34.5. Bias and Fairness in Algorithms

Try these first

1. 1.

   What is algorithmic bias?

   Hint

   Think about how data influences AI decisions.

2. 2.

   Name one way to reduce algorithmic bias.

   Hint

   Consider types of data used in training.

3. 3.

   What is the main issue with algorithmic bias?

   • It results from too much data
   • It leads to unfair treatment
   • It improves decision accuracy

   Hint

   Think about the effect of data bias.

4. 4.

   True or False: Using diverse datasets can help reduce bias in AI.

   • True
   • False

   Hint

   Consider the variety of input data used.

5. 5.

   Evaluate a real-world AI application in terms of its risk of algorithmic bias. Propose improvements.

   Hint

   Identify cases like facial recognition systems and their downsides.

6. 6.

   Design a bias-detection algorithm for a new AI product focused on recruitment. What metrics will you use, and how will you implement it?

   Hint

   Consider tracking hiring rates across demographics.