AWS Certified AI PractitionerResponsible AIHard
A credit scoring AI model is found to consistently give lower scores to individuals residing in certain zip codes, even when controlling for other financial factors. This leads to higher loan rejection rates for these individuals. This situation exemplifies which type of bias in AI?
- AAlgorithmic bias
- BSocietal bias
- CMeasurement bias
- DSelection bias
Show answer & explanationAnswer & explanation
Correct answer: A. Algorithmic bias
While the root cause might be societal bias reflected in data, the consistent lower scores specifically due to the AI model's processing of zip codes, leading to disparate impact, is an instance of algorithmic bias, where the algorithm itself perpetuates or amplifies existing biases.
Why the other options are wrong
- B. Societal bias is bias present in human behavior and society, which can be reflected in data but isn't the direct mechanism of the AI's unfair outcome itself.
- C. Measurement bias occurs when data collection methods systematically skew results, e.g., inaccurate sensors.
- D. Selection bias occurs when the data used to train the model is not representative of the population it will be applied to.
Algorithmic Bias
Algorithmic bias refers to systematic and repeatable errors in an AI system that lead to unfair or discriminatory outcomes, often as a result of biased training data, flawed model design, or inappropriate use.
- Can amplify existing societal biases.
- Leads to disparate impact on certain groups.
- Requires careful design, data, and evaluation to mitigate.
Memory trick: S.A.M.E. Bias in AI