Ethyka robotics.md: A Verifiable Ethics-as-Code Specification for Physical AI Agents

Roboethics has produced mature bodies of principles — human well-being, responsibility, transparency — but these remain high-level statements that are difficult to verify on a deployed robot. Meanwhile, foundation-model-enabled robots introduce a new failure mode: an agent whose plan can be manipulated through natural-language or network inputs into physically unsafe behavior. We present Ethyka robotics.md, an open "ethics-as-code" specification that addresses this gap for physical AI agents. The specification expresses eleven rules (ROB-01..11) — safety-first stopping, actuation limits, stop and override, movement honesty, sensor privacy, resistance to external manipulation, safe separation, operational envelope, forensic logging, safe exploration, and continuous hazard analysis — as machine-readable clauses with stable identifiers, measurable parameters, severities, and one adversarial test per rule. Numerical limits are not asserted by the specification; they remain parameters bound to the governing standards (ISO 10218, ISO/TS 15066, IEC 61508, ISO 13855, ISO 21448). A generation pipeline validates declared values against a JSON Schema and emits runtime guardrails, system prompts, a test suite, and a traceability manifest, with severity-based deployment gating. We describe the design, its grounding in the safety literature, and its limitations as a proposal that complements — not replaces — certification.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-28
DOI
https://doi.org/10.5281/zenodo.22141154
Primary Topic
Adversarial Robustness in Machine Learning
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Ethyka robotics.md: A Verifiable Ethics-as-Code Specification for Physical AI Agents

Pedro Diezma
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
preprint

Ethyka robotics.md: A Verifiable Ethics-as-Code Specification for Physical AI Agents

Pedro Diezma
preprint en

Abstract

Roboethics has produced mature bodies of principles — human well-being, responsibility, transparency — but these remain high-level statements that are difficult to verify on a deployed robot. Meanwhile, foundation-model-enabled robots introduce a new failure mode: an agent whose plan can be manipulated through natural-language or network inputs into physically unsafe behavior. We present Ethyka robotics.md, an open "ethics-as-code" specification that addresses this gap for physical AI agents. The specification expresses eleven rules (ROB-01..11) — safety-first stopping, actuation limits, stop and override, movement honesty, sensor privacy, resistance to external manipulation, safe separation, operational envelope, forensic logging, safe exploration, and continuous hazard analysis — as machine-readable clauses with stable identifiers, measurable parameters, severities, and one adversarial test per rule. Numerical limits are not asserted by the specification; they remain parameters bound to the governing standards (ISO 10218, ISO/TS 15066, IEC 61508, ISO 13855, ISO 21448). A generation pipeline validates declared values against a JSON Schema and emits runtime guardrails, system prompts, a test suite, and a traceability manifest, with severity-based deployment gating. We describe the design, its grounding in the safety literature, and its limitations as a proposal that complements — not replaces — certification.

Zenodo (CERN European Organization for Nuclear Research)
Toray (United States) (US)
Peace, Justice and strong institutions
Adversarial Robustness in Machine Learning
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Ethyka robotics.md: A Verifiable Ethics-as-Code Specification for Physical AI Agents — Pedro Diezma · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS