Market
AI law in PE
4 binding provisions TwinEthos encodes that reach PE: 4 in force, 0 enacted but not yet applying. Start from the guards to add.
Informational data, not legal advice. Summaries and rules have not been reviewed by a lawyer: always verify official law text for decisions. A suggested guard is intended to address each rule; adding it is not a statement of compliance to that law.
The guards that cover the most here
42 guards address 57 items across 1 jurisdiction with binding law: 4 binding law in force, 0 enacted but not yet applying, 29 standards and frameworks, 24 TwinEthos recommended guardrails.
Adverse AI decision without explanation/appeal
Send each adverse AI-assisted decision with its main reasons and the AI's role, plus a way to correct data and appeal to a human who can change the outcome.
Addresses 4 items: 1 binding law in force · 2 standards · 1 recommended guardrail
Law in force in PE.
Biometric categorisation of sensitive traits
Remove any model, prompt, or label set that infers race, political opinion, union membership, religion or beliefs, sex life, or sexual orientation from biometric data.
Addresses 1 item: 1 binding law in force
Law in force in PE.
Consequential AI decision without consumer notice
Send the person an AI-use notice on the decision path, before or when an AI system makes or substantially factors a consequential decision about them, and record its delivery.
Addresses 1 item: 1 binding law in force
Law in force in PE.
High-impact AI without risk management, explanations, and human oversight
Put human supervision and a per-decision explanation record between high-impact model output and the action it triggers, backed by a documented risk-management plan.
Addresses 1 item: 1 binding law in force
Law in force in PE.
AI chat interaction without disclosure
Show an AI-identity notice at or before the first assistant turn, in the UI or as the opening message, and answer truthfully when asked if it is a bot.
Addresses 3 items: 2 standards · 1 recommended guardrail
Untrusted content influences instructions or tools
Keep fetched, retrieved, and tool-returned content out of the system prompt, pass it as delimited data, and restrict which tools a turn holding that content can call.
Addresses 3 items: 2 standards · 1 recommended guardrail
Agent actions not traceable to identity and owner
Give each agent its own credential and a registry entry naming an accountable owner, and log every tool action with agent_id, owner, action, target, and timestamp.
Addresses 2 items: 1 standard · 1 recommended guardrail
Agent high-impact action without human approval
Classify agent tools by impact and route every high-impact or irreversible call through an enforced human-approval step in the executor, with the decision logged.
Addresses 2 items: 1 standard · 1 recommended guardrail
AI usage, agent steps, and spend not bounded
Cap agent steps and output tokens on every model call, set per-key and per-project budgets with usage alerts, and issue scoped, expiring model keys.
Addresses 2 items: 1 standard · 1 recommended guardrail
GenAI in consequential decisions without confabulation/output-validation controls
Validate GenAI output against a schema and its cited sources, and send unverifiable claims to review, before it drives a consequential decision or record.
Addresses 2 items: 1 standard · 1 recommended guardrail
The top 10 of 42; the build plan ranks all of them and lets you narrow by AI feature.
By AI feature
Plans for one feature in PE:
- Chat or assistant
- Agents that use tools or take actions
- Decisions about people (hiring, credit, insurance, health)
- Classification, scoring or biometrics
Laws
Coming into force
- : Explain high-risk AI decisions that affect human rights, with the key criteria and factors, in accessible language (Peru, Regulation of Law 31814 Art. 25.3) (PE)
- : Tell users in advance what a high-risk AI system is for, what it does and what decisions it can take (Peru, Regulation of Law 31814 Art. 25.1-25.2) (PE)
- : Keep a record of how a high-risk AI system works and people able to stop, correct or invalidate its decisions (Peru, Regulation of Law 31814 Art. 31.1, 31.4) (PE)
- : Explain high-risk AI decisions that affect human rights, with the key criteria and factors, in accessible language (Peru, Regulation of Law 31814 Art. 25.3) (PE)
- : Tell users in advance what a high-risk AI system is for, what it does and what decisions it can take (Peru, Regulation of Law 31814 Art. 25.1-25.2) (PE)
- : Keep a record of how a high-risk AI system works and people able to stop, correct or invalidate its decisions (Peru, Regulation of Law 31814 Art. 31.1, 31.4) (PE)
- : Explain high-risk AI decisions that affect human rights, with the key criteria and factors, in accessible language (Peru, Regulation of Law 31814 Art. 25.3) (PE)
- : Tell users in advance what a high-risk AI system is for, what it does and what decisions it can take (Peru, Regulation of Law 31814 Art. 25.1-25.2) (PE)
- : Keep a record of how a high-risk AI system works and people able to stop, correct or invalidate its decisions (Peru, Regulation of Law 31814 Art. 31.1, 31.4) (PE)
Informational data, not legal advice. Summaries are TwinEthos's own words and rules have not been reviewed by a lawyer: check the official text before relying on any of it. A guard addresses an item; adding it is not a statement that your code meets any law.