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AI Transparency

What Is AI Transparency? The Simple Definition

Transparency of AI systems involves informing stakeholders about the system’s objectives and processes. This could include details about how the model was trained, what data is used, and how risks are mitigated.

The Technical Definition

AI transparency refers to the degree to which the inner workings and decision-making processes of an artificial intelligence system can be examined, understood, and verified by humans, particularly by those responsible for its design, operation, and oversight.

It involves providing insights into the data, algorithms, and logic that drive AI systems, making them less like black boxes and more open to scrutiny.

Explain It Like I’m Five

Okay, imagine AI is like a magic box that makes predictions or decisions. AI transparency is like having a clear window on the box so that we can see what’s happening inside.

It helps us understand how and why the AI does what it does, like showing its tricks. This way, we can make sure it’s fair, safe, and trustworthy, just like when we watch a magician’s tricks and want to know how they work.

Use It At The Water Cooler

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

“Hey team, when we use AI for customer recommendations, let’s maintain AI transparency so that customers feel like they’re getting advice from a friendly expert rather than a mysterious machine.”

Related Terms

Machine Learning

Additional Resources

New York DFS AI Regulation, What Insurers Need To Know

New York DFS AI Regulation, What Insurers Need To Know

A must-read for insurance professionals. Instead of combing through pages and pages of legislation, this overview highlights everything you need to know. Understand fairness principles, and what is required for regulatory compliance for insurers licensed in New York. Stay informed about the best practices in AI governance to prevent discrimination and ensure transparency in insurance processes.

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