Whose experience becomes the default?

Suppose our invitation says, "Book through the app. Everyone has a smartphone."

That assumption could exclude neighbours who cannot use the app. A smooth sentence can hide a narrow idea of who the audience is.

Here, bias means a skewed or unfair pattern in an answer. It is different from the numerical bias used in a neuron.

Training text represents people and languages unevenly. Some communities have abundant published material; others have knowledge passed on orally or in languages with little digitised text. Models can learn stereotypes as well as gaps.

People also choose what data to collect and filter, how to train for preferred behaviour, and which product rules to apply. Those decisions can change the resulting biases.

For our invitation, ask whose needs the draft assumes. Confirm the actual booking options with the organiser before promising a telephone number or a walk-in option.