AI – It all begins with the concept of “data in, data out.” 

Know

If biased data is used to train AI models, the resulting outputs will inevitably reflect those biases. 

Machine learning algorithms have the power to amplify these biases, and unless we actively check for and address them, we risk perpetuating societal prejudices unintentionally. 

This issue becomes especially significant when AI is employed in decision-making processes, such as hiring, lending or criminal justice. 

Source: Mueller, M. (n.d.). Council Post: The Ethics Of AI: Navigating Bias, Manipulation And Beyond. Forbes. https://www.forbes.com/sites/forbestechcouncil/2023/06/23/the-ethics-of-ai-navigating-bias-manipulation-and-beyond/