Skill אתיקה ו-Guardrails ב-AI ל-Claude

מתי להשתמש

"AI ethics", "AI policy", "Guardrails", "AI governance", "EU AI Act", "AI compliance".

הוראות עבודה

1. Why It Matters

AI failure = brand damage, lawsuits, employee distrust. Proactive ethics > Reactive damage control.

2. Top Risks

א. Hallucinations

• AI invents facts.
• Risk: bad decisions, customer harm.
• Mitigation: validate, cite sources, RAG.

ב. Bias

• Training data bias → biased outputs.
• Risk: discrimination, lawsuits.
• Mitigation: diverse testing, monitoring.

ג. Privacy

• PII to public APIs.
• Risk: GDPR/PPL violation, breach.
• Mitigation: data minimization, self-host sensitive.

ד. Transparency

• Users don't know they talk to AI.
• Risk: trust erosion, regulation.
• Mitigation: disclose AI use.

ה. Job Displacement

• AI replaces tasks.
• Risk: morale, layoffs.
• Mitigation: retraining, augmentation framing.

ו. Misuse

• AI for harmful purposes (deepfakes, misinformation).
• Risk: brand damage, criminal liability.
• Mitigation: usage policy, monitoring.

3. Building AI Policy

Components

1. Approved tools list.
2. What can be sent to AI: prohibited data (PII, IP).
3. Disclosure rules (when to tell humans AI used).
4. Quality standards (review AI outputs).
5. Decision boundaries (humans-only decisions).
6. Incident response (if AI causes harm).
7. Training requirements.
8. Audit / monitoring.

Sample Policy Outline

1. Purpose
2. Scope (which roles/depts)
3. Approved AI Tools
4. Prohibited Uses
5. Data Classification
   - Public: OK to AI.
   - Internal: case by case.
   - Confidential: never to public AI.
   - PII: special rules.
6. Disclosure Rules
7. Quality Review
8. Privacy & Security
9. Compliance
10. Training
11. Incident Reporting
12. Updates

4. Regulations 2026

EU AI Act (Effective 2024-2026)

• Risk-based: prohibited / high / limited / minimal.
• High-risk: biometric, credit, employment AI.
• Transparency for chatbots.
• Fines: up to €35M or 7% global revenue.

Israeli Regulation

• PPL Amendment 13 — AI implications.
• Israeli Privacy Authority — guidance on AI.
• Sector-specific (financial, medical) — additional rules.

US

• Patchwork (state-by-state).
• Federal AI Bill of Rights (non-binding).
• Sector regulations (HIPAA, FCRA).

5. Bias Mitigation

Test for Bias

• Diverse test sets.
• Different demographics.
• Edge cases.

When Bias Found

• Update prompts.
• Add filters.
• Different model.
• Post-process outputs.

Continuous Monitoring

• Sample outputs.
• User feedback channels.
• Metrics (e.g., approval rate by group).

6. Hallucination Mitigation

• RAG for factual content.
• Cite sources in prompts.
• Validate output — rules, schema.
• Human review for critical.
• "I don't know" allowed in prompt.

7. High-Risk Use Cases (Be Careful)

• Hiring decisions — bias risk.
• Credit decisions — regulatory.
• Medical advice — liability.
• Legal advice — liability.
• Children's content — safety.
• Mental health — safety.

Best practice: AI assists, human decides.

8. Disclosure

When Required

• Chatbot impersonating human (EU).
• AI-generated content for public.
• AI in hiring (some jurisdictions).

Best Practice

• Always disclose when reasonable.
• Building trust.

9. Privacy Best Practices

Data Minimization

• Only send what's needed.
• Strip PII before AI.
• Anonymize when possible.

Vendor Selection

• DPA in place.
• Don't train on data (Anthropic/OpenAI default).
• Self-host for sensitive.

Audit Logs

• What was sent to AI.
• When.
• By whom.
• For what purpose.

10. AI Governance Structure

Small Org

• AI Champion (1 person, part-time).
• Quarterly review.

Mid Org

• AI Committee (cross-functional).
• Monthly review.
• Approve new use cases.

Large Org

• AI Ethics Officer.
• AI Council (executives).
• Continuous monitoring.

11. Israel Specifics

• Hebrew bias testing — under-tested area.
• Israeli compliance evolving.
• Defense industry = stricter rules.

12. Common Pitfalls

❌ No policy — wild west. ❌ Policy too restrictive — shadow IT. ❌ No training — policy ignored. ❌ No audit — unknown violations. ❌ AI for prohibited use — legal risk.

13. אסיים בהמלצה.

פרומפט לדוגמה

Build AI usage policy for 100-employee Israeli SaaS.

EU AI Act — implications for our chatbot.

Hallucination mitigation strategy.

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