| Abstract |
The different sets of regulations existing for different agencies within the government make the task of creating AI enabled solutions in government difficult. Regulatory restrictions inhibit sharing of data across different agencies, which could be a significant impediment to training AI models. We discuss the challenges that exist in environments where data cannot be freely shared and assess technologies which can be used to work around these challenges. We present results on building AI models using the concept of federated AI, which allows creation of models without moving the training data around. |