Telfer Research Seminar Series - Piers Steel
The Inference Engine: AI’s Imminent Leap Forward
***M.Sc. Students, these seminars can count towards the six mandatory Research Seminars Series required for your program (MGT 6191/ MGT 6991 / MHS 6991) (4 seminars for MSc Project-based students).***
The Inference Engine: AI’s Imminent Leap Forward
Piers Steel, PhD
The development of inference engines represents a critical leap in AI, allowing systems to make sophisticated, data-driven decisions. This talk explores how meta-analysis can serve as a foundational tool for building robust inference engines by aggregating and synthesizing vast datasets to extract meaningful patterns. By leveraging meta-analytic techniques, AI systems can achieve higher levels of predictive accuracy and generalizability across contexts. This convergence of meta-analysis and AI will democratize algorithmic decision-making, making advanced insights accessible to individuals and organizations alike. Ultimately, the talk will propose that this evolution could lead to the creation of an exocortex—a cognitive extension that enhances human capabilities by integrating AI-powered decision support into daily life, revolutionizing the way we think, work, and innovate.
About the Speaker
Piers Steel is a professor in the Organizational Behaviour and Human Resources area and is the Brookfield Research Chair at the Haskayne School of Business. He is a recognized authority on the science of motivation and is known internationally for his productivity research, receiving widespread media coverage.
Prof. Steel’s particular areas of research interest include culture, motivation and decision-making. He is also currently driving a systematic review of ethical research with the goal of identifying what is known and where knowledge gaps lie and sharing the knowledge in a practical and accessible format. He has expertise in systematic review and meta-analysis, having published over 25 scholarly articles on the topic, and is a member of the Society of Research Synthesis and Methodology. He has published several methodology papers on how to improve meta-analysis.