Automation Bias

What is Automation Bias and Machine Bias?

Automation bias is an over-reliance on automated aids and decision support systems, while machine bias relates to the ways in which algorithms exhibit the bias of the algorithm used or their input data.

To prevent data bias, use a comprehensive and broad dataset reflective of all possible edge use cases. Choose the right learning model for the problem and identify the best model for a given situation. Make sure to use training data that is diverse and includes different groups. Monitor performance using real data and simulate real-world applications as much as possible when building algorithms.

By understanding automation bias and machine bias, you can make better decisions and improve the accuracy of your AI predictions.