When you see an AI answer,

do you think about

the data behind it?

AI results are affected by data.

If the data has problems,

the result may also have problems.

For example:

• the data may be biased
• the source may be unclear
• the information may be old
• there may be copyright issues
• personal or sensitive data may be used

In this episode,

we talk about

Design and Development: Data Handling (A.7.2)

in AIMS.

We explain why organizations should check

data quality,

data bias,

and data sources.

This episode helps you notice

risks that are easy to miss.