Artificial Intelligence for Design and Process Science

This book provides a focused overview of what role artificial intelligence (AI) plays on the design and process of system development and perspectives on making it more and more relevant and beneficial for our society. It covers topics like large language models, generative AI, intelligenticism, communication dynamics representation, feature selection, smart design and social wellbeing, and it demonstrates the general applicability of AI to various problems in transdisciplinary domains.

The book is a Festschrift for two lifetime fellows of the Society for Design and Process Science (SDPS), Bernd Kramer and Murat Tanik, in order to appreciate their work and honor them for lifelong dedication to design and process science. It is based on a special honorary event held at the AI in Design and Process Science (AIDPS) workshop during the 2024 Hawaii International Conference in System Sciences (HICSS).

Overall, this book is a source of inspiration for everybody in academia and research sectors working on the vision of creating a strong, fruitful and creative community of design and process science for social wellbeing through the development of AI technologies.

AI for Social Good Education through a Culturally Responsive Pedagogy.- A Communication Dynamics Representation of Electron Energy of S-orbitals in Hydrogen-like Atoms. Creativity and AI.- Demystifying Computer Science: A Sentence Transformers & Neural Networks-Powered Chatbot.- A Revolutionary Artificial Intelligence Framework for a Business Value-Centric Living Laboratory.- The Power of Smart Design: How Intelligence Shapes Custom Digital Products.- Compound Noun Phrase Similarity in Bidirectional Transformer Language Models.- A Reinforcement Learning Framework for Transferable Neural Architecture Optimization.- Learning Shortcuts: On the Misleading Promise of NLU in Language Models.- The Philosophy of Intelligenticism and Its Implications on Potential Future Directions for IS Research and Practice.- Introducing Feature Selection before Propositionalization.

Sang Suh is a Regents Professor of Texas A&M University System and a Professor of Computer Science at Texas A&M University - Commerce. His primary research interests are in the areas of artificial general intelligence, human computer interaction, data mining, knowledge and data engineering, machine reasoning, and computing education. He has over 30 years of research experience and published 6 books and more than 150 research papers in the aforementioned areas.