Evaluating the Effectiveness of Artificial Intelligence Systems in Intelligence Analysis PDF Download
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Author: Daniel Ish
Publisher:
ISBN: 9781977407252
Category : Computers
Languages : en
Pages : 0
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Book Description
The authors develop methods for assessing the impact of deploying artificial intelligence (AI) systems to support intelligence missions.
Author: Daniel Ish
Publisher:
ISBN: 9781977407252
Category : Computers
Languages : en
Pages : 0
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Book Description
The authors develop methods for assessing the impact of deploying artificial intelligence (AI) systems to support intelligence missions.
Author: Tadeusz A. Grzeszczyk
Publisher: Taylor & Francis
ISBN: 1040094414
Category : Business & Economics
Languages : en
Pages : 89
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Book Description
Although some people had doubts about the usefulness of such solutions in the past, artificial intelligence (AI) plays a growing role in modern business. It can be expected that the interest in it will also lead to an increase in support for the planning, evaluation, and implementation of projects. In particular, the proper functioning of multifaceted evaluation methods has a crucial impact on the appropriate planning and execution of various projects, as well as the effective achievement of the organization’s goals. This book offers a presentation of the complex problems and challenges related to the development of AI in project management, proposes an integrated approach to knowledge-based evaluation, and indicates the possibilities of improving professional practical knowledge in this field. The unique contribution of this book is to draw attention to the possibilities resulting from conducting transdisciplinary research and drawing on the rich achievements in the field of research development on knowledge-based systems that can be used to holistically support the processes of planning, evaluation, and project management. The concept of the integrated approach to knowledge-based evaluation is presented and developed as a result of drawing inspiration mainly from the systems approach, generative AI, and selected mathematical models. Presented in a highly accessible manner, the book discusses mathematical tools in a simple way, which enables understanding of the content by readers across broad subject areas who may be not only participants in specialist training and university students but also practitioners, consultants, or evaluators. This book will be a valuable resource for academics and upper-level students, in particular, across project management-related fields, and of great interest to all those looking to understand the challenges and effectiveness of AI in business.
Author: Waymond Rodgers
Publisher: Bentham Science Publishers
ISBN: 9815049550
Category : Computers
Languages : en
Pages : 329
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Book Description
This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.
Author: Matthias Rudolph
Publisher: GRIN Verlag
ISBN: 3346324214
Category : Computers
Languages : en
Pages : 130
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Book Description
Master's Thesis from the year 2020 in the subject Computer Sciences - Artificial Intelligence, grade: 1,3, Friedrich-Alexander University Erlangen-Nuremberg (Wirtschaftsinformatik), language: English, abstract: The thesis aims to analyze this field of tension between the benefits and risks caused by the introduction of AI into recruiting based on a systematic analysis of academic publications. To the knowledge of the author, neither a literature review on ethical challenges of AI-based recruiting tools nor an overview addressing application fields and the resulting ethical risks has been published so far. Consequently, this thesis aims to close this research gap by disclosing how AI technologies affect the recruiting process and how ethical challenges arising from the implementation of AI-based tools are addressed in the same publications. Consequently, research question (RQ) one (RQ1) and RQ two (RQ2) can be derived: Which AI technologies are applied in the field of recruiting, and how do they influence the recruiting process? Which major ethical challenges arise from the introduction of AI into recruiting, and how are these challenges addressed by the proposed AI-based tools? Addressing these two RQs, the remainder of this thesis is structured as follows. Chapter 2 classifies recruiting and its subprocesses as a part of Human Resources (HR), establishes a common understanding of AI and machine learning (ML) algorithms relevant in AI-based recruiting tools, and derives major ethical challenges with a focus on the ethical principles fairness and transparency. In chapter 3, the methodical approach used for identifying and selecting relevant literature is described. Chapter 4 answers both RQs, based on the AI-based recruiting tools included in the literature set. In turn, the first part of the analysis focuses on analyzing how the needs raised through traditional recruiting means are addressed by AI-based recruiting tools, also touching base on the underlying technologies. The second part addresses if and, where applicable, how these publications incorporate fairness and transparency. Subsequently, chapter 5 discusses the main findings of the analysis of the literature set and provides implications for theory and practice, followed by a brief conclusion and the outlining of limitations and future research fields in chapter 6.
Author: J. Sabater-Mir
Publisher: IOS Press
ISBN: 1643680153
Category : Computers
Languages : en
Pages : 446
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Book Description
Artificial intelligence has now become an indispensible tool at the centre of problem-solving in a huge range of digital technologies, and remains one of the most vibrant topics for discussion and research. This book presents a compilation of the articles presented at the 22nd (2019) edition of the International Conference of the Catalan Association for Artificial Intelligence (CCIA), held in Mallorca, Spain, from 23 – 25 October 2019. This annual conference is an international event that serves as a meeting point for researchers into artificial intelligence based in the area of the Catalan speaking territories and for researchers from around the world. The book is divided into 8 sections. The first contains summaries of the 3 invited talks presented at the conference: ‘New methods for fusing information and the computational brain’, by Javier Fernandez; ‘From correlation to imagination: Deep generative models for artificial intelligence’ by Joan Serrà; and ‘Explainable AI’ by Anna Monreale. The remaining 7 sections contain 47 papers covering ethics and E-governance; machine learning; constraints and SAT, optimization and fuzzy; data science, recommender systems and decision support systems; agent-based and multi-agent systems; computer vision; and sentiment analysis and text analysis. The book provides an overview of the latest developments in the field, and as such will be of interest to all those whose work involves the study and application of artificial intelligence.
Author: Christophe Kolski
Publisher: Springer Nature
ISBN: 3031539575
Category :
Languages : en
Pages : 211
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Book Description
Author: Habib, Maki K.
Publisher: IGI Global
ISBN: 1522577947
Category : Education
Languages : en
Pages : 264
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Book Description
Artificial Intelligence (AI) serves as a catalyst for transformation in the field of digital teaching and learning by introducing novel solutions to revolutionize all dimensions of the educational process, leading to individualized learning experiences, teachers playing a greater role as mentors, and the automation of all administrative processes linked to education. AI and machine learning are already contributing to and are expected to improve the quality of the educational process by providing advantages such as personalized and interactive tutoring with the ability to adjust the content and the learning pace of each individual student while assessing their performance and providing feedback. These shifts in the educational paradigm have a profound impact on the quality and the way we live, interact with each other, and define our values. Thus, there is a need for an earnest inquiry into the cultural repercussions of this phenomenon that extends beyond superficial analyses of AI-based applications in education. Revolutionizing Education in the Age of AI and Machine Learning addresses the need for a scholarly exploration of the cultural and social impacts of the rapid expansion of artificial intelligence in the field of education including potential consequences these impacts could have on culture, social relations, and values. The content within this publication covers such topics as AI and tutoring, role of teachers, physical education and sports, interactive E-learning and virtual laboratories, adaptive curricula development, support critical thinking, and augmented intelligence and it is designed for educators, curriculum developers, instructional designers, educational software developers, education consultants, academicians, administrators, researchers, and professionals.
Author: Cornelius T. Leondes
Publisher: CRC Press
ISBN: 1420040812
Category : Technology & Engineering
Languages : en
Pages : 2400
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Book Description
Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study examples of successful practical techniques and solutions for diverse applications ranging from robotic systems to speech and signal processing, database management, and manufacturing.
Author: Osonde A. Osoba
Publisher: Rand Corporation
ISBN: 0833097636
Category : Computers
Languages : en
Pages : 45
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Book Description
Machine learning algorithms and artificial intelligence influence many aspects of life today. This report identifies some of their shortcomings and associated policy risks and examines some approaches for combating these problems.
Author: Hong Jiao
Publisher: IAP
ISBN: 1641139536
Category : Computers
Languages : en
Pages : 223
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Book Description
The general theme of this book is to present the applications of artificial intelligence (AI) in test development. In particular, this book includes research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing. By utilizing artificial intelligence, the efficiency of item development, test form construction, test delivery, and scoring could be dramatically increased. Chapters on automated item generation offer different perspectives related to generating a large number of items with controlled psychometric properties including the latest development of using machine learning methods. Automated scoring is illustrated for different types of assessments such as speaking and writing from both methodological aspects and practical considerations. Further, automated test assembly is elaborated for the conventional linear tests from both classical test theory and item response theory perspectives. Item pool design and assembly for the linear-on-the-fly tests elaborates more complications in practice when test security is a big concern. Finally, several chapters focus on computerized adaptive testing (CAT) at either item or module levels. CAT is further illustrated as an effective approach to increasing test-takers’ engagement in testing. In summary, the book includes both theoretical, methodological, and applied research and practices that serve as the foundation for future development. These chapters provide illustrations of efforts to automate the process of test development. While some of these automation processes have become common practices such as automated test assembly, automated scoring, and computerized adaptive testing, some others such as automated item generation calls for more research and exploration. When new AI methods are emerging and evolving, it is expected that researchers can expand and improve the methods for automating different steps in test development to enhance the automation features and practitioners can adopt quality automation procedures to improve assessment practices.
