Definition

AI ethics is about making good choices when building or using AI. It asks questions like: Is this fair? Is it safe? Will it hurt someone? Ethical AI is designed to protect people, avoid bias, and do the right thing.

Example

“AI ethics helps stop a hiring algorithm from being unfair to certain groups.”

How It’s Used in AI

AI ethics is used in how systems are built, tested, and deployed. It covers things like data privacy, bias, transparency, and who takes responsibility if something goes wrong. Companies and governments use ethical guidelines to avoid harm and protect people.

Brief History

The idea of ethics in tech goes back decades, but AI ethics gained major attention in the 2010s with the rise of facial recognition, algorithmic bias, and surveillance tools. Thinkers like Timnit Gebru and groups like the AI Ethics Lab helped lead the conversation.

Key Tools or Models

Tools include AI fairness checkers, bias detection models, and ethical AI frameworks from Google, Microsoft, and the OECD. LLMs like Claude and ChatGPT are often fine-tuned with ethical guardrails.

Pro Tip

Ethical AI isn't just a feature—it's a responsibility. Build with care, test with purpose, and stay transparent about what your AI can and can’t do.