Biologically Inspired Cognitive Architectures 2024
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Biologically Inspired Cognitive Architectures 2024
Author: Alexei V. Samsonovich
language: en
Publisher: Springer Nature
Release Date: 2024-12-09
This book reports on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, including artificial intelligence, linguistics, neuro- and social sciences, psychology and philosophy of mind, among others. The chapters are based on contributions presented at the 2024 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence (the 15th Annual Meeting of the BICA Society, BICA*AI 2024), organized in collaboration with the 17th Conference on Artificial General Intelligence (AGI 2024) and held on August 13-16, 2024, in Seattle, WA, USA. They cover emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, this book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.
Artificial Intelligence Applications and Innovations
Author: Ilias Maglogiannis
language: en
Publisher: Springer Nature
Release Date: 2025-06-21
This four-volume set constitutes the proceedings of the 21st IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2025, which was held in Limassol, Cyprus, during June 2025. The 123 full papers and 7 short papers were presented in this volume were carefully reviewed and selected from 303 submissions. They focus on ethical-moral AI aspects related to its Environmental impact, Privacy, Transparency, Bias, Discrimination and Fairness.
AI Use in Social Sciences
Artificial intelligence (AI)-based technologies are significantly impacting various social science disciplines. With the large data sets that are analyzed, technologies such as machine learning (ML), natural language processing (NLP), and neural networks are particularly useful in disciplines such as sociology, psychology, political science, anthropology, and economics. Thus, social science education and research benefit by the ability of AI to effectively analyze data sets, predict, and increase interactivity. However, ethical concerns regarding privacy and algorithm bias cause some to be resistant to adopting the use of AI in social science fields. Thus, it is crucial to consider the ethical consequences while exploring the multifaceted impact of AI on education, research, and social sciences. AI Use in Social Sciences explores the opportunities and challenges AI provides to the field of social sciences. It presents practical applications of AI and the societal implications they have. Covering topics such as, philosophy teaching, economic policy, and unified theory of acceptance and use of technology (UTAUT), this book is an excellent resource for social scientists, teachers, ethicists, policymakers, researchers, professionals, scholars, academicians, and more.