This book constitutes the post-conference proceedings of the First International Workshop on Value Engineering in Artificial Intelligence, VALE 2023, held in Krakow, Poland, on September 30, 2023. The 16 full papers presented were carefully reviewed and selected. The papers have been grouped into four themes, addressing a number of research questions for each: I. Frameworks for norms and values: What are existing or new frameworks for norms and values and how can they be represented in AI systems in order to make these systems norm- and value-aware? II. Detection of moral values: Given an existing AI system, how can we figure out whether its behavior is aligned with human values? III. Learning and engineering of value-aligned policies: How can policies for implementing norms and values be acquired or designed? IV. Implementation of norms: How can norms be implemented in concrete AI applications?

Artificial Intelligence in Engineering Design is a three volume edited collection of key papers from the field of artificial intelligence and design, aimed at providing a description of the field, and focusing on how ideas and methods from artifical intelligence can help engineers in the design of physical artifacts and processes. The book surveys a wide variety of applications in the areas of civil, mechanical, chemical, VLSI, electrical, and computer engineering. The contributors are from leading academic computer-aided design centers as well as from industry.

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.

Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence

Artificial Intelligence in Process Engineering aims to present a diverse sample of Artificial Intelligence (AI) applications in process engineering. The book contains contributions, selected by the editors based on educational value and diversity of AI methods and process engineering application domains. Topics discussed in the text include the use of qualitative reasoning for modeling and simulation of chemical systems; the use of qualitative models in discrete event simulation to analyze malfunctions in processing systems; and the diagnosis of faults in processes that are controlled by Programmable Logic Controllers. There are also debates on the issue of quantitative versus qualitative information. The control of batch processes, a design of a system that synthesizes bioseparation processes, and process design in the domain of chemical (rather than biochemical) systems are likewise covered in the text. This publication will be of value to industrial engineers and process engineers and researchers.

This book bridges the gap between the commoner's world and the AI technical world. This easy read book is suitable for anyone who wants to dig deeper into the practical aspects and explore the value of AI and build intelligent products for real-world use cases. You will learn about:- Where can AI or intelligent machines add Value?- What real-world problems can be solved and what problems are harder to solve using existing AI algorithms,- A brief explanation of the most applicable algorithms and for which use cases they are most suitable,- How to engineer and architect AI systems, - How to overcome some of the major challenges with gathering the data, developing the product, and making users adopt the product. The above steps are explained through use cases taken from banking, insurance, energy, sales, healthcare, and other sectors. Almost all the knowledge and use cases shared in this book have been gained during my many years (almost 10 years actually) spent working and researching various AI-related products and are based primarily on my personal experiences. However, this is not a course book on Artificial Intelligence (AI), or a comprehensive literature review on AI or its use cases