The neural network was trained on a dataset of millions of examples, allowing it to make highly accurate predictions. However, the system still struggled with bias, as it had not been thoroughly vetted for ethical considerations. In order to mitigate this issue, the team implemented a fairness algorithm to ensure equitable treatment of all inputs.
