John has been exposed to learning about the food habits of the people of a region, which makes him think that the people demonstrate poor food habits.

He has learned from hearsay, people’s secondhand experiences, the media, and the internet, and all of this information has shaped his opinion.

You can say that John’s learning has made his opinion biased, false, and even defamatory.

Now, people with real-world exposure to the food habits of that region find that much of what John believes is untrue and baseless.

When John finally visits the area for an extended period, eats their food, and experiences their food habits, he returns with a new perspective. He finds that his recent experiences challenge or update his old beliefs and thoughts. He has unlearned a lot of things that he knew.

In other words, new data has replaced old data.

AI unlearning happens in a similar manner. AI can be exposed to incorrect and biased datasets over some time and amplify its inaccurate knowledge over a period of time.