Concepts

AI Safety

Research and practices focused on ensuring AI systems behave as intended and don't cause unintended harm to humans or society.

What is AI Safety?

AI Safety is the field focused on making sure AI systems do what you want them to do, without causing unexpected harm.

It covers everything from preventing biased outputs and data leaks to ensuring advanced models don't develop dangerous behaviors as they scale. The field gained mainstream attention in 2023 when AI lab CEOs started publicly discussing existential risks.

For builders, this means testing your AI features for edge cases, monitoring for harmful outputs, and implementing guardrails before shipping. Most teams start with content filtering, rate limiting, and logging all AI interactions.

Key frameworks include NIST's AI Risk Management Framework and the White House Executive Order on AI. Both the US and UK established AI Safety Institutes in 2023.

Good to Know

Covers both near-term risks like bias and data leaks, and long-term concerns about advanced AI behavior
The US AI Safety Institute and UK AI Safety Institute were both established in 2023
Key areas include AI alignment (making sure AI does what you want), robustness testing, and transparency
Major AI labs now have dedicated safety teams that test models before public release
Practical safety measures include content filtering, rate limiting, monitoring outputs, and adversarial testing

How Vibe Coders Use AI Safety

1
Testing your AI chatbot with adversarial prompts before launch to catch harmful outputs
2
Adding content filters to your image generation feature to block inappropriate requests
3
Logging all AI interactions so you can audit for bias or safety issues
4
Implementing rate limits on your AI API to prevent abuse and unexpected costs

Frequently Asked Questions

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