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@@ -112,3 +112,36 @@ The model has an accuracy of %
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  author={Nouar AlDahoul, Yasir Zaki}
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  }
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  author={Nouar AlDahoul, Yasir Zaki}
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  }
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  ```
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+ ## Governance & Responsible Use
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+ The **FaceScanPaliGemma** model processes highly sensitive biometric data (facial attributes). Deployment of this model must follow **strict governance frameworks** to ensure responsible and ethical use.
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+ ### ✅ Permitted Uses
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+ - Academic research, benchmarking, and reproducibility studies.
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+ - Educational projects exploring bias, fairness, and multimodal AI.
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+ - Development of fairness-aware systems with proper safeguards.
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+
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+ ### ❌ Prohibited Uses
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+ - **Surveillance or mass monitoring** of individuals or groups.
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+ - **Identity verification or authentication** without explicit and informed consent.
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+ - **Applications that discriminate against or marginalize** individuals or communities.
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+ - Use on **scraped datasets or facial images** collected without consent.
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+
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+ ### ⚠️ Law Enforcement Use
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+ - Direct use in **law enforcement contexts is not recommended** due to high societal risks.
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+ - Risks include **bias amplification**, **wrongful identification**, and **privacy violations**.
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+ - If ever considered, deployment must be:
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+ - Governed by **strict legal frameworks** (e.g., EU AI Act, GDPR, CCPA).
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+ - Subject to **independent auditing, transparency, and accountability**.
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+ - Limited to **proportional, necessary, and rights-respecting use cases**.
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+
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+ ### Governance Principles
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+ 1. **Access & Control** – Limit deployment to contexts with clear oversight and accountability.
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+ 2. **Transparency** – Always disclose when and how the model is used.
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+ 3. **Bias & Fairness Auditing** – Evaluate performance across demographic groups before deployment.
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+ 4. **Privacy Protection** – Respect GDPR, CCPA, and local regulations; never process data without consent.
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+ 5. **Accountability** – Establish internal review boards or ethics committees for production use.
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+ ### Community Reporting
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+ We encourage the community to report issues, biases, or misuse of this model through the **Hugging Face Hub discussion forum**.