Explainable AI
Explainable Artificial Intelligence
Technology that explains, in terms people can understand, why an AI reached a decision or prediction.
In Simple Terms
Explainable AI is technology that shows you the reasoning and process behind an AI's answer. For example, when an AI rejects a bank loan application, it's used to show people why the request was denied. This lets people check an AI's judgment and feel confident about using it.
Behind the Name
The name simply combines "Explainable" with "AI" — the whole idea is to make an AI's reasoning something people can follow, instead of leaving it as an unexplained "black box." It's often shortened to "XAI."
Take a Closer Look!
Explainable AI is technology that, when an artificial intelligence reaches a particular conclusion or prediction, explains the reasoning behind that judgment in a way people can understand.
Older AI models tended to be so complex that nobody could tell why they arrived at a given answer — a state often called a "black box."
That's why systems were developed to show, often through graphs, which data an AI weighted most heavily when making its decision.
For example, in healthcare, when an AI detects a disease, showing doctors which part of a medical image it based its judgment on helps increase confidence in the diagnosis.
It's also used in important money-related situations, such as financial loan screening, to help confirm that an AI's decision is sound.
Put simply, it's like a translator that lets you peek inside an AI's "mind" and get an explanation you can actually accept.
That way, people don't just have to blindly trust an AI's decisions — they can trust it and work alongside it instead.