My research, supervised by Prof. David Lagnado, focuses mainly on how people mentally represent their causal models and reason through them in the context of different types of real-world scenarios. People use narratives and causal models to understand the world, yet these models are swayed by cognitive biases. What causes are weighted the most highly? Which are left out altogether? What happens with more complex causal structures?
Present methodologies seldom allow participants to map their own models; the questions being asked do the framing for them. One way to address this problem is to let people construct their own causal models from data, text and evidence. By using an interactive model-building interface, I aim to explore the relation between causal models and judgments.
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