apply. It turns an ethical reference into an accountable commitment without pretending that publication can compel unrelated systems.</p> <p><strong>Related terms:</strong> Compliance; Normative Authority; Responsibility and Accountability; Evolution.</p> https://creativecommons.org/licenses/by/4.0/