Federated AI for building AI Solutions across Multiple Agencies

Abstract

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.

arXiv commentPresented at AAAI FSS-18: Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA

References in corpus (1)

• Adaptive Federated Learning in Resource Constrained Edge Computing Systems

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