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CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Artificial Intelligence - Introduction and Basics

A Mumbai lender uses a machine-learning model to approve personal loans. Audit shows the model rejects applicants from certain pin codes at much higher rates, because past approval data reflected historical lending patterns. Which AI risk does this best illustrate?

The scenario shows algorithmic bias. The model learned from historical approval data that already reflected skewed lending patterns, so it reproduces discriminatory outcomes against certain pin codes. It is not a security attack or a hardware or network problem.

  1. AAlgorithmic bias arising from skewed training dataCorrect
  2. BModel inversion by an external attacker
  3. CHardware failure in the processing server
  4. DLatency caused by insufficient network bandwidth

Explanation

The model learned from historical decisions that were themselves skewed, so it reproduces the pattern. This is algorithmic (data) bias. Model inversion is a privacy attack on a model, which is not described here.

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