The different sets of regulations existing for differ-ent agencies within the government make the task of creating AI enabled solutions in government dif-ficult. Regulatory restrictions inhibit sharing of da-ta 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 tech-nologies which can be used to work around these challenges. We present results on building AI models using the concept of federated AI, which al-lows creation of models without moving the training data around.
@article{arxiv.1809.10036,
title = {Federated AI for building AI Solutions across Multiple Agencies},
author = {Dinesh Verma and Simon Julier and Greg Cirincione},
journal= {arXiv preprint arXiv:1809.10036},
year = {2018}
}
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Presented at AAAI FSS-18: Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA