AI Ethics & Human Oversight

At SafeVoice, we believe that AI should serve as an empathetic, objective, and privacy-preserving bridge—never as the final arbiter of justice. This document outlines our core ethical commitments.

1. Human-in-the-Loop Validation

Our triage model classifies reports, assesses risk levels, and extracts red flags. However, no automated decision is ever final or actionable on its own. Every triaged case must be reviewed, validated, and approved by a verified human caseworker at WGHEN before any institutional escalation occurs.

2. Multilingual Empathy

We train our triage keyword engine specifically to understand localized dialects, campus slang, and regional vocabulary (English, Hausa, Pidgin). This ensures that survivors can tell their stories in their own comfortable languages without fearing automated misunderstanding.

3. Transparency & Bias Minimization

We maintain absolute transparency: our local rule-based parsing engine is free from opaque deep learning biases and is fully auditable. We prevent defamatory tarnishing patterns using localized red-flag filters to ensure fairness.