The Big Picture
Use a five-step, auditable risk check before automating: if long-term risks to knowledge, resilience, regulation, or trust are high, keep people in the loop or preserve the role rather than automating.
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The Evidence
A practical decision protocol evaluates four long-term risks that typical cost-driven models miss: loss of tacit knowledge, reduced organizational redundancy, future regulatory exposure, and erosion of public trust. The protocol runs five sequential gates and produces one of four clear outcomes—automate, preserve, augment, or hybrid—each with prescribed governance actions. Scoring is deterministic and based on a 40-field input schema so decisions are reproducible and auditable, and language models may only assist narrative justification, not the scores themselves. Evaluation-Driven Development (EDDOps).
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Data Highlights
1Five sequential gates map to outcomes: failing Gates 1–3 → preserve, Gate 4 → hybrid, Gate 5 → augment; clearing all gates and the composite check → automate.
2A 40-field structured input schema powers deterministic scoring so identical inputs always produce the same decision and a full audit trail.
3Per-gate thresholds are set at 0.70 and the final composite threshold at 0.60 to catch accumulated moderate risk that single gates might miss.
What This Means
Product and engineering leaders deciding which roles or workflows to automate should use this to avoid losing institutional memory or creating brittle systems. Compliance, risk, and operations teams can use the protocol to produce auditable pre-decision records that link governance actions to specific risks. Human-in-the-Loop Pattern
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Learn MoreYes, But...
This is a version 1 conceptual protocol: many numeric parameters (weights, thresholds, country multipliers) were chosen by expert judgement, not empirical optimization. Composite-driven outcomes are more sensitive to parameter choices than single-gate decisions, so calibration per industry and sensitivity testing are important. The protocol focuses on organizational risks and does not replace post-deployment audits required by regulatory frameworks—it complements them upstream. Cascading Reliability Failures.
Methodology & More
A five-gate decision protocol evaluates automation candidates against four long-term, hard-to-price risks: tacit-knowledge erosion (losing institutional judgment), resilience reduction (creating correlated failure modes), regulatory exposure (cost of reversing automation if oversight is later required), and socio-institutional capital degradation (loss of trust with customers or partners). Candidates must pass an initial net-benefit filter before a structured scoring process—each risk dimension is computed from observable fields, normalized to a 0–1 range, and compared to per-gate thresholds. Failures route to explicit outcomes—preserve, hybrid, augment—or, if all checks are passed, automate. Vector Database Emergence-Aware Monitoring Pattern
Operationally, the protocol uses a 40-field input schema that yields deterministic scores and a versioned, approver-signed audit trail so regulators and auditors can reproduce decisions. Large language models are allowed only to help translate process descriptions into the structured fields or to draft narrative justification; they do not influence the numeric scoring. The design is intended as an upstream complement to existing post-deployment frameworks: it decides whether to commit to automation at all, rather than acting after deployment. Next steps are empirical validation, cross-industry calibration, and learning how scores drift over time from accumulated assessments.
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Credibility Assessment:
ArXiv preprint with no author affiliations or h-index information and zero citations. No recognizable institutional or author reputation signals — lowest credibility per rubric.