How do we make decisions when we are uncertain? In more real-world settings there is often a vast array of information available to guide the decision, from an understanding of the social situation, to prior beliefs and experience, to information available in the current environment. Yet much of the research into uncertain decision-making has typically studied the process by isolating it from this rich source of information that decision-makers usually have available to them. This thesis takes a different approach. To explore how decisions are made under uncertainty in more real-world settings, this thesis considers how raters decide if someone is lying or telling the truth. Because people are skilled liars, there is little information available to make a definitive decision. How do raters negotiate the ambiguous environment to reach a decision? Raters show a truth bias, which is to say they judge statements as truthful more often than they are so. Recent research has begun to consider dual process theories, suggesting there are two routes for processing information. They claim the truth bias results from an error-prone processing route, but that a more effortful and analytical processing route may overcome it. I will generate a set of testable hypotheses that arise from the dual process position and show that the theory does not stand up to the test. The truth bias can be better explained as resulting from a single process that attempts to make the most 3 informed guess despite being uncertain. To make the informed guess, raters come to rely on context-relevant information when the behaviour of the speaker is not sufficiently diagnostic. An adaptive decision maker position is advocated. I propose the truth bias is an emergent property of making the best guess. That is, in a different context where speakers may be expected to lie, a bias towards disbelieving should be seen. I argue context-dependency is key to understanding decision-making under uncertainty.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:602848 |
| Date | January 2013 |
| Creators | Street, C. N. H. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1414942/ |
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