Biography
Charles is broadly interested in how humans make decisions against a certain causal structure or representation of the world. Recently, the adoption of statistical learning algorithms has introduced a novel causal context for studying the human learning-cum-decision-making process. Charles' research explores how statistical learning algorithms interact with human agency, human causal reasoning, organizational information-processing, and organizational decision-making.
Previously Charles worked as a commodities trader in Europe, the US, and Asia.
For more information please visit https://wan-charles.github.io/.
Rotterdam School of Management, Erasmus University
PhD candidate | Rotterdam School of Management
- wan@rsm.nl
More information
Work
- Charles Wan, Rodrigo Belo, Leid Zejnilović & Susana Lavado (2023) - The Duet of Representations and How Explanations Exacerbate It - doi: 10.1007/978-3-031-44067-0_10 - [link]
- Charles Wan (2023) - Timescales, Levels of Organization, and Multi-objective Agents - doi: 10.1162/isal_a_00562 - [link]
- Charles Wan, Leid Zejnilović & Susana Lavado (2023) - How Differential Robustness Creates Disparate Impact: A European Case Study - [link]
- Charles Wan, Rodrigo Crisostomo Pereira Belo & Leid Zejnilović (2022) - Explainability's Gain is Optimality's Loss? — How Explanations Bias Decision-making - doi: 10.1145/3514094.3534156 - [link]
