Systems Engineering and Artificial Intelligence
暫譯: 系統工程與人工智慧
Lawless, William F., Mittu, Ranjeev, Sofge, Donald A.
相關主題
商品描述
This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams--where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy.
The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.商品描述(中文翻譯)
本書提供了一個廣泛的概述，探討系統工程設計哲學在架構由人工智慧（AI）、機器學習（ML）和人類組成的複雜系統中的好處，特別是在混亂環境中的應用。主要主題包括使用AI/ML進行系統的出現、驗證和驗證，以及人類系統整合，以發展穩健且有效的人機團隊——這些機器可能因其嵌入的AI/ML的複雜性而具有不同程度的自主性。各章節不僅描述了所學到的知識，還提出了必須回答的問題，以進一步推進自主科學的發展。
人類和機器作為團隊運作的科學需要來自社會科學、國內外法學、倫理與政策、社會學和心理學等多個學科的見解。社會科學提供了如何構建情境的資訊，當人類和機器相互依賴時，信任如何受到影響，以及人機團隊需要共享的解釋語言。國內外法學確定了非平凡人機失敗的法律責任，倫理標準塑造全球政策，而社會學則為理解跨文化的團隊規範提供了基礎。心理學的見解可能幫助我們理解，如果基於AI/ML的機器開始超越其人類隊友，並因此降低他們的價值或重要性，對人類的負面影響。本書邀請專業人士和好奇者共同見證自主科學的興起，開啟一個新的前沿。
作者簡介
Ranjeev Mittu is the Branch Head for the Information Management and Decision Architectures Branch within the Information Technology Division at the U.S. Naval Research Laboratory. The research within the branch is focused on visual analytics and augmented reality, immersive simulations, intelligent decision support applications, distributed systems and enterprise and service oriented architectures.
Donald A. Sofge is a Computer Scientist with the Naval Research Laboratory, Washington, DC, USA, where he leads the Distributed Autonomous Systems Group. He has extensive expertise in the application of artificial intelligence, machine learning, machine vision (and other forms of artificial perception), planning and control theory to robotic systems.
Thomas Shortell is a Systems Engineer at Lockheed Martin. He has been awarded the PhD degree by Drexel University.
Tom McDermott is a leader, educator, and innovator in multiple technology fields. He currently serves as Deputy Director of the Systems Engineering Research Center at Stevens Institute of Technology in Hoboken, NJ, as well as a consultant specializing in strategic planning for uncertain environments. He serves as Director of Strategic Integration on the Board of the International Council on Systems Engineering.
作者簡介(中文翻譯)
威廉·勞萊斯是數學與心理學的教授。勞萊斯博士已發表超過五十篇書籍章節和/或期刊文章，並在超過120篇經過同行評審的會議出版物中亮相。
蘭吉夫·米圖是美國海軍研究實驗室資訊科技部資訊管理與決策架構分部的部門負責人。該分部的研究專注於視覺分析和擴增實境、沉浸式模擬、智能決策支持應用、分散式系統以及企業和服務導向架構。
唐納德·A·索夫吉是美國華盛頓特區海軍研究實驗室的計算機科學家，負責領導分散式自主系統小組。他在人工智慧、機器學習、機器視覺（及其他形式的人工感知）、規劃與控制理論在機器人系統中的應用方面擁有豐富的專業知識。
托馬斯·肖特爾是洛克希德·馬丁公司的系統工程師。他獲得德雷克塞爾大學的博士學位。
湯姆·麥克德莫特是多個技術領域的領導者、教育者和創新者。他目前擔任新澤西州霍博肯史蒂文斯科技學院系統工程研究中心的副主任，並擔任專注於不確定環境的戰略規劃顧問。他還擔任國際系統工程理事會的戰略整合主任。
