Research and Education in Equitable AI and Machine Learning: Cybersecurity Implications for National

Abstract

As the U.S. Military future battlefield strategies invoke enhanced Artificial Intelligence (AI) and Machine Learning (ML), cybersecu,rity risks will abound. The future performance of engagements will rely on the most accurate, effective, and efficient strategies a,nd implementations of trustworthy AI/ML, especially in cybersecurity. However, algorithmic bias in AI/ML cybersecurity systems may e,xist due to insufficient diversity of thought. The primary objective of this work is to address a critical DoD need for research in,building diverse knowledge bases related to equitable and trustworthy AI/ML, especially with respect to cybersecurity. The National,Center for Equitable Artificial Intelligence and Machine Learning at Morgan State University will research the development of new fo,rmal standards, and best practices in the areas of data preparation, feature engineering, model training, and deployment. Work will,be conducted to formalize testing protocols for new trustworthy AI innovations to mitigate potential algorithmic bias. Another objec,tive of this work is to provide education and research opportunities for students and increase the number of graduates in these key,areas of national importance.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 03, 2022
Source ID
N000142212716

Entities

People

  • Willie May

Organizations

  • Morgan State University
  • Office of Naval Research
  • United States Navy

Tags

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks
  • Cyber