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Ethics, Privacy & Professionalism 🛡️

CommitVigil is a high-pressure accountability tool, but it is built with the "Supportive First" philosophy. Addressing feedback on the human implications of AI-driven enforcement is critical for enterprise adoption.

1. Ethical Tone Escalation

One of our most discussed features is the "Confrontational" tone. Here is how we handle it ethically:

  • The Empathy Buffer: The system is hardcoded to prioritize SUPPORTIVE tones if anything resembling burnout or personal distress is detected.
  • The Burnout Safety Valve: If the ExcuseDetector identifies signs of fatigue, the system blocks confrontational escalation and triggers a "Burnout Alert" for the manager instead.
  • Tone Drift & Cooling-off: To prevent morale fatigue, the system implements mathematical tone-damping. If a user receives 3 consecutive "Firm" or "Confrontational" follow-ups, the logic automatically locks the agent into a NEUTRAL or SUPPORTIVE state for 48 hours (configurable via COOLING_OFF_PERIOD_HOURS).

2. Industry-Specific Semantic Firewall 🧱

CommitVigil provides hard-coded safety guarantees for regulated industries: * Healthcare (HIPAA): The system hard-blocks unauthorized medical mandates or PII disclosure. * Finance (SEC): Prevents the agent from accidentally facilitating market manipulation or providing unregulated financial advice. * HR Territory: Discussions involving Salary, PIP (Performance Improvement Plans), or Firing are immediately escalated to human review.

3. Continuous Learning & ROI Metrics 📈

CommitVigil doesn't just act; it learns: * Manager Feedback Loop: Every intervention can be reviewed by a supervisor. Their "Accept/Modify/Reject" decisions are persisted. * ROI Dashboard: The system calculates the Intervention Acceptance Rate to quantify the AI's alignment with management intent.

  • Sensitivity Calibration: CommitVigil supports Cultural Tone Profiles. Managers can calibrate the "Pressure Sensitivity" of the agents to match their specific team norms (e.g., High-Directness vs. High-Context locales).
  • Domain-Specific Jargon: The NLP models are refined to recognize that certain industry vernacular (e.g., "I'm swamped") may be a routine status update rather than an excuse in specific high-velocity teams.

4. Privacy & Data Integrity

Monitoring at the granularity of Slack threads and Git commits requires a strict privacy stance:

  • Scoped Monitoring: CommitVigil is designed to monitor designated #project channels, not private DMs or unrelated chatter.
  • Source-Level Only: Commit monitoring is restricted to commit messages and PR metadata—not the proprietary logic within the source code files themselves.
  • Identity Anonymization: Internal IDs are used for analysis; real names can be masked in the database if necessary.

5. Handling Ambiguity (The "100% Visibility" Claim) 🧠

Ambiguity is the greatest challenge in Engineering NLP. Here is how we move toward high accuracy:

  • Confidence Scores: Every extraction (Commitment, Risk, Excuse) is accompanied by a confidence_score.
  • Human-in-the-Loop (HITL): If a score falls below 0.75, the system flags the extraction as "Ambiguous" and asks the manager for manual validation instead of taking autonomous action.
  • Semantic Context: By correlating Git activity with Slack messages, we resolve ambiguity. If a dev says "I'll handle it," but we see a corresponding Git branch with the task name, the "soft commitment" is confirmed.

🚀 Deployment & The Future

Why build this? CommitVigil was inspired by the "Slack Stall"—the invisible friction where professional promises disappear into the scroll history of remote teams. It turns "I'll get to it" into a technical obligation.

Real-World Testing: The next phase of the project involves a Private Beta where the TruthGapDetector will be tested against real-world ambiguous data to refine its "Precision Accountability" engine.