G2TT
来源类型Report
规范类型报告
DOIhttps://doi.org/10.7249/RR-A929-1
来源IDRR-A929-1
Supporting the Royal Australian Navy's Strategy for Robotics and Autonomous Systems: Building an Evidence Base
Peter Dortmans; Joanne Nicholson; James Black; Marigold Black; Carl Rhodes; Scott Savitz; Linda Slapakova; Victoria M. Smith
发表日期2021-09-14
出版年2021
页码120
语种英语
结论

Seven objectives can drive the integration of RAS-AI into the current and planned Fleet

  • Maintain undersea advantage.
  • Grow mass on the surface.
  • Posture to gain a strategic advantage through data.
  • Coordinate through a common control system.
  • Normalise human-machine teaming to create effects.
  • Adapt acquisition processes to optimise investment in RAS-AI.
  • Mobilise academia and industry as part of the total maritime capability.

Given these objectives, Navy's strategy for RAS-AI must recognise key trends and requirements

  • AI will be increasingly pervasive and RAS capabilities increasingly numerous in the future operational environment.
  • Agile and distributed command, control and communications is necessary to support increasingly rapid decisionmaking.
  • Navy must adapt concepts, practices and training to optimise the complex array of interactions between humans and machines.
  • RAS-AI capabilities offer new mission sets that have the potential to change how effects are delivered.
  • Along with seaworthiness and cyberworthiness, trustworthiness is an essential attribute for future capabilities.
  • Although replacing crewed systems with uncrewed ones offers significant benefits, there are hidden costs that are not consistently recognised.
  • An evergreening acquisition approach is needed to ensure the rapid advances in RAS-AI technologies can be readily identified, developed and fielded.
摘要

The Royal Australian Navy has embarked on an ambitious plan to modernise its maritime capabilities to support Australia's defence strategy. The 2020 Defence Strategic Update calls for Australia to be ready to shape the strategic environment, deter actions against its interests and respond with military force when required.

,

Maritime capabilities feature heavily in the update, including those related to robotics, autonomous systems and artificial intelligence (RAS-AI). The Navy recently established the RAS-AI Directorate, giving it the responsibility of developing a maritime RAS-AI strategic roadmap to provide a path for developing and employing RAS-AI out to 2040.

,

In this report, the authors provide an evidence base to inform the Navy's thinking as it develops its RAS-AI Strategy 2040. Analysing a range of information captured through a literature review, environmental scan, interviews and workshops, the authors make observations that should shape the evolution of the strategy. A framework for the strategy, consisting of the future operational context, potential RAS-AI effects and a high-level technology roadmap, is developed and populated, and objectives for RAS-AI and implementation lines of effort are identified and discussed.

,

For the Navy's RAS-AI strategy to succeed, its implementation needs to be planned in a manner that recognises the evolving environment that the service will contend with over the next two decades.

目录
  • Chapter One

    Introduction

  • Chapter Two

    Australia's Strategic Environment to 2040

  • Chapter Three

    Technology Enablers and Transition for RAS-AI

  • Chapter Four

    Lessons for Developing RAS-AI Capabilities

  • Chapter Five

    Building a Strategic Roadmap for Maritime RAS-AI

  • Chapter Six

    Summary

  • Appendix A

    Literature Review Summary

  • Appendix B

    Stakeholder Interview Summaries

  • Appendix C

    U.S. Workshops

主题Artificial Intelligence ; Australia ; Autonomous Military Systems
URLhttps://www.rand.org/pubs/research_reports/RRA929-1.html
来源智库RAND Corporation (United States)
引用统计
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/524559
推荐引用方式
GB/T 7714
Peter Dortmans,Joanne Nicholson,James Black,et al. Supporting the Royal Australian Navy's Strategy for Robotics and Autonomous Systems: Building an Evidence Base. 2021.
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