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AI Ethics

What Are AI Ethics? The Simple Definition

The study and development of principles and guidelines to ensure that AI is designed, developed, and deployed in a manner that is beneficial, fair, transparent, and respects human rights.

The Technical Definition

AI ethics refers to the moral principles and guidelines that should be considered when developing, deploying, and using artificial intelligence technologies.

It encompasses a broad range of issues including transparency, fairness, accountability, privacy, security, and the potential impacts on society and individuals. The goal of AI ethics is to ensure that AI technologies are used in a way that is beneficial to society and does not cause harm or unfairly disadvantage any particular group of people.

Explain It Like I’m Five

Imagine if you had a super-smart toy robot that could do a lot of things on its own. “AI Ethics” is like teaching that robot to always play nicely and fairly, to be kind to everyone, and not to cheat or hurt others.

It’s like the rules we follow when we play games, so everyone is happy and safe. It makes sure our robot friend doesn’t make bad choices!

Use It At The Water Cooler

How to use “AI ethics” in a sentence at work:

“To maintain public trust in our company’s technology, understanding and applying AI ethics is crucial.”

Related Terms

AI Compliance, Responsible AI Standards

Additional Resources

What Is AI Governance? Jargon-Free With Examples [2025]

What Is AI Governance? Jargon-Free With Examples [2025]

Discover the secret to simplifying AI governance. Written in plain language, we dive into the top 5 insights everyone should know about AI governance and showcase how AI governance tools, like FairNow, are evolving to meet compliance needs. Our guide offers a refreshing perspective without the jargon. Learn how to make AI governance straightforward and empowering for your organization.

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Part 2: ISO 42001 Playbook

Part 2: ISO 42001 Playbook

Part 2 of the ISO 42001 Playbook explores how organizations move from AI governance principles to certification readiness. Learn how to structure controls, assess system-level risk, and align AI management practices with ISO 42001 Certification requirements.

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