Algorithmic Bias in AI

Machine learning algorithms are dependent on significantly large datasets. Algorithmic bias occurs when, algorithm designs or the data development process precursor (collection, labeling, cleaning) to train algorithms, result in unfair outcomes that show bias to a select group of individuals at the expense of other groups.

Algorithmic bias is found everywhere online including search engine results, social media platforms,  recruitment tools, digital advertising, facial recognition technology, criminal justice software and more.

These companies offer products, services, data sets and tools that use GDPR based audit frameworks or statistical methods to identify and test for hidden biases in algorithms. Additionally, they may offer diverse datasets to facilitate AI application outcomes that are fair and equal for ALL users.

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