AI Output Indicator par Libor Benes

AI Output Indicator is a Firefox sidebar extension that uses deterministic, rule-based analysis to identify governance-relevant linguistic indicators in AI-generated text.

Critical Distinction: This tool highlights GOVERNANCE INDICATORS in AI output, it does NOT verify compliance or correctness. Results are heuristic signals for human review, not definitive judgments.

Purpose:
Analyze AI-to-human communication through five governance categories:
• Obligation (AI-stated requirements).
• Prohibition (AI-stated restrictions).
• Risk (danger/harm language).
• Uncertainty (ambiguity).
• Policy (governance references).

Designed and Built for:
• AI governance professionals monitoring system outputs.
• Risk managers assessing AI's safety communication.
• Compliance officers verifying policy acknowledgments.
• Auditors reviewing AI transparency.

Privacy-First Design:
• 100% offline.
• No data collection.
• No tracking.
• Deterministic pattern matching.
• Unlike cloud-based tools, it keeps sensitive AI outputs completely private while providing professional-grade analysis.

AI Output As Part of a Comprehensive AI Analysis Toolkit:
AI Output Indicator is the third component in a specialized toolkit designed for systematic analysis of AI-related communication. Together with its companion tools, it enables end-to-end review of human-AI interaction:

The Complete AI Communication Workflow:
• AI Prompt Linter → Analyzes prompt structure & clarity.
Purpose: Optimize how humans write instructions to AI systems.
Focus: Prompt engineering, clarity checking, instructional quality.

• AI Intent Indicator → Analyzes directive patterns in prompts.
Purpose: Understand what types of instructions humans give to AI.
Focus: Directive strength, compliance review, security analysis.
Key distinction: Highlights indicators, does NOT infer intent.

• AI Output Indicator → Analyzes governance language in AI responses.
Purpose: Assess how AI communicates about risks, policies, and compliance.
Focus: Governance awareness, risk communication, policy alignment.
Key distinction: Highlights indicators, does NOT verify compliance or correctness.

Why Three Specialized Tools:
Each tool serves a distinct professional need in the AI communication lifecycle:
• Before interaction: Use AI Prompt Linter to write clear, effective instructions.
• During instruction design: Use AI Intent Indicator to analyze directive patterns.
• After AI responds: Use AI Output Indicator to review governance communication.

Practical Workflow Example: Compliance Review
A financial institution ensuring responsible AI deployment:
• First, optimize the prompt with AI Prompt Linter:
"Provide investment advice" → "Provide educational information about investment options with appropriate risk disclosures".

• Then, analyze directive patterns with AI Intent Indicator:
Highlights obligations ("must include disclosures"), warnings ("risks"), prohibitions ("must not guarantee returns").

• Finally, review AI responses with AI Output Indicator:
Verifies AI acknowledges risks, cites policies, uses appropriate uncertainty language.

Shared Design Philosophy:
All three tools share the same core principles:
• 100% offline operation - No data leaves your browser.
• Deterministic pattern matching - No AI inference, same input → same output.
• Transparent rules - All patterns explicitly listed.
• Professional focus - Designed for critical review, not casual use.
• Privacy-first - Built for sensitive organizational environments.

Choosing the Right Tool:
• For prompt engineering: Start with AI Prompt Linter, then use AI Intent Indicator.
• For compliance teams: Use AI Intent Indicator for prompts, AI Output Indicator for responses.
• For security review: AI Intent Indicator identifies strong directives, AI Output Indicator assesses AI's security awareness.
• For governance monitoring: Focus on AI Output Indicator to track AI's policy communication.

This toolkit enables organizations to systematically review, optimize, and govern their AI communications with professional-grade tools that respect privacy and provide transparent, reproducible analysis.