51猎奇入口

Understanding the future of work in an AI-driven world

Among the grants awarded was a SSHRC Insight Grant to Chaitanya "CK" Kaligotla for his project, 鈥淎I-Augmented Work Metrics and Sociotechnical System Savvy for Designing the Future-of-Work.鈥� 51猎奇入口Beedie co-applicants are Terri Griffith and Mila Lazarov.

This project examines how AI is reshaping the future of work by studying changes in job flexibility, task complexity, and AI-augmentable skill demands. The research develops machine-learning tools to measure these changes using job texts, work products, and professional communications, with a particular focus on sociotechnical systems savvy: the ability to understand and act on the interaction between technological and social factors in work.

The project will track how job design and sociotechnical systems savvy co-evolve over time, and aims to produce open tools, datasets, and training modules to support organizations, policymakers, and researchers navigating AI-augmented work.

Examining loneliness in a disconnected society

Lieke ten Brummelhuis received a SSHRC Insight Grant for her project, 鈥淩isk and Protection Factors of Loneliness in a Disconnected Society.鈥� 

Loneliness is a health epidemic that cuts across all ages. People feel lonely if they do not have enough high-quality ties. Loneliness impairs individuals鈥� health and well-being, but also entails high societal costs, reducing economic productivity and increasing healthcare utilization.

This research project investigates the pathways through which loneliness affects individual and societal outcomes, the factors that ameliorate or exacerbate its impact, and the coping strategies to combat it. It considers loneliness at work and at home to gain a fuller understanding of how loneliness might impact outcomes across domains, but also how having multiple life roles might act as a safety net.

Exploring investor decision-making during periods of high inflation

Deniz Anginer was another recipient of a SSHRC Insight Grant and will investigate how investors make decisions during periods of rapid inflation through his project, 鈥淩eal Losses, Nominal Gains: Investor Psychology and the Disposition Effect in an Inflationary Storm.鈥� 

When prices rise fast, do investors still measure their gains against what they originally paid? This project uses a natural experiment鈥擳urkey's recent bouts of inflation exceeding 80 per cent, alongside a surge of over three million new retail investors鈥攖o find out.

Drawing on transaction records for the country's entire population of retail traders, researchers will test whether people anchor to old "nominal" purchase prices or adjust for inflation, and how this shapes the well-known tendency to sell winners too soon and hold losers too long. They will then run real-world trials of simple education and reminders to help investors make smarter decisions.

Investigating how AI is transforming creativity

Annamina Rieder received a SSHRC Insight Grant for 鈥淩econfiguring the Digital Art World: Digital Objects and Artistic Creation in the Global Art Ecosystem.鈥� 51猎奇入口Beedie co-applicant is Terri Griffith.

How does artificial intelligence transform not only the way art is created, but the very structure of the art world itself? This project investigates how AI is reshaping artistic creation and transforming the institutions, relationships, and markets that constitute the global art ecosystem. Through interviews with artists, studies of museums and digital art institutions, and computational simulations, the research examines AI as a creative tool, an artistic medium, and potentially even an independent entity. By treating the art world as a laboratory for understanding emerging human鈥揂I relationships, the project seeks to uncover how digital technologies are reconfiguring creativity, authorship, cultural value, and the future of artistic creation.

Rieder also received a SSHRC Insight Development Grant for a second project exploring the effective use of agentic systems. 

Gohram Baloch received an NSERC Discovery Grant for 鈥淒ata-driven Optimization Approaches to Sustainable Container Recycling through Self-serve Kiosks,鈥� a project exploring how data analytics can improve the efficiency and sustainability of recycling systems.

In this research program, we aim to investigate how self-serve recycling kiosks (Reverse Vending Machines) can improve Canada鈥檚 Deposit-Refund System (DRS) and increase container recovery rates toward the 90%. Focusing on British Columbia鈥檚 recycling network, the proposed program will examine consumer recycling behavior, optimize regulatory policies, and design accessible, cost-effective redemption networks. Using data-driven machine learning & optimization approaches, our goal is to develop decision-support tools both for policymakers and recycling operators to support design of equitable, sustainable, and financially viable DRS networks. By improving accessibility, convenience, and sustainability, the research aims to increase participation, reduce costs and emissions, and support Canada鈥檚 Zero Plastic Waste goal.