Future Implication
Research on the implications of future AI technologies focuses on understanding and mitigating the risks and biases inherent in increasingly powerful models, while also exploring their potential benefits across diverse fields. Current work examines the impact of large language models (LLMs) on various tasks, including translation, sentiment analysis, and human activity recognition, investigating issues like memorization, bias propagation, and the effectiveness of different model architectures (e.g., transformer-based models, diffusion models). This research is crucial for ensuring responsible AI development and deployment, informing ethical guidelines, and improving the reliability and fairness of AI systems in both academic and practical applications.
Papers
Generative AI: Implications and Applications for Education
Anastasia Olga, Tzirides, Akash Saini, Gabriela Zapata, Duane Searsmith, Bill Cope, Mary Kalantzis, Vania Castro, Theodora Kourkoulou, John Jones, Rodrigo Abrantes da Silva, Jen Whiting, Nikoleta Polyxeni Kastania
Implications of Deep Circuits in Improving Quality of Quantum Question Answering
Pragya Katyayan, Nisheeth Joshi