Artificial Intelligence
Artificial intelligence (AI) research focuses on creating systems capable of performing tasks that typically require human intelligence, with current efforts concentrating on improving model alignment with human values, enhancing transparency and accountability in AI systems, and mitigating risks associated with bias and malicious use. Prominent approaches involve large language models (LLMs), deep learning architectures like nnU-Net, and reinforcement learning techniques, often applied within specific domains such as healthcare, cybersecurity, and scientific research. The widespread adoption of AI across diverse fields necessitates rigorous investigation into its ethical implications, safety, and societal impact, driving ongoing research to develop more robust, reliable, and responsible AI systems.
Papers
Learning Random Numbers to Realize Appendable Memory System for Artificial Intelligence to Acquire New Knowledge after Deployment
Kazunori D Yamada
Navigating the United States Legislative Landscape on Voice Privacy: Existing Laws, Proposed Bills, Protection for Children, and Synthetic Data for AI
Satwik Dutta, John H. L. Hansen
AI-Driven Healthcare: A Survey on Ensuring Fairness and Mitigating Bias
Sribala Vidyadhari Chinta, Zichong Wang, Xingyu Zhang, Thang Doan Viet, Ayesha Kashif, Monique Antoinette Smith, Wenbin Zhang
Business and Regulatory Responses to Artificial Intelligence: Dynamic Regulation, Innovation Ecosystems and the Strategic Management of Disruptive Technology
Mark Fenwick, Erik P. M. Vermeulen, Marcelo Corrales Compagnucci
A Generic Review of Integrating Artificial Intelligence in Cognitive Behavioral Therapy
Meng Jiang, Qing Zhao, Jianqiang Li, Fan Wang, Tianyu He, Xinyan Cheng, Bing Xiang Yang, Grace W. K. Ho, Guanghui Fu
Integrating Cognitive AI with Generative Models for Enhanced Question Answering in Skill-based Learning
Rochan H. Madhusudhana, Rahul K. Dass, Jeanette Luu, Ashok K. Goel
Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance
Mohammmad Tahaei, Daricia Wilkinson, Alisa Frik, Michael Muller, Ruba Abu-Salma, Lauren Wilcox
Human-artificial intelligence teaming for scientific information extraction from data-driven additive manufacturing research using large language models
Mutahar Safdar, Jiarui Xie, Andrei Mircea, Yaoyao Fiona Zhao
Understanding XAI Through the Philosopher's Lens: A Historical Perspective
Martina Mattioli, Antonio Emanuele Cinà, Marcello Pelillo
Collaborative Evolving Strategy for Automatic Data-Centric Development
Xu Yang, Haotian Chen, Wenjun Feng, Haoxue Wang, Zeqi Ye, Xinjie Shen, Xiao Yang, Shizhao Sun, Weiqing Liu, Jiang Bian
She Works, He Works: A Curious Exploration of Gender Bias in AI-Generated Imagery
Amalia Foka
Assessing AI Utility: The Random Guesser Test for Sequential Decision-Making Systems
Shun Ide, Allison Blunt, Djallel Bouneffouf
Exploring the Limitations of Kolmogorov-Arnold Networks in Classification: Insights to Software Training and Hardware Implementation
Van Duy Tran, Tran Xuan Hieu Le, Thi Diem Tran, Hoai Luan Pham, Vu Trung Duong Le, Tuan Hai Vu, Van Tinh Nguyen, Yasuhiko Nakashima
Why Machines Can't Be Moral: Turing's Halting Problem and the Moral Limits of Artificial Intelligence
Massimo Passamonti
Pensieve Discuss: Scalable Small-Group CS Tutoring System with AI
Yoonseok Yang, Jack Liu, J. D. Zamfirescu-Pereira, John DeNero
Generative artificial intelligence in dentistry: Current approaches and future challenges
Fabián Villena, Claudia Véliz, Rosario García-Huidobro, Sebastián Aguayo
Open Challenges on Fairness of Artificial Intelligence in Medical Imaging Applications
Enzo Ferrante, Rodrigo Echeveste