Transitioning Science to Practice

Abstract

Many of the significant National Security challenges of our near future will require a new approach to collaborative problem solving across many specialized disciplines to address new and yet unforeseen challenges or opportunities. To effectively address these challenges, artificial intelligence (AI) technologies such as machine learning (ML), deep learning (DL), etc., are being developed. The development of AI/ML systems requires a shift in how research and development (R and D) is traditionally developed. New development processes need to support the understanding that research is iterative, technology insertion is incremental, and the final capability is evolutionary. In addition, AI/ML capabilities development requires a level of cross disciplinary research and involves some intersection -fusion - of technology and emergent scientific discovery. There needs to be a concerted effort for facilitated bridging of the respective research and development trajectories such that the corresponding advances may be applied in concert to achieve a desired outcome. This paper proposes a new systems engineering/research Vortical model concept as a more effective approach for R and D of complex AI/ML enabled capabilities. The Vortical model extends the foundational and well characterized spiral systems engineering and development model to incorporate the agility and flexibility of agile systems engineering methods. Additionally, the Vortical model introduces an iterative framework through which emerging advances in research outcomes are effectively demonstrated and validated for integration, as new capabilities, at varying technology insertion points or windows of opportunity. Our goal is to encourage adoption of best practices that facilitate the transfer of knowledge from emerging research activities for more effective and more rapid adoption and integration into the ICs mission capabilities.

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Document Details

Document Type
Technical Report
Publication Date
Aug 30, 2023
Accession Number
AD1211663

Entities

People

  • Rosa R. Heckle
  • Stuart D. Harshbarger

Organizations

  • MITRE Corporation

Tags

DTIC Thesaurus Topics

  • Agile Software Development
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Best Practices
  • Character Recognition
  • Computer Languages
  • Computer Vision
  • Computers
  • Engineering
  • Language
  • Machine Learning
  • Machine Translation
  • Named Entity Recognition
  • Natural Language Processing
  • Software Development
  • Spiral Development
  • Systems Engineering

Fields of Study

  • Computer science

Readers

  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Maritime Combat Support and Expeditionary Logistics.
  • Organizational Process Management (OPM).

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy