Root Out Bias at Every Stage of Your AI-Development Process

Bias mitigation is a fairly technical process, where certain techniques can be deployed depending on the stage in the machine learning pipeline: pre-processing, in-processing and post-processing. Each offers a unique opportunity to reduce underlying bias and create a technology that is honest and fair to all. Leaders must make it a priority to take a closer look at the models and techniques for addressing bias in each of these stages to identify how best to implement the models across their technology. Ultimately, there is no way to completely eliminate AI bias, but it’s the industry’s responsibility to collaborate and help mitigate its presence in future technology. With AI playing an increasing important role in our lives, and with so much promise for future innovation, it is necessary that we acknowledge and address prejudice in our technology, as well as in our society.