​AI Personalization & Responsible AI

​This event explores three questions about large language models: how AI should adapt to different users and cultures, how we should think about the safety of increasingly capable AI systems, and how we can identify AI-generated text.

​The talks will explore three perspectives:

• ​🌍 Personalization & Cultural Competence: How LLMs can use information about users and their cultures to provide more useful responses, while avoiding stereotypes, echo chambers, and cultural bias.

• ​🛡️ AI Safety & Superintelligence: Whether more intelligent AI systems would also become more moral, and what this question means for the safety of future AI.

• ​🔍 Watermarking LLM Outputs: How hidden signals can be added to AI-generated text so that it can later be detected, and how well these methods work when the text is edited or rewritten.

​This session is for AI engineers, researchers, founders, product builders, data scientists, students, and anyone interested in current developments in AI.

​🗓️ Program

​5:30 PM – 5:50 PM 👋 Arrival & networking
Doors close at 5:45 PM
5:50 PM – 6:05 PM 🔍 Issam Laradji | Watermarking LLM Outputs
6:10 PM – 6:50 PM 🌍 Vered Shwartz | To Personalize or Not to Personalize? That Is the Question
6:50 PM – 7:00 PM ☕ Break
7:00 PM – 7:40 PM 🛡️ Sherif Salem | Should We Be AI Optimists? A Case for AI Safety
7:40 PM – 7:55 PM 🤝 Closing & networking
🍽️ After 7:55 PM (Optional) Head to Good Co. for food, drinks, and more networking 📍 965 Granville St, Vancouver, BC

​Timing is approximate.

​ℹ️ Disclaimers

​🍱 Feel free to bring your own food and water bottle.
💧 There is a water fountain at the venue.
🚗 Paid parking is available nearby, including EasyPark.
🐾 The venue is not pet-friendly (service animals welcome).
🚲 Bicycles are not permitted inside the building.
⏰ Doors close at 5:45 PM, so please arrive before then.
🏢 Before 5:45 PM, someone in the lobby can guide you to the event space on the 14th floor.

​🎤 Speaker 1: Vered Shwartz

​Assistant Professor, Computer Science, UBC | CIFAR AI Chair, Vector Institute

​Vered Shwartz is an Assistant Professor of Computer Science at the University of British Columbia and a CIFAR AI Chair at the Vector Institute. Her research focuses on understanding and improving large language models and vision-language models, developing AI that works well across different cultures, and building responsible NLP systems for sensitive areas such as law and medicine.

​Before joining UBC, she was a postdoctoral researcher at the Allen Institute for AI (AI2) and the Paul G. Allen School of Computer Science & Engineering at the University of Washington. She received her PhD in Computer Science from Bar-Ilan University in 2019.

​🌍 To Personalize or Not to Personalize? That Is the Question

​Millions of people use LLMs every day for advice, information, and assistance. AI systems can remember information about users and their preferences to provide more personalized responses. But personalization also comes with risks.

​Vered will explore these trade-offs through cultural competence, which means responding in ways that reflect appropriate cultural knowledge and norms. She will discuss how knowing a user's location can sometimes make an AI system more useful, but also how changing answers based on someone's location or cultural background can reinforce stereotypes or create echo chambers.

​At the same time, giving everyone the same answer is not necessarily the solution because today's models are heavily biased toward Western cultures. Vered will present recent work on building LLMs that can represent multiple cultural viewpoints.

​🎤 Speaker 2: Sherif Salem

​Researcher in Philosophy of Science & Technology | Background in Economics & Philosophy

​Sherif Salem has a background in economics and philosophy. His research interests include the philosophy of science and technology, how we understand knowledge, and the history of capitalism.

​🛡️ Should We Be AI Optimists? A Case for AI Safety

​Should we be optimistic about where AI development is heading?

​One argument for optimism is that a future superintelligent AI would also become more moral because intelligence and morality are somehow connected. If this were true, highly intelligent AI systems might naturally behave in ways that are good for humanity.

​Sherif will challenge this idea and present a philosophical argument for why becoming more intelligent does not necessarily mean becoming more moral. He will discuss what this means for how we think about the safety of future AI systems.

​🎙️ Opening: Issam Laradji

​Adjunct Professor, UBC

​🔍 Watermarking LLM Outputs

​As AI-generated text becomes more common, it is becoming harder to tell whether something was written by a person or generated by an AI system.

​Issam will introduce LLM watermarking, a set of methods for adding hidden signals to AI-generated text that can later be detected. He will explain how these watermarks work, how we can test whether a piece of text contains one, and what happens when someone edits or rewrites the text.

​The talk will also cover the trade-offs between making a watermark easy to detect, keeping it difficult to remove, and maintaining the quality of the generated text.

​🌲 About

​Vancouver AI Meetup (VAM!) is a community of researchers, engineers, founders, students, and AI practitioners who come together to learn, share ideas, and discuss the latest developments in artificial intelligence.

​Northeastern University was founded in 1898 and is a global research university and a leader in experiential learning. With campuses across the U.S., U.K., and Canada, its global network connects students, researchers, and industry partners around the world.

​Located in downtown Vancouver, the Vancouver campus offers master's-level technology programs, including pathways for students from non-STEM backgrounds to pursue graduate studies in technology.