Breakout Session 1

Discover how Retrieval Augmented Generation (RAG), a technique that combines AI's generative capabilities with targeted information retrieval, is influencing the landscape of information management and library science. We will explore how libraries are applying their unique "librarian's perspective" to document organization, while highlighting powerful tools like NotebookLM. You'll gain skills in crafting targeted prompts to uncover relevant information and explore new connections. We will also discuss best practices for ethical AI use in academic settings and explore how these tools and techniques can directly support students in their research and learning.

About Benjamin Ehlers:

Ben Ehlers is a Digital Literacy Librarian at Edmonton Public Library, where he focuses on empowering staff with the skills to effectively use AI in their work supporting library patrons. With a background in library and information studies, Ben is passionate about bridging the gap between emerging technologies and information access. He is currently exploring practical applications of AI within library services and is keen to share his insights on how to ethically and effectively navigate the evolving landscape of artificial intelligence in information management.

Artificial Intelligence is only as good as the information it has when the user engages with it. This means the majority of the systems being built today are utilizing AI that favours the perspective of the cis, able-bodied Eurocentric male. As many Canadians are learning now, the true history between Indigenous Peoples and Canadian systems is vastly different from what was taught in school. The information currently online about Indigenous Peoples is largely inaccurate, biased and dehumanizing - this is the information AI is collecting about Indigenous communities. How do we work together to create a more holistic approach to building AI, a critical piece of infrastructure that experts predict will touch all aspects of our daily lives? 

In this session we will talk about what kinds of information is used to create AI, who the information is about, and where AI is found in our day-to-day lives. We will consider what happens when AI works well, how it can help, and what happens when it doesn't go well and just reenforces biases.  

About Dr. Bailey Kacsmar:

Dr. Bailey Kacsmar is an Assistant Professor at the University of Alberta where she leads the Practical Usable Security and Privacy (PUPS) research lab. She is also a fellow at Amii (the Alberta machine intelligence institute). Dr. Bailey’s research centers on the privacy implications and potential of machine learning and artificial intelligence. She develops human-centred privacy technology through the parallel study of technical solutions for private data analysis alongside the corresponding user perceptions, concerns, and comprehension of these developments. Prior to joining the University of Alberta, she received her PhD in Computer Science and her Masters of Mathematics, both from the University of Waterloo.

The scope and speed of change that is coming with the emergence of Artificial intelligence (A.I.) will be profound. It is expected that A.I. may reach human levels by around 2029, and that by 2045 we will have multiplied our human biological intelligence a billion-fold. This session is intended to share a discussion about the impact of artificial intelligence (AI) on the future of everything, most especially learning in the future and how it will impact the lives of high-school students about to enter the world or work or post-secondary studies. Dr. McRae will share key findings from his research and work internationally as the special advisor on Artificial Intelligence to the Secretary-General of Education International (EI), which represents 33 million teachers around the world. 

About Dr. Phil McRae:

Dr. Phil McRae is an internationally recognized thought leader and highly sought-after speaker known for his dynamic keynote addresses and insightful perspectives on education, school improvement, technology, and change. You can find his research, publications and presentations at www.philmcrae.com 

In this talk, we overview the history of Artificial Intelligence (AI) research from the dawn of expert systems, the growth of connectionism to recent developments in Generative AI and Large-language models. We will discuss AI research at the University of Alberta, highlighting recent breakthroughs and real-world applications including adaptive prosthetics and water treatment. We will wrap up speculating about the future of AI: developing systems with goals and purposes.

About Adam White:

Adam White is an Assistant Professor at the University of Alberta, where he co-leads the Reinforcement Learning and Artificial Intelligence research (RLAI) group and serves as Scientific Director of the Alberta Machine Intelligence Institute (Amii). He also holds a prestigious Canada CIFAR Chair in Artificial Intelligence. Previously, Adam was a Staff Research Scientist at Google Deepmind. Adam co-created the Reinforcement Learning Specialization, taken by over 90,000 students on Coursera. 

Adam's research is focused on understanding the fundamental principles of learning in both simulated worlds and industrial control applications. His research program explores how the problem of intelligence can be modeled as a reinforcement learning agent interacting with some unknown environment, learning from a scalar reward signal rather than explicit feedback. Adam's group is deeply passionate about good empirical practices and new methodologies to help determine if our algorithms are ready for deployment in the real world. Adam has pioneered applications of reinforcement learning to real drinking and wastewater treatment plants and is the co-founder of RL Core Technologies, a startup applied AI and machine learning across industrial control.