Responsible Human / Human Judgment Policy

Why this policy exists

Responsible technology cannot be achieved by writing rules for machines while assuming humans are automatically fair, attentive, informed, or accountable. People design the system, choose the data, set the incentives, approve the action, interpret the result, and decide whether to listen when harm is reported.

A human was involved is not, by itself, a safety standard.

Commitments

• Consequential work should have an identifiable owner with enough context and authority to question, pause, correct, or stop it.
• Human review must be active and informed: reviewers should understand what they are approving, inspect relevant evidence, and recognize uncertainty.
• We treat people as participants rather than raw material, with appropriate consent, privacy, agency, and a practical way to raise a question or report harm when circumstances warrant it.
• We question whose perspective is treated as normal, who bears risk, who receives benefit, who is absent, and who has power to challenge the result.
• Memory, intuition, authority, familiarity, and confidence are not substitutes for evidence.

No responsibility laundering

We do not blame an AI system, vendor, contractor, customer, or junior reviewer for a decision whose authority remained with DRKNYT. Nor do we describe a process as human-led when the human lacked time, information, choice, or realistic power to change the outcome.

Responsible human practice requires recognizing limits, inviting informed challenge, documenting important decisions, correcting verified harm, and changing systems that repeatedly produce the same failure.