AI Safety

Introduction

AI safety in prompts covers harm prevention, bias mitigation, refusals, and graceful failure modes.

Beginner analogy: Like car safety — seatbelts, airbags, ABS — many layers, all needed.

Understanding the topic

Core concepts to understand:

• Refusal rules for harmful / illegal / sensitive content.
• Bias testing across demographics.
• Graceful failure: 'I can't help with that, here's an alternative'.
• Escalation paths for self-harm or emergency content.
• Content moderation API on inputs & outputs.

Syntax reference

Visual workflow / architecture:

Layers:
  prompt refusal rules
  + output moderation (toxicity, self-harm)
  + escalation pathways
  + bias audit

Real-world use

OpenAI's moderation endpoint, Anthropic's Constitutional AI, Google's safety filters — all baked into prompts at scale.

Best practices

• Layer defences — never rely on prompt alone.
• Escalate self-harm / emergencies to humans.
• Audit bias quarterly.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. Why layered safety?
• Q2. Self-harm escalation — design?
• Q3. Bias audits — how?
• Q4. Refusal UX?