Abstract

While the public views the federal government as a monolith, in truth United States departments and agencies often function independently. Due to privacy regulations and statutory reasons, they often cannot share data about individuals with each other. Yet, such data collaboration would facilitate the development of artificial intelligence models to significantly improve the provision of social services. We argue that a particular privacy-enhancing technology (split learning operating over vertically partitioned data), together with data governance through metadata supply chains, can be part of larger sociotechnical systems that can improve life for the most vulnerable among us.

Original languageEnglish (US)
Title of host publicationProceedings - 2024 IEEE International Conference on Big Data, BigData 2024
EditorsWei Ding, Chang-Tien Lu, Fusheng Wang, Liping Di, Kesheng Wu, Jun Huan, Raghu Nambiar, Jundong Li, Filip Ilievski, Ricardo Baeza-Yates, Xiaohua Hu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2294-2296
Number of pages3
ISBN (Electronic)9798350362480
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Big Data, BigData 2024 - Washington, United States
Duration: Dec 15 2024Dec 18 2024

Publication series

NameProceedings - 2024 IEEE International Conference on Big Data, BigData 2024

Conference

Conference2024 IEEE International Conference on Big Data, BigData 2024
Country/TerritoryUnited States
CityWashington
Period12/15/2412/18/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Modeling and Simulation

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