How can ai discrimination be prevented?

After all, people generate biased data, and humans and algorithms created by humans are the ones who verify the data to detect and correct biases. However, we can combat AI bias by testing data and algorithms and using best practices to collect data, use it, and create AI algorithms. MEPs urge to avoid the use of biased data that reflects existing gender inequality or discrimination when training AI. Instead, ethical and inclusive data sets should be developed, with the help of stakeholders and civil society, to be used during the “deep learning process”.