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
Generative AI in Education: A Study of Educators' Awareness, Sentiments, and Influencing Factors
Aashish Ghimire, James Prather, John Edwards
A Technological Perspective on Misuse of Available AI
Lukas Pöhler, Valentin Schrader, Alexander Ladwein, Florian von Keller
(Un)making AI Magic: a Design Taxonomy
Maria Luce Lupetti, Dave Murray-Rust
The Ethics of AI in Education
Kaska Porayska-Pomsta, Wayne Holmes, Selena Nemorin
End-to-End Mineral Exploration with Artificial Intelligence and Ambient Noise Tomography
Jack Muir, Gerrit Olivier, Anthony Reid
Particip-AI: A Democratic Surveying Framework for Anticipating Future AI Use Cases, Harms and Benefits
Jimin Mun, Liwei Jiang, Jenny Liang, Inyoung Cheong, Nicole DeCario, Yejin Choi, Tadayoshi Kohno, Maarten Sap
Envisioning the Next-Generation AI Coding Assistants: Insights & Proposals
Khanh Nghiem, Anh Minh Nguyen, Nghi D. Q. Bui
Dynamic Explanation Emphasis in Human-XAI Interaction with Communication Robot
Yosuke Fukuchi, Seiji Yamada
From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Fora
Virginia Morini, Valentina Pansanella, Katherine Abramski, Erica Cau, Andrea Failla, Salvatore Citraro, Giulio Rossetti
Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
Dimitrios P. Panagoulias, Evridiki Tsoureli-Nikita, Maria Virvou, George A. Tsihrintzis
AI and Memory Wall
Amir Gholami, Zhewei Yao, Sehoon Kim, Coleman Hooper, Michael W. Mahoney, Kurt Keutzer
Navigating Fairness: Practitioners' Understanding, Challenges, and Strategies in AI/ML Development
Aastha Pant, Rashina Hoda, Chakkrit Tantithamthavorn, Burak Turhan
The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency, and Usability in Artificial Intelligence
Matt White, Ibrahim Haddad, Cailean Osborne, Xiao-Yang Liu Yanglet, Ahmed Abdelmonsef, Sachin Varghese
Analysing and Organising Human Communications for AI Fairness-Related Decisions: Use Cases from the Public Sector
Mirthe Dankloff, Vanja Skoric, Giovanni Sileno, Sennay Ghebreab, Jacco Van Ossenbruggen, Emma Beauxis-Aussalet
AI for bureaucratic productivity: Measuring the potential of AI to help automate 143 million UK government transactions
Vincent J. Straub, Youmna Hashem, Jonathan Bright, Satyam Bhagwanani, Deborah Morgan, John Francis, Saba Esnaashari, Helen Margetts
GPT-4 as Evaluator: Evaluating Large Language Models on Pest Management in Agriculture
Shanglong Yang, Zhipeng Yuan, Shunbao Li, Ruoling Peng, Kang Liu, Po Yang
Embracing the Generative AI Revolution: Advancing Tertiary Education in Cybersecurity with GPT
Raza Nowrozy, David Jam
Automated data processing and feature engineering for deep learning and big data applications: a survey
Alhassan Mumuni, Fuseini Mumuni