fairness-in-ai

Vocabulary Word

Definition

'Fairness in AI' is like having an unbiased teacher who grades everyone's test accurately. It refers to the requirement for artificial intelligence to be unbiased and not discriminate against certain groups.

Examples in Different Contexts

In technology policy, 'fairness in AI' focuses on establishing guidelines and regulations that ensure AI technologies are used in ways that are equitable and just. A policy maker might note, 'Fairness in AI is a key consideration in drafting legislation to govern the use of artificial intelligence, aiming to protect all members of society.'

Practice Scenarios

Tech

Scenario:

We're training our image recognition AI with more diverse datasets. This is crucial to avoid any unintentionally biased results.

Response:

Exactly! We need to stick to the principles of fairness in AI by using a diverse range of datasets for training our image recognition AI.

Business

Scenario:

Our new machine learning model is designed to better predict customer churn. However, we must ensure that it's free of any discriminatory biases.

Response:

I absolutely agree. Let's conduct a fairness in AI audit of our prediction model to ensure that it doesn't discriminate customers.