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Basé sur la classification professionnelle SOC
name AI Governance description Comprehensive AI risk management, EU AI Act compliance, and LLM usage governance license Apache-2.0 version 1.0 author Hack23 AB tags ["ai-governance","eu-ai-act","llm-security"] category security frameworks ["EU AI Act","ISO 27001:2022","NIST AI RMF"] related_policies ["AI_Policy.md"]
🤖 AI Governance Skill
🎯 Purpose
Enforce comprehensive AI risk management and EU AI Act compliance, based on AI Policy .
Key Principle: "AI systems require systematic risk management and human oversight."
📚 Scope
🤖 AI System Classification (EU AI Act risk levels)
🛡️ LLM Usage Governance (GitHub Copilot, ChatGPT)
👁️ Human Oversight Requirements
⚖️ Bias and Fairness Controls
📊 AI Risk Assessment
🔍 Transparency and Explainability
⚙️ Security Rules
MUST Requirements
ai_system_classification:
unacceptable_risk:
prohibited_systems:
- social_scoring: government_or_private_social_credit
- real_time_biometric: public_space_surveillance_without_warrant
- subliminal_manipulation: ai_that_manipulates_behavior
- exploit_vulnerabilities: ai_targeting_vulnerable_groups
action: never_develop_deploy_or_use
high_risk_systems:
examples:
- recruitment_ai: candidate_screening_or_selection
- credit_scoring: loan_approval_algorithms
- law_enforcement: predictive_policing_tools
requirements:
- risk_assessment: comprehensive_before_deployment
- data_quality: high_quality_representative_datasets
-
documentation:
technical_docs_and_user_manuals
-
human_oversight:
meaningful_human_review_required
-
transparency:
users_informed_of_ai_involvement
-
conformity_assessment:
third_party_audit_required
limited_risk_systems:
examples:
-
chatbots:
customer_service_bots
-
deepfakes:
synthetic_media_generation
requirements:
-
transparency_obligations:
users_informed_interacting_with_ai
-
disclosure:
ai_generated_content_labeled
minimal_risk_systems:
examples:
-
spam_filters:
email_filtering
-
ai_video_games:
entertainment_applications
-
github_copilot:
code_completion_assistance
requirements:
-
voluntary_codes:
follow_best_practices
-
basic_transparency:
disclose_ai_use_in_documentation
llm_usage_governance:
github_copilot:
approved_use:
-
code_completion:
autocomplete_and_suggestions
-
documentation:
generating_code_comments
-
test_generation:
creating_unit_test_scaffolding
security_controls:
-
code_review:
all_ai_generated_code_manually_reviewed
-
secret_scanning:
automated_pre_commit_hooks
-
license_compliance:
verify_suggested_code_licenses
-
no_sensitive_data:
never_input_customer_or_confidential_data
prohibited_use:
-
production_secrets:
entering_api_keys_or_passwords
-
customer_data:
inputting_personal_or_business_data
-
unreviewed_deployment:
deploying_ai_code_without_review
chatgpt_claude:
approved_use:
-
research:
general_information_gathering
-
brainstorming:
idea_generation_and_planning
-
documentation:
writing_assistance_for_public_docs
prohibited_use:
-
confidential_data:
client_information_or_trade_secrets
-
source_code:
proprietary_code_or_algorithms
-
personal_data:
customer_or_employee_information
human_oversight:
ai_decisions:
code_generation:
-
review_required:
all_copilot_suggestions_reviewed
-
testing:
ai_code_must_pass_automated_tests
-
security_scan:
sast_sca_checks_mandatory
business_decisions:
-
ai_as_advisor:
ai_provides_recommendations_only
-
human_final_decision:
ceo_makes_final_call
-
documentation:
record_ai_input_and_human_decision
MUST NOT Prohibitions prohibited_ai_practices:
- unclassified_systems: deploying_ai_without_risk_assessment
- no_human_oversight: fully_automated_critical_decisions
- biased_training_data: using_unrepresentative_datasets
- black_box_systems: unexplainable_ai_for_high_risk_decisions
- sensitive_data_training: training_ai_on_personal_data_without_consent
- bypassing_controls: using_personal_ai_for_business_without_approval
💡 Examples
Example 1: GitHub Copilot Secure Usage copilot_workflow:
development:
enable_copilot: vscode_github_copilot_extension
use_suggestions:
- code_completion: accept_for_boilerplate_code
- function_generation: review_logic_before_accepting
- test_scaffolding: verify_test_coverage_and_assertions
security_checks:
pre_commit:
- secret_scanning: gitleaks_pre_commit_hook
- code_review: manual_review_of_ai_suggestions
- license_check: verify_no_copyleft_violations
ci_cd_pipeline:
- sast: sonarcloud_static_analysis
- sca: dependabot_vulnerability_scanning
- test_coverage: minimum_80_percent_coverage
prohibited_inputs:
never_type:
- api_keys: aws_access_keys_database_passwords
- customer_data: email_addresses_names_personal_info
- proprietary_algorithms: trade_secret_business_logic
- production_configs: database_connection_strings
documentation:
- attribution: note_ai_assisted_code_in_comments
- review_notes: document_manual_changes_to_ai_suggestions
- lessons_learned: track_copilot_false_positives_for_training
Example 2: AI Risk Assessment Process ai_risk_assessment:
system_identification:
name: recruitment_candidate_screening_tool
classification: HIGH_RISK_per_eu_ai_act
trigger: involves_employment_decisions
risk_analysis:
potential_harms:
- discrimination: algorithm_may_have_gender_or_age_bias
- privacy: processes_personal_data_from_resumes
- transparency: candidates_unaware_of_ai_involvement
likelihood: MEDIUM
impact: HIGH
overall_risk: HIGH
risk_mitigation:
technical_measures:
- bias_testing: fairness_metrics_on_diverse_test_set
- explainability: shap_or_lime_for_decision_explanations
- data_quality: representative_training_dataset
organizational_measures:
- human_review: recruiter_reviews_all_ai_recommendations
- transparency: candidates_informed_of_ai_use
- appeal_process: candidates_can_request_human_review
- audit: annual_third_party_fairness_audit
compliance_obligations:
eu_ai_act:
- risk_management_system: implemented_and_documented
- data_governance: high_quality_training_data_verified
- technical_documentation: available_for_authorities
- conformity_assessment: third_party_audit_planned
gdpr:
- lawful_basis: legitimate_interest_assessment
- data_minimization: only_relevant_resume_data_processed
- automated_decision: human_review_prevents_art_22_violation
approval:
decision: APPROVED_WITH_CONDITIONS
approver: CEO
date: 2026_02_10
review_date: 2026_08_10_semi_annual
conditions:
- quarterly_bias_testing
- monthly_human_override_rate_monitoring
- annual_external_audit
Example 3: Prohibited AI Use (Corrected) incorrect_chatgpt_use:
prompt: "Review this customer database schema and suggest optimizations"
attached: production_database_dump_with_customer_emails
risk: exposing_personal_data_to_third_party_ai
compliant_chatgpt_use:
data_anonymization:
- remove_personal_data: replace_emails_with_placeholders
- sanitize_schema: generic_field_names_only
- sample_data: synthetic_test_data_not_production
prompt: "Review this anonymized schema and suggest optimizations"
attached: sanitized_schema_with_no_real_data
verification:
- no_personal_data: verified_before_submission
- no_secrets: no_connection_strings_or_credentials
- documented: ai_consultation_logged_in_project_notes
🔗 Integration Skills: owasp-llm-security, data-classification, privacy-policy
Frameworks: EU AI Act, NIST AI RMF, ISO 42001 (draft)
📋 Document Control
Version: 1.0 | Updated: 2026-02-10License: Apache-2.0Classification: 
