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
Predicting the usability of mobile applications using AI tools: the rise of large user interface models, opportunities, and challenges
Abdallah Namoun, Ahmed Alrehaili, Zaib Un Nisa, Hani Almoamari, Ali Tufail
Responsible AI: Portraits with Intelligent Bibliometrics
Yi Zhang, Mengjia Wu, Guangquan Zhang, Jie Lu
Artificial intelligence for context-aware visual change detection in software test automation
Milad Moradi, Ke Yan, David Colwell, Rhona Asgari
Towards Green AI: Current status and future research
Christian Clemm, Lutz Stobbe, Kishan Wimalawarne, Jan Druschke
From Keyboard to Chatbot: An AI-powered Integration Platform with Large-Language Models for Teaching Computational Thinking for Young Children
Changjae Lee, Jinjun Xiong
Strategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer
Marc Schmitt
Automated Generation of High-Quality Medical Simulation Scenarios Through Integration of Semi-Structured Data and Large Language Models
Scott Sumpter
Artificial Intelligence in Bone Metastasis Analysis: Current Advancements, Opportunities and Challenges
Marwa Afnouch, Fares Bougourzi, Olfa Gaddour, Fadi Dornaika, Abdelmalik Taleb-Ahmed
Artificial intelligence and machine learning applications for cultured meat
Michael E. Todhunter, Sheikh Jubair, Ruchika Verma, Rikard Saqe, Kevin Shen, Breanna Duffy
Reimagining AI in Social Work: Practitioner Perspectives on Incorporating Technology in their Practice
Katie Wassal, Carolyn Ashurst, Jiri Hron, Miri Zilka
Data Set Terminology of Deep Learning in Medicine: A Historical Review and Recommendation
Shannon L. Walston, Hiroshi Seki, Hirotaka Takita, Yasuhito Mitsuyama, Shingo Sato, Akifumi Hagiwara, Rintaro Ito, Shouhei Hanaoka, Yukio Miki, Daiju Ueda
A University Framework for the Responsible use of Generative AI in Research
Shannon Smith, Melissa Tate, Keri Freeman, Anne Walsh, Brian Ballsun-Stanton, Mark Hooper, Murray Lane
Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP
Sanjana Gautam, Mukund Srinath
What is Reproducibility in Artificial Intelligence and Machine Learning Research?
Abhyuday Desai, Mohamed Abdelhamid, Nakul R. Padalkar
Strategic Behavior and AI Training Data
Christian Peukert, Florian Abeillon, Jérémie Haese, Franziska Kaiser, Alexander Staub