What “Explainable AI (XAI)” means

What is explainable AI, explained simply

Explainable AI (XAI) refers to systems designed to make their decisions easier to understand.

Instead of just giving an answer, the system shows how it reached that answer. That might mean highlighting which factors mattered most, or offering a reason you can follow.

For example, a credit decision system might explain that income level and repayment history were the main reasons behind an outcome.

This becomes more important when decisions affect people. Without explanation, it’s harder to trust the result or challenge it. With it, you can at least see the logic, even if you don’t agree with it.

The trade-off is that more explainable systems are not always the most accurate. Some of the most powerful AI models are also the hardest to interpret.

So the question becomes: do we prioritise understanding, or performance?