A new perspective on human judgement and decision making as optimal: A framework for behaviour change

点击翻译按钮获取中文摘要

Psychology and Economics typically characterise human judgement & decision-making (JDM) as flawed. JDM is commonly described as irrational, biased or sub-optimal and there are many observations that appear to support this viewpoint. For example, when asked to make a judgment about the likely outcome of a coin toss after a long sequence of previous tosses coming up heads, many people expect a tail on the next toss, when in reality previous tosses do not change the 50:50 head:tail chance. This misperception is known as the Gamblers Fallacy (GF). If, however, we accept that humans have a narrow focus of attention and a limited memory capacity for say, only the last 5 tosses, this will limit what can be learnt from the long sequence. This limited experiential window means that, mathematically, not all sequences of a given length have the same chance of occurring in a longer (but finite) sequence and as a result the gamblers' expectation of a tail after a run of heads can be shown to be entirely reasonable.In this project we aim to show that if we take into account the limits on human cognitive capacity or the limits imposed by the environment, human JDM is not flawed and is in fact optimal given those constraints. We will demonstrate this for two examples, the GF above and 'Preference Reversals' (PR) another class of phenomena in which JDM is commonly described as biased. Further, we will show that if we change cognitive or environmental constraints, humans will adapt and remain optimal given the new constraints. This will allow us to test the consequences of manipulating the causal determinants of human JDM performance and therefore will allow for better policy development. To do so we will conduct behavioural experiments as well as formulate and evaluate computational models of our experimental tasks.The project comprises two themes running mostly in parallel over the 18 months project. Theme 1 will investigate human Perception of Randomness and the associated GF phenomenon. The ability of humans to perceive structure in the environment and differentiate it from its counterpart, randomness, is at the heart of our ability to make causal links between events. For this reason, studying perception of randomness is vital for our understanding of how humans understand the world. Using the GF and our theoretical analysis, we will run a series of behavioural experiments to explain GF as optimal under constraints - namely the short-term memory limitation as a proxy for an individual's window of experience. We will use computational models to test if the observed behaviour is optimal under such constraints. Further experiments will simulate interventions that modify the key constraints, for instance, temporarily reducing the size of the window of experience by varying cognitive load. We hypothesise that behaviour will change in line with model predictions, and remain optimal. This would be a significant finding and a strong test of the proposed framework. Theme 2 will investigate context effects and Preference Reversal (PR). PR occurs when the addition of further choices changes a person's preference, even when the new choices are worse. Although PR is used as evidence of human irrationality, our pilot work shows that introducing new choices provides additional information about priors, such that PR becomes an optimal behaviour. We will manipulate the distribution of choice problems and measure adaptation to the different task distributions by measuring changes in the reliance on context.