{ "file_id": "11_vertical_hr_workforce_management", "version": "2026.03.16", "schema_version": "2.2", "status": "Production Authority", "last_authoritative_sync": "2026-03-16", "description": "Human resources fields cover recruitment, employment decisions, workforce planning, learning, payroll, and employee services. Use the vocabulary to record the purpose and outcome of a workflow.", "vertical_metadata": { "vertical_key": "hr_workforce", "industry": "Human Resources & Workforce Management", "primary_standards": [ "EU AI Act (2024/1689) Annex III para 4, High-risk AI in employment, worker management, and access to self-employment", "EU AI Act Article 5(1)(b), Prohibition on AI exploiting vulnerabilities of workers", "EU AI Act Article 10, Training data governance and bias mitigation for high-risk AI", "Uniform Guidelines on Employee Selection Procedures, Selection-validation reference; agency applicability requires review", "EEOC Technical Assistance on AI and Algorithmic Fairness (2023)", "EEOC Strategic Enforcement Plan FY2024-2028, AI-enabled discrimination as enforcement priority", "NYC Local Law 144 (2021), Automated Employment Decision Tools (AEDT), effective July 5, 2023", "NYC Local Law 144 Rules (DCWP), Bias audit and notice requirements", "Illinois Artificial Intelligence Video Interview Act (820 ILCS 42), Applicant notice, explanation, consent, and specified demographic reporting", "Colorado SB 26-189, Automated decision-making technology used in consequential decisions; requirements begin January 1, 2027", "California FEHA employment regulations on automated-decision systems; effective October 1, 2025", "EU GDPR Article 22, Automated individual decision-making including HR profiling", "EU General Data Protection Regulation, Employment data processing (Recital 155; Article 88)", "EU Directive 2019/1152, Transparent and Predictable Working Conditions", "EU Directive 2023/970, Pay transparency; national transposition deadline June 7, 2026, with phased employer reporting", "EU Directive 2002/14/EC, Information and Consultation of Employees (works council AI consultation)", "European Works Council Directive 2009/38/EC, Transnational information and consultation; revised by Directive (EU) 2025/2450", "Title VII of the Civil Rights Act (42 USC § 2000e), Prohibited employment discrimination", "Age Discrimination in Employment Act (ADEA 29 USC § 621), Age discrimination in hiring and employment", "Americans with Disabilities Act (ADA Title I), Employment discrimination; AI assessment accommodations", "Equal Pay Act (29 USC § 206(d)), Compensation equity", "NLRA (29 USC § 151), National Labour Relations Act; employee monitoring and AI surveillance", "WARN Act (29 USC § 2101), Worker Adjustment and Retraining Notification; AI-driven layoff decisions", "FLSA (29 USC § 201), Fair Labour Standards Act; AI-driven scheduling and wage calculation", "OSHA 29 CFR Part 1904, Recordkeeping and reporting occupational injuries and illnesses", "ISO 30414:2018, Human capital reporting guidelines", "Society for Industrial and Organizational Psychology (SIOP) Principles for the Validation and Use of Personnel Selection Procedures (2018)" ], "primary_source_labels": { "https://employment-social-affairs.ec.europa.eu/policies-and-activities/rights-work/labour-law/employee-involvement/european-works-councils_en": "European Commission: European Works Councils", "https://leg.colorado.gov/bills/SB26-189": "Colorado SB 26-189", "https://calcivilrights.ca.gov/civilrightscouncil/rulemaking-actions/": "California Civil Rights Council: rulemaking actions", "https://www.eeoc.gov/ai-and-algorithmic-fairness": "EEOC: AI and algorithmic fairness", "https://rules.cityofnewyork.us/rule/automated-employment-decision-tools/": "New York City: automated employment decision tools", "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689": "EU Artificial Intelligence Act", "https://gdpr-info.eu/art-22-gdpr/": "GDPR Article 22: automated decisions (GDPR-Info)", "https://www.dol.gov/agencies/whd/flsa": "U.S. Department of Labor: wages and the FLSA", "https://www.osha.gov/recordkeeping": "OSHA: injury and illness recordkeeping", "https://www.iso.org/standard/69030.html": "ISO 30414:2018: human capital reporting" }, "primary_source_urls": [ "https://employment-social-affairs.ec.europa.eu/policies-and-activities/rights-work/labour-law/employee-involvement/european-works-councils_en", "https://leg.colorado.gov/bills/SB26-189", "https://calcivilrights.ca.gov/civilrightscouncil/rulemaking-actions/", "https://www.eeoc.gov/ai-and-algorithmic-fairness", "https://rules.cityofnewyork.us/rule/automated-employment-decision-tools/", "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689", "https://gdpr-info.eu/art-22-gdpr/", "https://www.dol.gov/agencies/whd/flsa", "https://www.osha.gov/recordkeeping", "https://www.iso.org/standard/69030.html" ], "otel_namespace": "hr", "opa_namespace": "data.hr", "agentic_ai_deployment_context": "For a hiring workflow, distinguish screening recommendations from employment decisions. Record who reviewed the recommendation and whether the application completed the approved action.", "key_regulatory_risk_note": "Assess employment, privacy, notice, and accessibility requirements for the actual tool and jurisdiction. A catalog value or completed review does not prove that a decision was fair." }, "subdomains": [ { "subdomain": "Recruitment & Applicant Tracking", "description": "Fields for recruitment stages, screening, and candidate notices. Map the workflow to the employment and AI requirements that apply in its jurisdiction.", "relevant_standards": [ "EU AI Act (2024/1689) Annex III para 4(a), AI in recruitment and selection is high-risk", "NYC Local Law 144 (2021), AEDT bias audit and notice requirements", "Uniform Guidelines on Employee Selection Procedures, Selection-validation reference", "EEOC Technical Assistance on AI and Algorithmic Fairness (2023)", "SIOP Principles for the Validation and Use of Personnel Selection Procedures (2018)", "Colorado SB 26-189, Covered automated decision-making technology; requirements begin January 1, 2027", "California FEHA employment regulations on automated-decision systems; effective October 1, 2025" ], "categories": [ { "enum_name": "RecruitmentStage", "label": "Recruitment Stage", "otel_attribute": "hr.recruitment.stage", "opa_policy_path": "data.hr.recruitment.stage", "rego_input_key": "hr_recruitment_stage", "stability": "stable", "description": "Records the candidate’s recruitment stage, from screening to assessment. Use the stage with the tool’s purpose and jurisdiction to select applicable rules.", "permitted_values": [ "job_posted", "application_received", "resume_screening", "ai_assessment", "phone_screen", "ai_video_interview_analysis", "interview_scheduled", "interview_completed", "reference_check", "background_check", "offer_extended", "offer_accepted", "offer_declined", "hired", "rejected", "withdrawn", "pipeline_hold" ], "value_labels": { "job_posted": "Job Posted", "application_received": "Application Received", "resume_screening": "Resume Screening", "ai_assessment": "AI Assessment", "phone_screen": "Phone Screen", "ai_video_interview_analysis": "AI Video Interview Analysis", "interview_scheduled": "Interview Scheduled", "interview_completed": "Interview Completed", "reference_check": "Reference Check", "background_check": "Background Check", "offer_extended": "Offer Extended", "offer_accepted": "Offer Accepted", "offer_declined": "Offer Declined", "hired": "Hired", "rejected": "Rejected", "withdrawn": "Withdrawn", "pipeline_hold": "Pipeline Hold" }, "code_definitions": { "resume_screening": "AI reviewing and scoring resumes against job requirements; AEDT if output substantially assists employment decision per NYC LL144 definition", "ai_assessment": "AI administers or scores a cognitive, personality, or skills assessment. Evaluate job relevance, accessibility, and the requirements that apply to the selection process.", "ai_video_interview_analysis": "AI evaluates a recorded interview. For Illinois-based positions, applicants must receive an explanation and consent before the interview. Other restrictions depend on the analysis used.", "pipeline_hold": "Candidate is qualified but no current opening; AI-managed talent pool for future consideration" }, "regulatory_mappings": { "eu_ai_act_annex3_4a": "EU AI Act Annex III paragraph 4(a) covers high-risk recruitment and selection uses. The high-risk requirements apply from December 2, 2027, subject to scope and transitional provisions.", "nyc_ll144": "NYC Local Law 144, AEDT use at 'resume_screening', 'ai_assessment', and 'ai_video_interview_analysis' stages requires prior bias audit and candidate notice at least 10 business days before use", "eeoc_title_vii": "Title VII governs discriminatory employment practices. Assess the selection procedure, job relevance, and applicable legal standard; not every assessment requires the same validation study.", "illinois_aivia": "For Illinois-based positions, notify applicants, explain the AI analysis, and obtain their consent before the interview. Solely AI-based selection for in-person interviews also triggers annual demographic reporting under Section 20." }, "use_case": "Example company rule: check the required audit and notice before screening or assessment. Stop the agent when either requirement is unmet.", "source": "EU AI Act Annex III para 4; NYC Local Law 144 DCWP Rules; EEOC Uniform Guidelines 29 CFR Part 1607", "source_url": "https://www.eeoc.gov/ai-and-algorithmic-fairness" }, { "enum_name": "AIEmploymentDecisionType", "label": "AI Employment Decision Type", "otel_attribute": "hr.ai_decision.type", "opa_policy_path": "data.hr.ai_decision.type", "rego_input_key": "hr_ai_decision_type", "stability": "stable", "description": "Records the employment decision that AI assists or makes. Assess EU AI Act scope from the intended use and Article 6, not the catalog value alone. NYC Local Law 144 has a separate scope for covered hiring and promotion tools.", "permitted_values": [ "resume_ranking", "candidate_screening_pass_fail", "interview_scheduling_prioritisation", "ai_video_interview_scoring", "skills_assessment_scoring", "performance_evaluation_ai_generated", "performance_rating_calibration", "promotion_recommendation", "succession_planning_identification", "compensation_adjustment_recommendation", "pay_equity_gap_identification", "termination_risk_flag", "involuntary_separation_recommendation", "workforce_reduction_targeting", "task_allocation_assignment", "shift_scheduling_optimisation", "learning_path_recommendation", "attrition_flight_risk_score" ], "value_labels": { "resume_ranking": "Resume Ranking", "candidate_screening_pass_fail": "Candidate Screening Pass Fail", "interview_scheduling_prioritisation": "Interview Scheduling Prioritisation", "ai_video_interview_scoring": "AI Video Interview Scoring", "skills_assessment_scoring": "Skills Assessment Scoring", "performance_evaluation_ai_generated": "Performance Evaluation AI Generated", "performance_rating_calibration": "Performance Rating Calibration", "promotion_recommendation": "Promotion Recommendation", "succession_planning_identification": "Succession Planning Identification", "compensation_adjustment_recommendation": "Compensation Adjustment Recommendation", "pay_equity_gap_identification": "Pay Equity Gap Identification", "termination_risk_flag": "Termination Risk Flag", "involuntary_separation_recommendation": "Involuntary Separation Recommendation", "workforce_reduction_targeting": "Workforce Reduction Targeting", "task_allocation_assignment": "Task or shift allocation", "shift_scheduling_optimisation": "Shift Scheduling Optimisation", "learning_path_recommendation": "Learning Path Recommendation", "attrition_flight_risk_score": "Attrition Flight Risk Score" }, "code_definitions": { "candidate_screening_pass_fail": "AI producing a binary pass/fail or tiered ranking substantially assisting a decision to proceed or not proceed with a candidate; core NYC LL144 AEDT definition", "termination_risk_flag": "AI flags a possible termination concern for review. Assess the system’s intended role in employment decisions under Annex III paragraph 4(b).", "workforce_reduction_targeting": "AI identifying employees for inclusion in a reduction-in-force; WARN Act assessment required for large-scale AI-assisted layoffs", "task_allocation_assignment": "AI assigns tasks, shifts, or work. Annex III paragraph 4(b) covers task allocation based on individual behaviour, personal traits, or characteristics." }, "regulatory_mappings": { "eu_ai_act_annex3_4a": "Annex III paragraph 4(a) covers recruitment and selection; paragraph 4(b) covers specified work-related decisions, task allocation, and performance monitoring. Apply Article 6 classification criteria.", "nyc_ll144": "NYC LL144, 'resume_ranking', 'candidate_screening_pass_fail', 'ai_video_interview_scoring', 'skills_assessment_scoring' are AEDTs requiring annual bias audit", "eeoc_adea": "ADEA, 'attrition_flight_risk_score', 'workforce_reduction_targeting', and 'termination_risk_flag' must not produce age-based disparate impact on workers 40+", "warn_act": "WARN Act, 'workforce_reduction_targeting' triggering 50+ separations at a single site within 30 days may require 60-day advance notice", "eu_pay_transparency": "Directive (EU) 2023/970 phases in employer reporting from June 2027 and June 2031 according to workforce size. Check national requirements." }, "use_case": "Example company rule: route termination and workforce-reduction recommendations to HR and legal reviewers. Stop the agent from communicating a decision until they approve it.", "source": "EU AI Act Annex III para 4; NYC Local Law 144 DCWP Rules; EEOC Strategic Enforcement Plan FY2024-2028", "source_url": "https://rules.cityofnewyork.us/rule/automated-employment-decision-tools/" }, { "enum_name": "CandidateNoticeStatus", "label": "Candidate Notice Status", "otel_attribute": "hr.recruitment.candidate_notice_status", "opa_policy_path": "data.hr.recruitment.candidate_notice_status", "rego_input_key": "hr_recruitment_candidate_notice_status", "stability": "stable", "description": "Tracks candidate notice delivery, waiting periods, and requests for an alternative process. Apply the notice requirements for the tool and jurisdiction.", "permitted_values": [ "notice_not_required", "notice_pending_delivery", "notice_delivered_window_running", "notice_window_elapsed_aedt_permitted", "alternative_process_requested", "alternative_process_in_progress", "notice_failed_delivery" ], "value_labels": { "notice_not_required": "Notice not Required", "notice_pending_delivery": "Notice Pending Delivery", "notice_delivered_window_running": "Notice Delivered Window Running", "notice_window_elapsed_aedt_permitted": "Notice Window Elapsed Aedt Permitted", "alternative_process_requested": "Alternative Process Requested", "alternative_process_in_progress": "Alternative Process in Progress", "notice_failed_delivery": "Notice Failed Delivery" }, "code_definitions": { "notice_delivered_window_running": "Notice was delivered, but the applicable waiting period has not ended. NYC Local Law 144 requires ten business days for covered notices.", "notice_window_elapsed_aedt_permitted": "The notice waiting period has ended. Other applicable audit, access, and policy checks still govern use of the tool.", "alternative_process_requested": "The candidate requested an alternative selection process. Route the request according to company policy and applicable accommodation requirements." }, "regulatory_mappings": { "nyc_ll144": "NYC Local Law 144 requires covered notices ten business days before use and instructions for requesting an alternative process or accommodation. It does not itself require an alternative process.", "colorado_ai_act": "Colorado SB 26-189 requires notice at interaction with covered automated decision-making technology and disclosure after an adverse consequential decision. Requirements begin January 1, 2027." }, "use_case": "Example company rule: stop covered screening while required notice is pending or its waiting period is running. Route alternative-process requests to HR before screening continues.", "source": "NYC Local Law 144 DCWP Rules § 20-871; Colorado SB 26-189", "source_url": "https://rules.cityofnewyork.us/rule/automated-employment-decision-tools/" }, { "enum_name": "RequisitionApprovalStatus", "label": "Requisition Approval Status", "otel_attribute": "hr.recruitment.requisition_status", "opa_policy_path": "data.hr.recruitment.requisition_status", "rego_input_key": "hr_recruitment_requisition_status", "stability": "proposed", "description": "Tracks a job requisition through approval and closure. Use its status to control when an agent can contact or assess candidates.", "permitted_values": [ "draft", "pending_hm_approval", "pending_finance_approval", "pending_dei_review", "approved_open", "on_hold", "filled", "cancelled" ], "value_labels": { "draft": "Draft", "pending_hm_approval": "Pending HM Approval", "pending_finance_approval": "Pending Finance Approval", "pending_dei_review": "Pending DEI Review", "approved_open": "Approved Open", "on_hold": "On Hold", "filled": "Filled", "cancelled": "Cancelled" }, "use_case": "Example company rule: require an approved, open requisition before candidate outreach or interview progression. Pending approvals stop the action.", "source": "SHRM hiring process framework; ATS platform requisition workflows", "source_url": "https://www.shrm.org/" } ] }, { "subdomain": "Bias Audit & Algorithmic Fairness", "description": "Fields for audit outcomes, disparity analysis, and remediation. Record the finding separately from the decision to pause or continue a workflow.", "relevant_standards": [ "Uniform Guidelines on Employee Selection Procedures, Four-fifths comparison method; not a legal determination", "EEOC Technical Assistance on AI and Algorithmic Fairness (2023)", "NYC Local Law 144 DCWP Bias Audit Rules (effective July 5, 2023)", "EU AI Act Article 10, Training data governance and bias mitigation for high-risk AI", "EU AI Act Article 9, Risk management system including bias testing", "SIOP Principles, Validity evidence requirements for personnel selection", "ISO/IEC TR 24027:2021, Bias in AI systems and AI aided decision making" ], "categories": [ { "enum_name": "BiasAuditOutcome", "label": "Bias Audit Outcome", "otel_attribute": "hr.bias_audit.outcome", "opa_policy_path": "data.hr.bias_audit.outcome", "rego_input_key": "hr_bias_audit_outcome", "stability": "stable", "description": "Records an independent employment-tool bias audit’s outcome. For covered NYC use, the audit must be within the preceding year. Company policy determines how findings affect further use, alongside applicable anti-discrimination requirements.", "permitted_values": [ "compliant_no_disparate_impact", "compliant_with_conditions", "disparate_impact_detected_below_threshold", "disparate_impact_detected_above_threshold", "requires_remediation", "remediation_in_progress", "remediation_completed_reaudit_required", "audit_failed_methodology", "audit_not_yet_conducted", "audit_expired_renewal_required" ], "value_labels": { "compliant_no_disparate_impact": "Compliant No Disparate Impact", "compliant_with_conditions": "Compliant with Conditions", "disparate_impact_detected_below_threshold": "Disparate Impact Detected Below Threshold", "disparate_impact_detected_above_threshold": "Disparate Impact Detected Above Threshold", "requires_remediation": "Requires Remediation", "remediation_in_progress": "Remediation in Progress", "remediation_completed_reaudit_required": "Remediation Completed Reaudit Required", "audit_failed_methodology": "Audit Failed Methodology", "audit_not_yet_conducted": "Audit not Yet Conducted", "audit_expired_renewal_required": "Audit Expired Renewal Required" }, "code_definitions": { "compliant_no_disparate_impact": "The audit found no disparity meeting the selected review threshold. This result alone does not establish lawful use or absence of discrimination.", "compliant_with_conditions": "The audit recommends conditions for continued use, such as monitoring. Record the conditions and the responsible reviewer’s decision.", "disparate_impact_detected_above_threshold": "A measured disparity crossed the selected review threshold. Investigate the finding; the four-fifths rule is an indicator, not a legal determination.", "audit_expired_renewal_required": "NYC LL144 requires annual audit; prior audit results are more than 12 months old; AEDT must be suspended until new audit is completed", "audit_failed_methodology": "The audit could not support a valid conclusion. Record the reason and obtain a valid audit before covered use." }, "regulatory_mappings": { "nyc_ll144": "Covered use requires an independent bias audit within the preceding year and publication of its summary. Local Law 144 prescribes no particular response to audit results.", "eeoc_uniform_guidelines": "The four-fifths comparison is an indicator from the Uniform Guidelines, not a legal determination. Review the applicable agency rules and the statistical context.", "eu_ai_act_art10": "EU AI Act Article 10, Training, validation, and testing data must be examined for biases; bias detection findings must inform risk management system" }, "use_case": "Example company rule: stop covered screening when the required audit is missing or expired. Send threshold findings to a reviewer before allowing further use.", "source": "NYC Local Law 144 DCWP Rules; EEOC Uniform Guidelines 29 CFR Part 1607; EU AI Act Article 10", "source_url": "https://rules.cityofnewyork.us/rule/automated-employment-decision-tools/" }, { "enum_name": "AdverseImpactProtectedClass", "label": "Adverse Impact Protected Class", "otel_attribute": "hr.bias_audit.protected_class", "opa_policy_path": "data.hr.bias_audit.protected_class", "rego_input_key": "hr_bias_audit_protected_class", "stability": "stable", "description": "Identifies a characteristic used to compare selection outcomes. Choose categories for the applicable audit and legal scope; this list does not authorize collection of personal data.", "permitted_values": [ "race_ethnicity", "sex_gender", "age_40_plus", "disability_status", "national_origin", "religion", "pregnancy_status", "sexual_orientation", "gender_identity", "veteran_status", "genetic_information" ], "value_labels": { "race_ethnicity": "Race Ethnicity", "sex_gender": "Sex Gender", "age_40_plus": "Age 40 Plus", "disability_status": "Disability Status", "national_origin": "National Origin", "religion": "Religion", "pregnancy_status": "Pregnancy Status", "sexual_orientation": "Sexual Orientation", "gender_identity": "Gender Identity", "veteran_status": "Veteran Status", "genetic_information": "Genetic Information" }, "regulatory_mappings": { "nyc_ll144_mandatory": "NYC LL144 requires bias audit to calculate impact ratio by sex, race/ethnicity category at minimum", "title_vii": "Title VII, race_ethnicity, sex_gender, national_origin, religion protected", "adea": "ADEA, age_40_plus protected", "ada": "ADA, disability_status protected", "eu_ai_act_art10": "EU AI Act Article 10 and EU anti-discrimination directives, all categories applicable in EU deployment" }, "source": "NYC LL144 DCWP Rules; EEOC Uniform Guidelines 29 CFR Part 1607 § 4; Title VII, ADEA, ADA; EU Equal Treatment Directives", "source_url": "https://www.eeoc.gov/laws/guidance/questions-and-answers-clarify-and-provide-common-interpretation-uniform-guidelines" }, { "enum_name": "FairnessMitigationTechnique", "label": "Fairness Mitigation Technique", "otel_attribute": "hr.bias_audit.mitigation_technique", "opa_policy_path": "data.hr.bias_audit.mitigation_technique", "rego_input_key": "hr_bias_audit_mitigation_technique", "stability": "proposed", "description": "Records a technique used to address a measured disparity in an HR model. Evaluate its effect on job relevance and outcomes before approving the change.", "permitted_values": [ "reweighting_training_data", "resampling_underrepresented_groups", "adversarial_debiasing", "calibrated_equalised_odds", "threshold_adjustment_per_group", "feature_removal_proxy_variables", "model_selection_fairness_constrained", "human_in_loop_override_sampling", "pre_employment_test_adverse_impact_redesign" ], "value_labels": { "reweighting_training_data": "Reweighting Training Data", "resampling_underrepresented_groups": "Resampling Underrepresented Groups", "adversarial_debiasing": "Adversarial Debiasing", "calibrated_equalised_odds": "Calibrated Equalised Odds", "threshold_adjustment_per_group": "Threshold Adjustment Per Group", "feature_removal_proxy_variables": "Feature Removal Proxy Variables", "model_selection_fairness_constrained": "Model Selection Fairness Constrained", "human_in_loop_override_sampling": "Human-in-the-Loop Override Sampling", "pre_employment_test_adverse_impact_redesign": "Pre-Employment Test Adverse Impact Redesign" }, "regulatory_mappings": { "eeoc_uniform_guidelines": "Uniform Guidelines materials discuss validation and alternative selection procedures. Check the applicable agency rules and legal standard before treating a technique as required or sufficient.", "eu_ai_act_art10": "EU AI Act Article 10(2)(f), Training data must be examined for possible biases; mitigation technique and its effectiveness must be documented" }, "use_case": "AI model development agent records the mitigation technique applied during model development. This record feeds the EU AI Act Article 10 technical documentation and the bias audit evidence package submitted to the independent auditor.", "source": "EU AI Act Article 10; EEOC Uniform Guidelines; NIST AI RMF BIAS-P1; ISO/IEC TR 24027:2021", "source_url": "https://csrc.nist.gov/publications/detail/ai/100-1/final" } ] }, { "subdomain": "Performance Management & Employee Monitoring", "description": "Covers EU AI Act Annex III para 4, GDPR Article 88, and NLRA enumerations for AI-driven performance evaluation, continuous monitoring, and employee surveillance governance. These are the most contentious HR AI applications from a worker rights perspective.", "relevant_standards": [ "EU AI Act Annex III paragraph 4(b), Specified work-related decisions, task allocation, and performance monitoring", "EU GDPR Article 88, Processing of employee personal data; member state implementing laws", "NLRA (29 USC § 151), Employee monitoring must not chill protected concerted activity", "EU Directive 2019/1152, Transparent and predictable working conditions", "European Works Council Directive 2009/38/EC, Transnational information and consultation in covered organizations", "ETUC AI and Workers' Rights Declaration (2023)" ], "categories": [ { "enum_name": "PerformanceEvaluationSource", "label": "Performance Evaluation Source", "otel_attribute": "hr.performance.evaluation_source", "opa_policy_path": "data.hr.performance.evaluation_source", "rego_input_key": "hr_performance_evaluation_source", "stability": "proposed", "description": "Records the data source used for AI-assisted performance evaluation. Assess the use under Annex III paragraph 4(b) and applicable employee privacy requirements.", "permitted_values": [ "manager_review_structured", "peer_360_feedback", "self_assessment", "objective_kpi_system_data", "ai_productivity_monitoring", "communication_sentiment_analysis", "code_commit_activity", "customer_satisfaction_csat", "attendance_punctuality_data", "learning_completion_data", "sales_crm_activity_data", "ticket_resolution_data" ], "value_labels": { "manager_review_structured": "Manager Review Structured", "peer_360_feedback": "Peer 360 Feedback", "self_assessment": "Self-Assessment", "objective_kpi_system_data": "Objective KPI System Data", "ai_productivity_monitoring": "AI Productivity Monitoring", "communication_sentiment_analysis": "Communication Sentiment Analysis", "code_commit_activity": "Code Commit Activity", "customer_satisfaction_csat": "Customer Satisfaction Csat", "attendance_punctuality_data": "Attendance Punctuality Data", "learning_completion_data": "Learning Completion Data", "sales_crm_activity_data": "Sales Crm Activity Data", "ticket_resolution_data": "Ticket Resolution Data" }, "regulatory_mappings": { "eu_ai_act_annex3_4a_ii": "EU AI Act Annex III paragraph 4(b) covers systems intended to monitor or evaluate workers’ performance and behaviour. Apply Article 6 classification criteria.", "gdpr_art13_14": "GDPR Articles 13/14, Employees must be informed at time of data collection of purposes and data sources used in automated performance evaluation", "nlra": "NLRA, 'communication_sentiment_analysis' monitoring must not be used to identify or suppress protected concerted activity (union organising, collective complaints)", "eu_directive_2019_1152": "EU Directive 2019/1152 Article 4, Workers have right to information about monitoring mechanisms, including AI performance evaluation data sources" }, "use_case": "AI performance evaluation agent records all data sources used for each evaluation. This drives GDPR Article 13 privacy notice accuracy and EU AI Act technical documentation. OPA policy blocks 'communication_sentiment_analysis' source data from feeding any termination or performance improvement plan recommendation without prior works council consultation.", "source": "EU AI Act Annex III paragraph 4(b); GDPR Articles 13 and 14; NLRA Section 7", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" }, { "enum_name": "EmployeeMonitoringType", "label": "Employee Monitoring Type", "otel_attribute": "hr.monitoring.type", "opa_policy_path": "data.hr.monitoring.type", "rego_input_key": "hr_monitoring_type", "stability": "stable", "description": "Type of AI-enabled employee monitoring. Each type carries different legal consent requirements, transparency obligations, and works council consultation requirements. Some types may be prohibited outright in certain jurisdictions.", "permitted_values": [ "productivity_keystroke_mouse_activity", "application_usage_tracking", "video_surveillance_workplace", "video_surveillance_remote_work", "email_communication_monitoring", "location_tracking_gps", "biometric_access_control", "biometric_fatigue_detection", "call_recording_analysis", "social_media_monitoring_internal", "ai_meeting_transcription_analysis", "ambient_listening_office" ], "value_labels": { "productivity_keystroke_mouse_activity": "Productivity Keystroke Mouse Activity", "application_usage_tracking": "Application Usage Tracking", "video_surveillance_workplace": "Video Surveillance Workplace", "video_surveillance_remote_work": "Video Surveillance Remote Work", "email_communication_monitoring": "Email Communication Monitoring", "location_tracking_gps": "Location Tracking Gps", "biometric_access_control": "Biometric Access Control", "biometric_fatigue_detection": "Biometric Fatigue Detection", "call_recording_analysis": "Call Recording Analysis", "social_media_monitoring_internal": "Social Media Monitoring Internal", "ai_meeting_transcription_analysis": "AI Meeting Transcription Analysis", "ambient_listening_office": "Ambient Listening Office" }, "code_definitions": { "biometric_fatigue_detection": "AI detects physical fatigue from facial or physiological signals. Fatigue detection alone is not emotion recognition under EU AI Act Recital 18.", "ambient_listening_office": "Continuous audio monitoring in an office. Assess the purpose, recording rules, employee privacy, and protected workplace activity before use.", "ai_meeting_transcription_analysis": "AI transcribes meetings or analyzes their content. Notice and consent requirements depend on the recording location and applicable law." }, "regulatory_mappings": { "eu_ai_act_art5_1f": "Article 5(1)(f) prohibits workplace emotion inference, except for medical or safety purposes. Recital 18 distinguishes physical fatigue detection from emotion recognition.", "gdpr_art9": "Article 9 covers biometric data processed to uniquely identify someone, and other listed categories such as health data. Processing requires an applicable Article 9 condition as well as an Article 6 lawful basis.", "nlra_sec7": "NLRA § 7, Employee monitoring must not interfere with protected concerted activity; blanket communication monitoring for union-related communications is unlawful", "eu_works_councils": "Directive 2009/38/EC covers transnational information and consultation in qualifying organizations. National co-determination rights and the applicable council agreement also affect the process." }, "source": "EU AI Act Article 5; GDPR Article 9; NLRA § 7; European Works Council Directive 2009/38/EC; national implementing laws", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" }, { "enum_name": "PerformanceImprovementPlanStatus", "label": "Performance Improvement Plan Status", "otel_attribute": "hr.performance.pip_status", "opa_policy_path": "data.hr.performance.pip_status", "rego_input_key": "hr_performance_pip_status", "stability": "proposed", "description": "Tracks a performance improvement plan from an initial concern through review and completion. Keep the AI recommendation separate from the authorized employment decision.", "permitted_values": [ "not_on_pip", "ai_flagged_for_consideration", "hrbp_review_in_progress", "pip_initiated_employee_notified", "pip_active_monitoring", "pip_completed_successfully", "pip_failed_separation_process", "pip_withdrawn_performance_improved" ], "value_labels": { "not_on_pip": "Not on Pip", "ai_flagged_for_consideration": "AI Flagged for Consideration", "hrbp_review_in_progress": "Hrbp Review in Progress", "pip_initiated_employee_notified": "Pip Initiated Employee Notified", "pip_active_monitoring": "Pip Active Monitoring", "pip_completed_successfully": "Pip Completed Successfully", "pip_failed_separation_process": "Pip Failed Separation Process", "pip_withdrawn_performance_improved": "Pip Withdrawn Performance Improved" }, "regulatory_mappings": { "eu_ai_act_annex3_4a": "EU AI Act Annex III paragraph 4(b) covers systems intended to make decisions on termination of work-related contractual relationships.", "gdpr_art22": "Article 22 restricts solely automated decisions with legal or similarly significant effects. Assess the decision's effects, any applicable exception, and required safeguards." }, "use_case": "Example company rule: stop an agent from initiating a performance improvement plan until an authorized reviewer approves it. Record the decision with the plan.", "source": "EU AI Act Annex III para 4; GDPR Article 22; SHRM PIP best practices", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" } ] }, { "subdomain": "Compensation Equity & Pay Transparency", "description": "Fields for pay-gap findings, compensation bands, and follow-up reviews. Keep the analysis result separate from reporting deadlines and joint-assessment requirements.", "relevant_standards": [ "EU Pay Transparency Directive (2023/970), Member state transposition by June 7, 2026", "Equal Pay Act (29 USC § 206(d)), US federal equal pay requirements", "Lilly Ledbetter Fair Pay Act (2009), Extended statute of limitations for pay discrimination claims", "Colorado Equal Pay for Equal Work Act (2021), Pay range disclosure in job postings", "NYC Salary Transparency Law (Local Law 32, 2022), Pay range disclosure", "California SB 1162 (2022), Pay scale disclosure and pay data reporting", "Illinois Equal Pay Act (2021 amendments), Pay data reporting" ], "categories": [ { "enum_name": "PayEquityAnalysisOutcome", "label": "Pay Equity Analysis Outcome", "otel_attribute": "hr.pay_equity.analysis_outcome", "opa_policy_path": "data.hr.pay_equity.analysis_outcome", "rego_input_key": "hr_pay_equity_analysis_outcome", "stability": "stable", "description": "Records a pay-equity analysis result for a worker group. A finding starts a review; it does not alone establish whether a statutory joint assessment is required.", "permitted_values": [ "equitable_no_unexplained_gap", "gap_identified_within_5pct_justified", "gap_identified_5_to_20pct_review_required", "gap_identified_above_20pct_assessment_mandatory", "gap_identified_remediation_in_progress", "gap_remediated_verified", "analysis_in_progress", "insufficient_data_for_analysis" ], "value_labels": { "equitable_no_unexplained_gap": "Equitable No Unexplained Gap", "gap_identified_within_5pct_justified": "Gap Identified Within 5pct Justified", "gap_identified_5_to_20pct_review_required": "Gap Identified 5 to 20pct Review Required", "gap_identified_above_20pct_assessment_mandatory": "Gap Identified Above 20pct Assessment Mandatory", "gap_identified_remediation_in_progress": "Gap Identified Remediation in Progress", "gap_remediated_verified": "Gap Remediated Verified", "analysis_in_progress": "Analysis in Progress", "insufficient_data_for_analysis": "Insufficient Data for Analysis" }, "code_definitions": { "gap_identified_5_to_20pct_review_required": "A measured gap falls within the catalog’s 5–20% review band. Record its explanation and follow-up; assess statutory duties separately.", "gap_identified_above_20pct_assessment_mandatory": "The gap exceeds the company’s 20% mandatory-assessment threshold. This catalog value represents company policy, not a separate threshold in the EU directive.", "gap_identified_remediation_in_progress": "Unjustified pay gap confirmed; remediation plan agreed with workers' representatives; timeline and targets documented" }, "regulatory_mappings": { "eu_pay_transparency_directive": "Directive (EU) 2023/970: Article 9 covers reporting, Article 10 sets joint-assessment conditions, and Article 7 covers workers’ information rights.", "equal_pay_act": "EPA 29 USC § 206(d), Pay differences for substantially equal work must be justified by seniority, merit, quantity/quality of production, or factor other than sex", "california_sb1162": "California SB 1162, Annual pay data report to CRD; mean and median pay data by race, ethnicity, and sex for each job category" }, "use_case": "AI pay equity agent runs annual analysis across all employees grouped by comparable work. 'Gap_identified_5_to_20pct_review_required' triggers notification to CHRO and works council. OPA policy blocks AI from recommending compensation adjustments in the annual merit cycle for any group where pay equity status is 'analysis_in_progress' or 'insufficient_data_for_analysis'.", "source": "EU Pay Transparency Directive (2023/970) Articles 7–10; Equal Pay Act; California SB 1162", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32023L0970" }, { "enum_name": "CompensationBandingStatus", "label": "Compensation Banding Status", "otel_attribute": "hr.compensation.banding_status", "opa_policy_path": "data.hr.compensation.banding_status", "rego_input_key": "hr_compensation_banding_status", "stability": "proposed", "description": "Shows where an employee’s compensation falls within the pay band for their role and level. Flag outliers for review before acting on a recommendation.", "permitted_values": [ "below_range_minimum", "in_range_low_quartile", "in_range_mid_point", "in_range_high_quartile", "above_range_maximum", "red_circle_above_range_frozen", "green_circle_below_range_priority", "band_not_established" ], "value_labels": { "below_range_minimum": "Below Range Minimum", "in_range_low_quartile": "In Range Low Quartile", "in_range_mid_point": "In Range Mid Point", "in_range_high_quartile": "In Range High Quartile", "above_range_maximum": "Above Range Maximum", "red_circle_above_range_frozen": "Red Circle Above Range Frozen", "green_circle_below_range_priority": "Green Circle Below Range Priority", "band_not_established": "Band not Established" }, "use_case": "AI compensation agent generates annual merit recommendations based on banding status and performance rating. 'Below_range_minimum' status receives priority increases. OPA policy blocks AI from recommending a zero merit increase for an employee in 'below_range_minimum' status without documented justification and manager HITL override.", "source": "WorldatWork compensation management framework; Mercer / Radford compensation benchmarking taxonomy", "source_url": "https://worldatwork.org/" } ] }, { "subdomain": "Workforce Planning & People Analytics", "description": "Covers AI-driven workforce planning, predictive attrition, and people analytics enumerations. Workforce planning AI that produces headcount reduction recommendations triggers WARN Act assessment and works council consultation obligations.", "relevant_standards": [ "WARN Act (29 USC § 2101), 60-day notice for plant closings and mass layoffs", "EU Collective Redundancies Directive (98/59/EC), Information and consultation obligations", "European Works Council Directive 2009/38/EC, Information and consultation for covered transnational workforce decisions", "ISO 30414:2018, Human capital reporting, workforce stability metrics", "SHRM Workforce Planning Framework" ], "categories": [ { "enum_name": "AttritionRiskLevel", "label": "Attrition Risk Level", "otel_attribute": "hr.workforce.attrition_risk_level", "opa_policy_path": "data.hr.workforce.attrition_risk_level", "rego_input_key": "hr_workforce_attrition_risk_level", "stability": "proposed", "description": "Estimates how likely an employee is to leave. HR teams can use the score to prioritize retention conversations; it is not an employment decision.", "permitted_values": [ "low_risk", "moderate_risk", "high_risk", "critical_risk_key_talent", "already_resigned", "model_confidence_insufficient" ], "value_labels": { "low_risk": "Low Risk", "moderate_risk": "Moderate Risk", "high_risk": "High Risk", "critical_risk_key_talent": "Critical Risk Key Talent", "already_resigned": "Already Resigned", "model_confidence_insufficient": "Model Confidence Insufficient" }, "regulatory_mappings": { "eu_ai_act_annex3_4a": "Annex III paragraph 4(b) covers specified employment decisions, task allocation, and worker monitoring. Classify the intended use under Article 6.", "gdpr_art22": "Article 22 restricts solely automated decisions with legal or similarly significant effects. An attrition score alone does not determine whether these conditions apply." }, "use_case": "Example company rule: allow high attrition scores to prompt retention conversations. Block their use to exclude employees from promotions, assignments, or pay increases.", "source": "IBM Watson Talent / Workday People Analytics attrition model taxonomy; EU AI Act Annex III para 4", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" }, { "enum_name": "WorkforceReductionTriggerType", "label": "Workforce Reduction Trigger Type", "otel_attribute": "hr.workforce.reduction_trigger_type", "opa_policy_path": "data.hr.workforce.reduction_trigger_type", "rego_input_key": "hr_workforce_reduction_trigger_type", "stability": "stable", "description": "Records the reason for a proposed workforce reduction. Use the affected locations, headcounts, and dates to assess notice and consultation requirements.", "permitted_values": [ "individual_performance_separation", "role_elimination_restructure", "site_closure", "mass_layoff_us_warn_act", "collective_redundancy_eu", "voluntary_separation_programme", "contractor_workforce_reduction", "ai_automation_displacement" ], "value_labels": { "individual_performance_separation": "Individual Performance Separation", "role_elimination_restructure": "Role Elimination Restructure", "site_closure": "Site Closure", "mass_layoff_us_warn_act": "Mass Layoff Us Warn Act", "collective_redundancy_eu": "EU collective redundancy", "voluntary_separation_programme": "Voluntary Separation Programme", "contractor_workforce_reduction": "Contractor Workforce Reduction", "ai_automation_displacement": "AI Automation Displacement" }, "code_definitions": { "mass_layoff_us_warn_act": "A proposed layoff assessed under federal WARN. Coverage depends on the employer, employment losses, site, counting periods, and applicable exceptions.", "collective_redundancy_eu": "A proposed reduction assessed under national rules implementing Directive 98/59/EC. Thresholds depend on the national counting method and establishment size.", "ai_automation_displacement": "Roles are proposed for elimination because of AI or automation. Assess the resulting employment changes under applicable notice and consultation rules." }, "regulatory_mappings": { "warn_act": "Covered plant closings and mass layoffs generally require 60 days' advance written notice. Assess 30-day and 90-day aggregation rules, worker-count exclusions, exceptions, and any separate state requirements.", "eu_collective_redundancy": "Directive 98/59/EC requires consultation on contemplated collective redundancies and notification to the competent authority. Apply national thresholds, procedures, and waiting periods." }, "use_case": "Example company rule: stop an agent from finalizing a reduction list until an authorized reviewer confirms the required notices and consultation. Save the assessment with the proposal.", "source": "WARN Act 29 USC § 2101; EU Collective Redundancies Directive 98/59/EC", "source_url": "https://www.dol.gov/sites/dolgov/files/ETA/layoffs/pdfs/WARNAct1988.pdf" } ] }, { "subdomain": "Learning, Development & Skills Management", "description": "Record why learning was recommended and how a skill was assessed. Evaluate the actual use, especially when recommendations affect promotion or access to opportunities.", "relevant_standards": [ "SCORM 2004 / xAPI (TinCan), Learning activity tracking standards", "IMS Global LTI Advantage, LMS integration (see also higher education vertical)", "WCAG 2.2 AA, Accessibility for AI-generated learning content", "EU AI Act Annex III paragraph 4(b), AI used for promotion decisions", "Skills-based hiring frameworks, ONET, ESCO (EU), LinkedIn Skills Graph" ], "categories": [ { "enum_name": "LearningRecommendationTrigger", "label": "Learning Recommendation Trigger", "otel_attribute": "hr.learning.recommendation_trigger", "opa_policy_path": "data.hr.learning.recommendation_trigger", "rego_input_key": "hr_learning_recommendation_trigger", "stability": "proposed", "description": "Records why an employee received a learning recommendation. Keep the reason with the recommendation so employees and reviewers can understand its purpose.", "permitted_values": [ "skill_gap_identified_role", "career_path_next_role", "performance_review_development_goal", "compliance_mandatory_training", "role_change_onboarding", "ai_automation_reskilling", "manager_nominated", "self_nominated", "succession_planning_readiness", "license_certification_renewal" ], "value_labels": { "skill_gap_identified_role": "Skill Gap Identified Role", "career_path_next_role": "Career Path Next Role", "performance_review_development_goal": "Performance Review Development Goal", "compliance_mandatory_training": "Compliance Mandatory Training", "role_change_onboarding": "Role Change Onboarding", "ai_automation_reskilling": "AI Automation Reskilling", "manager_nominated": "Manager Nominated", "self_nominated": "Self Nominated", "succession_planning_readiness": "Succession Planning Readiness", "license_certification_renewal": "License Certification Renewal" }, "regulatory_mappings": { "eu_ai_act_annex3_4a_iii": "Assess promotion-related uses under Annex III paragraph 4(b). A learning recommendation alone does not determine the system’s legal classification.", "ada_title_i": "ADA Title I, Learning content and assessment tools must be accessible; 'compliance_mandatory_training' must accommodate employees with disabilities" }, "use_case": "Example workflow: record the reason for each recommended course. When automation changes a role's skill needs, route the learning plan to the employee's development advisor.", "source": "VeriProof learning-workflow vocabulary; EU AI Act Annex III paragraph 4(b) for relevant employment uses", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32024R1689" }, { "enum_name": "SkillProficiencyLevel", "label": "Skill Proficiency Level", "otel_attribute": "hr.skills.proficiency_level", "opa_policy_path": "data.hr.skills.proficiency_level", "rego_input_key": "hr_skills_proficiency_level", "stability": "stable", "description": "Records an assessed skill level using the company's criteria. ESCO can identify the skill; these proficiency labels are VeriProof vocabulary, not an ESCO rating scale.", "permitted_values": [ "awareness", "foundational", "intermediate", "advanced", "expert", "not_assessed" ], "value_labels": { "awareness": "Awareness", "foundational": "Foundational", "intermediate": "Intermediate", "advanced": "Advanced", "expert": "Expert", "not_assessed": "Not Assessed" }, "ordered": true, "value_ordinals": { "awareness": 1, "foundational": 2, "intermediate": 3, "advanced": 4, "expert": 5 }, "use_case": "Example company rule: require assessment evidence before using a skill rating to reject an opportunity match. Treat 'not_assessed' as missing evidence, not low ability.", "source": "VeriProof proficiency vocabulary; ESCO classification for skill concepts", "source_url": "https://esco.ec.europa.eu/en/about-esco/what-esco" } ] }, { "subdomain": "Employee Relations, HR Case Management & Works Councils", "description": "Track HR cases and required employee-representative consultation. The applicable process depends on the organization, proposed change, and national rules.", "relevant_standards": [ "European Works Council Directive 2009/38/EC, Transnational information and consultation in covered organizations", "German Betriebsverfassungsgesetz (BetrVG) § 87(1)(6), Works council co-determination on monitoring", "French CNIL guidance on employee monitoring", "NLRA § 8, Unfair labour practices including unilateral implementation of AI monitoring", "ADA Title I, HR case management for disability-related accommodation requests" ], "categories": [ { "enum_name": "HRCaseType", "label": "HR Case Type", "otel_attribute": "hr.case.type", "opa_policy_path": "data.hr.case.type", "rego_input_key": "hr_case_type", "stability": "stable", "description": "Identifies the employee's request or concern so the agent can route it to the right team. Assess confidentiality, deadlines, and reporting duties from the case facts.", "permitted_values": [ "harassment_complaint", "discrimination_complaint", "pay_dispute", "accommodation_request_disability", "accommodation_request_religious", "leave_of_absence_request", "grievance_general", "whistleblower_protected_disclosure", "workplace_safety_incident", "performance_dispute", "wrongful_termination_claim", "data_privacy_employee_request", "ethics_policy_violation", "retaliation_complaint" ], "value_labels": { "harassment_complaint": "Harassment complaint", "discrimination_complaint": "Discrimination complaint", "pay_dispute": "Pay dispute", "accommodation_request_disability": "Disability accommodation request", "accommodation_request_religious": "Religious accommodation request", "leave_of_absence_request": "Leave request", "grievance_general": "General grievance", "whistleblower_protected_disclosure": "Protected whistleblower disclosure", "workplace_safety_incident": "Workplace safety incident", "performance_dispute": "Performance dispute", "wrongful_termination_claim": "Wrongful termination claim", "data_privacy_employee_request": "Employee privacy request", "ethics_policy_violation": "Ethics policy violation", "retaliation_complaint": "Retaliation complaint" }, "code_definitions": { "whistleblower_protected_disclosure": "A report handled under an applicable whistleblower protection framework. Restrict access to authorized handlers and protect information that could identify the reporter.", "harassment_complaint": "An employee reports harassment. Route the complaint for investigation and limit access to people responsible for handling it.", "accommodation_request_disability": "A request for a workplace adjustment related to disability. Assess the employee's needs and effective options while protecting medical information." }, "regulatory_mappings": { "eu_whistleblower_directive": "Directive 2019/1937 Articles 9 and 16 protect reporting-channel confidentiality and limit disclosure of the reporter's identity. Consent and specified legal obligations can permit disclosure.", "ada_title_i": "Covered employers must provide reasonable accommodation to qualified individuals unless it causes undue hardship. Discuss needs and effective options when needed; protect medical information.", "osha": "OSHA Part 1904 sets employer coverage, recordability criteria, and separate reporting duties. A workplace-safety case label alone does not establish a recording obligation." }, "use_case": "Example company rule: route whistleblower and retaliation reports to authorized handlers outside the implicated management chain. Block complaint closure until an authorized reviewer records the investigation outcome.", "source": "EU Whistleblower Directive 2019/1937; ADA Title I; OSHA recordkeeping; Title VII", "source_url": "https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32019L1937" }, { "enum_name": "WorksCouncilConsultationStatus", "label": "Works Council Consultation Status", "otel_attribute": "hr.works_council.consultation_status", "opa_policy_path": "data.hr.works_council.consultation_status", "rego_input_key": "hr_works_council_consultation_status", "stability": "stable", "description": "Tracks consultation with employee representatives about a proposed HR AI system. Record whether consultation is required and its outcome. Consultation and approval rights vary by jurisdiction.", "permitted_values": [ "not_required_jurisdiction", "consultation_not_yet_initiated", "information_provided_awaiting_response", "consultation_in_progress", "consultation_completed_agreement_reached", "consultation_completed_no_agreement", "appeal_to_conciliation_board", "deployment_blocked_by_works_council" ], "value_labels": { "not_required_jurisdiction": "Consultation not required", "consultation_not_yet_initiated": "Consultation not started", "information_provided_awaiting_response": "Awaiting council response", "consultation_in_progress": "Consultation in progress", "consultation_completed_agreement_reached": "Consultation complete, agreement reached", "consultation_completed_no_agreement": "Consultation complete, no agreement", "appeal_to_conciliation_board": "Referred for conciliation", "deployment_blocked_by_works_council": "Deployment on hold pending council resolution" }, "code_definitions": { "deployment_blocked_by_works_council": "An unresolved council requirement prevents deployment. Record the requirement and the resolution needed to proceed.", "consultation_completed_no_agreement": "Consultation ended without agreement. This status does not authorize deployment; check whether agreement or another resolution is required." }, "regulatory_mappings": { "german_betrvg_87_1_6": "BetrVG Section 87(1)(6) covers co-determination for employee-monitoring technology where applicable. Under Section 87(2), a conciliation committee can resolve disagreement.", "eu_works_council_directive": "Directive 2009/38/EC governs transnational information and consultation in covered organizations. Directive (EU) 2025/2450 revises that framework; assess national implementation and applicable transition dates.", "nlra_sec8_a_5": "NLRA § 8(a)(5), US employers with recognised unions must bargain in good faith over implementation of AI monitoring that affects terms and conditions of employment" }, "use_case": "Example company rule: hold deployment until required consultation is complete and any agreement requirement is resolved. Save the outcome with the deployment decision.", "source": "German BetrVG § 87; European Works Council Directive 2009/38/EC and amending Directive (EU) 2025/2450; NLRA § 8", "source_url": "https://employment-social-affairs.ec.europa.eu/policies-and-activities/rights-work/labour-law/employee-involvement/european-works-councils_en" } ] }, { "subdomain": "Payroll, Benefits & Labour Compliance", "description": "Covers FLSA wage and hour compliance, benefits eligibility, and AI-driven payroll anomaly detection enumerations.", "relevant_standards": [ "FLSA (29 USC § 201), Minimum wage, overtime, exempt/non-exempt classification", "ERISA (29 USC § 1001), Employee benefit plan administration", "ACA (26 USC § 4980H), Affordable Care Act employer mandate", "FMLA (29 USC § 2601), Family and Medical Leave Act", "IRS Publication 15-T, Federal income tax withholding", "GDPR Articles 6 and 9, Payroll data needs a lawful basis; health data also requires an applicable special-category condition" ], "categories": [ { "enum_name": "WorkerClassificationStatus", "label": "Worker Classification Status", "otel_attribute": "hr.payroll.worker_classification", "opa_policy_path": "data.hr.payroll.worker_classification", "rego_input_key": "hr_payroll_worker_classification", "stability": "stable", "description": "Records a worker's classification for the workflow. Employment status, overtime eligibility, and tax treatment can require separate assessments; one label does not settle all three.", "permitted_values": [ "employee_exempt_flsa", "employee_nonexempt_flsa", "employee_part_time", "employee_temporary", "independent_contractor_1099", "leased_worker_peo", "intern_paid", "intern_unpaid_compliant", "gig_worker_platform", "classification_under_review" ], "value_labels": { "employee_exempt_flsa": "Employee Exempt Flsa", "employee_nonexempt_flsa": "Employee Nonexempt Flsa", "employee_part_time": "Employee Part Time", "employee_temporary": "Employee Temporary", "independent_contractor_1099": "Independent Contractor 1099", "leased_worker_peo": "Leased Worker Peo", "intern_paid": "Intern Paid", "intern_unpaid_compliant": "Intern Unpaid Compliant", "gig_worker_platform": "Gig Worker Platform", "classification_under_review": "Classification Under Review" }, "code_definitions": { "employee_exempt_flsa": "Employee classified under an applicable FLSA exemption. Record the exemption and supporting facts; the label alone does not establish eligibility.", "employee_nonexempt_flsa": "Employee covered by FLSA minimum-wage and overtime protections. The usual federal rule requires 1.5 times the regular rate for hours above 40 in a workweek.", "independent_contractor_1099": "Worker classified as an independent contractor. A 1099 form does not determine status; assess the actual working relationship under each applicable law.", "classification_under_review": "The worker's classification is unresolved. Route decisions that depend on it to the responsible reviewer." }, "regulatory_mappings": { "flsa": "FLSA protections depend on coverage and exemption status. Record hours and apply the wage and overtime rules that cover the worker.", "irs_ss8": "IRS Form SS-8 requests a federal employment-tax classification determination. IRS common-law rules assess control and independence; state and wage-law tests are separate.", "california_ab5": "California generally uses the ABC test for covered classification decisions. Statutory exceptions can require a different test, including Borello." }, "use_case": "Example company rule: stop an automated classification change while review is pending. Route the proposed change and its supporting facts to payroll; preserve timely payment of wages owed.", "source": "FLSA 29 USC § 201; IRS common-law classification rules; California DIR independent-contractor guidance", "source_url": "https://www.dol.gov/agencies/whd/flsa" }, { "enum_name": "PayrollAnomalyType", "label": "Payroll Anomaly Type", "otel_attribute": "hr.payroll.anomaly_type", "opa_policy_path": "data.hr.payroll.anomaly_type", "rego_input_key": "hr_payroll_anomaly_type", "stability": "proposed", "description": "Records a payroll discrepancy for investigation. A flagged payment is not proof of fraud or a wage violation. Use company rules to decide which corrections need approval.", "permitted_values": [ "overtime_threshold_exceeded", "minimum_wage_violation_suspected", "duplicate_payment", "ghost_employee_indicator", "unusual_pay_rate_change", "off_cycle_payment_unauthorised", "benefit_deduction_mismatch", "tax_withholding_error", "wage_garnishment_calculation_error", "pay_equity_outlier" ], "value_labels": { "overtime_threshold_exceeded": "Overtime Threshold Exceeded", "minimum_wage_violation_suspected": "Minimum Wage Violation Suspected", "duplicate_payment": "Duplicate Payment", "ghost_employee_indicator": "Ghost Employee Indicator", "unusual_pay_rate_change": "Unusual Pay Rate Change", "off_cycle_payment_unauthorised": "Off Cycle Payment Unauthorised", "benefit_deduction_mismatch": "Benefit Deduction Mismatch", "tax_withholding_error": "Tax Withholding Error", "wage_garnishment_calculation_error": "Wage Garnishment Calculation Error", "pay_equity_outlier": "Pay Equity Outlier" }, "regulatory_mappings": { "flsa": "Check suspected underpayments against the worker's hours, applicable rate, and coverage. Confirm and correct amounts owed; an alert alone does not establish a violation.", "eu_pay_transparency": "A pay-equity outlier can prompt further analysis. Directive 2023/970 reporting and joint-assessment duties depend on employer scope and the conditions in Articles 9 and 10." }, "use_case": "Example company rule: stop an unapproved automated payroll adjustment and route the discrepancy to payroll for review. Investigate suspected duplicate payments without treating the flag as confirmed fraud.", "source": "FLSA; EU Pay Transparency Directive 2023/970", "source_url": "https://www.dol.gov/agencies/whd/flsa" } ] } ], "opa_rego_policy_patterns": { "description": "Human Resources & Workforce Management-specific OPA Rego policy patterns referencing enum values from this file and from 00_core_sdk_and_governance.json. Illustrative patterns, not production policies.", "patterns": [ { "pattern_id": "hr.block_aedt_use_without_bias_audit_and_candidate_notice", "pattern_name": "block_aedt_use_without_bias_audit_and_candidate_notice", "display_name": "Check the bias audit and candidate notice before hiring decisions", "enforcement_effect": "deny", "description": "Hold covered hiring actions until the current independent bias audit and required advance notice are recorded. Findings that breach the employer's configured criteria also stop the action.", "applicable_enums": [ "RecruitmentStage", "BiasAuditOutcome", "CandidateNoticeStatus", "AIEmploymentDecisionType" ], "regulatory_basis": "NYC Local Law 144: covered tool use requires an independent audit within one year, published audit information, and applicable advance notices. Required candidate notice precedes use by at least 10 business days; blocking findings are an employer-defined control." }, { "pattern_id": "hr.block_adverse_employment_decision_without_hitl", "pattern_name": "block_adverse_employment_decision_without_hitl", "enforcement_effect": "require_hitl_approval", "description": "Example company rule: stop an agent from finalizing a termination, demotion, performance plan, or layoff selection without an authorized reviewer's approval. Save the approval with the proposed action.", "applicable_enums": [ "AIEmploymentDecisionType", "PerformanceImprovementPlanStatus", "WorkforceReductionTriggerType" ], "regulatory_basis": "EU AI Act Article 14 addresses human oversight for high-risk systems. GDPR Article 22 restricts solely automated decisions with significant effects, subject to exceptions and safeguards. The company rule sets its own approval requirement." }, { "pattern_id": "hr.enforce_works_council_consultation_gate_eu", "pattern_name": "enforce_works_council_consultation_gate_eu", "enforcement_effect": "deny", "description": "Example company rule: stop deployment while required employee consultation or agreement remains unresolved. Apply the control only where those requirements cover the proposed change.", "applicable_enums": [ "WorksCouncilConsultationStatus", "EmployeeMonitoringType", "AIEmploymentDecisionType" ], "regulatory_basis": "German BetrVG Section 87 covers specified co-determination rights. Directive 2009/38/EC governs covered transnational consultation, with revisions under Directive (EU) 2025/2450. National implementation and council agreements determine the applicable process." }, { "pattern_id": "hr.enforce_eu_pay_transparency_joint_assessment", "pattern_name": "enforce_eu_pay_transparency_joint_assessment", "enforcement_effect": "deny", "description": "Example company rule: hold a compensation action for review when a reported pay gap reaches 5%. Track the explanation, remediation date, and any required joint assessment with workers’ representatives.", "applicable_enums": [ "PayEquityAnalysisOutcome", "CompensationBandingStatus", "AIEmploymentDecisionType" ], "regulatory_basis": "Directive (EU) 2023/970 Article 10 applies to employers subject to Article 9 reporting when all joint-assessment conditions hold. Reporting shows a gap of at least 5% in a worker category, without objective gender-neutral justification, and it remains unremedied six months after submission." }, { "pattern_id": "hr.block_biometric_emotion_inference_monitoring", "pattern_name": "block_biometric_emotion_inference_monitoring", "enforcement_effect": "deny", "description": "Example company rule: block an agent from using fatigue measurements or inferred emotions to make employment decisions. This control is broader than the workplace emotion-recognition prohibition.", "applicable_enums": [ "EmployeeMonitoringType", "AIEmploymentDecisionType", "BiasAuditOutcome" ], "regulatory_basis": "EU AI Act Article 5(1)(f) prohibits workplace emotion inference except for medical or safety purposes. Recital 18 excludes physical fatigue from emotion recognition. GDPR Article 9 applies to qualifying biometric and health data, with specified processing conditions." } ] }, "agent_registry_fields": { "description": "Recommended fields for registering a human resources or workforce management domain agentic AI system in the GRC portal. Supplements the core agent identity schema from 00_core_sdk_and_governance.json.", "fields": [ { "field": "eu_ai_act_annex3_employment_category", "type": "string", "description": "Records the employment use case for an EU AI Act scope assessment. Annex III high-risk requirements apply from December 2, 2027, subject to transitional provisions. Catalog values describe workflow categories; assess legal scope against Annex III paragraph 4.", "required_when": "All AI systems used in recruitment, selection, task allocation, employee monitoring, promotion, or termination decisions affecting EU-based workers" }, { "field": "nyc_ll144_aedt_registered", "type": "boolean", "description": "True if this AI system meets the NYC Local Law 144 definition of an Automated Employment Decision Tool and has an annual independent bias audit on file with results publicly posted.", "required_when": "All AI recruitment and selection tools used for NYC-based employment decisions" }, { "field": "bias_audit_expiration_date", "type": "string", "description": "Expiration date of the most recent independent bias audit. NYC LL144 requires annual audits; audit expiration blocks continued AEDT use.", "required_when": "All AEDTs subject to NYC LL144 or equivalent state law bias audit requirements" }, { "field": "works_council_agreement_reference", "type": "string", "description": "Reference number of the works council agreement (Betriebsvereinbarung or equivalent) governing the use of this AI system for employee monitoring or employment decisions. Required in EU jurisdictions with co-determination rights.", "required_when": "All HR AI monitoring and employment decision systems deployed in EU member states with works council co-determination rights (DE, AT, NL, FR, BE and others)" }, { "field": "eeoc_validity_evidence_type", "type": "string", "description": "Records the validity evidence supporting a selection tool. Identify the study method and job context, or record that no study has been conducted. Assess required evidence under the applicable legal standard.", "required_when": "All AI assessment, screening, and selection tools used in employment decisions" }, { "field": "pay_transparency_disclosure_enabled", "type": "boolean", "description": "True if this AI compensation tool supports EU Pay Transparency Directive Article 7 requirements, providing employees with information about salary levels for comparable work categories.", "required_when": "When applicable pay-transparency reporting or company policy requires a pay-equity review" }, { "field": "employee_data_processing_basis", "type": "string", "description": "GDPR lawful basis for processing employee personal data by this AI system. Employment data processing under GDPR typically relies on Article 6(1)(b) (contract performance), 6(1)(c) (legal obligation), or 6(1)(f) (legitimate interests), explicit consent is rarely appropriate in an employment relationship. Use values such as 6_1_b_contract_performance, 6_1_c_legal_obligation, 6_1_f_legitimate_interests, 9_2_b_employment_law, or not_processing_eu_employee_data.", "required_when": "All AI agents processing personal data of EU-based employees" }, { "field": "illinois_aivia_consent_mechanism", "type": "boolean", "description": "True if applicants receive notice and an explanation of the AI analysis, then give consent before the interview. Tracks the Section 5 consent process, not demographic reporting.", "required_when": "Employers request recorded video interviews and use AI to evaluate applicants for Illinois-based positions" } ] } }