[MUSIC] Now, let us look at the following three figures, each visualizing the probability of norm abandonment when a specific proportion of people is deviating from an established norm. These figures exemplify how the independent factors of risk sensitivity, risk perception and norm sensitivity, jointly predict how likely one is to switch from an established norm to a new behavior. In the first figure, nobody has yet switched to the new behavior. Even extremely norm insensitive individuals will factor into their decision making, how many of their peers have abandoned the norm, and the risk of doing so themselves. What differentiates the first movers in this figure from other norm insensitive individuals is their risk sensitivity and situation specific perception of risk. Remember, it's the alpha that combines the two in the left most distribution. Different sectors with very low norm sensitivity and equally low risk perception and risk sensitivity fall at the very extreme ends of both distributions of k's and alpha's, which means that only a very small segment of the population is willing to be the first to deviate from the established norm. Note that the changing colors in these figures from deep red to light yellow, represent the probability of abandonment. As you can see, the probability, the red colored area, is extremely low. You can also see that as alpha and k increase, the colors gradually become lighter, representing a decrease in the likelihood of abandonment. Also please note that they use the variable alpha to represent a person combination of risk sensitivity and risk perception. If nobody has yet changed behavior, the alpha distribution is skewed to the right, towards the value of one since the objective risk is very high, and risk perception usually hovers around it. Now look at the second figure. Here 30% of the population has already abandoned the norm, and we see that moderately norm sensitive individuals who were completely unwilling to abandon the norm when 0% of the population had abandoned it, are beginning to consider abandonment as a viable option. Note that the distribution of alpha has significantly changed from the original distribution in the previous figure. Because a larger proportion of the population has abandoned the norm, the perceived risk of deviating are likely diminished. Recall that alpha again is a combination of the stable trait of risk sensitivity and the more variable perception of risk. Also note that the distribution of norm sensitivity i.e., the distribution of the case has remained the same. However, the probability of norm abandonment has significantly increased as is shown by the darker colors in the distribution of kn. This is true for every value of k in this new distribution. Here we see that more moderate individuals and not just trendsetters are abandoning the norm. Finally, the third figure depicts a situation in which 55% of the population has abandoned the norm. There is now a light majority of deviators and it appears that a tipping point has been reached. Notice that the distribution of alpha has again changed and is skewed toward lower values. These represent a further shift in people perception of risk. Since a majority has abandoned the norm, the risks of deviating are considerably smaller than what they were initially. Similarly, the distribution of k's remain the same, but the probability of abandonment for each value of k has substantially increased as the darker colors show. When identifying potential trendsetters in a population, it is important to accurately measure their predictive traits, that is, risk sensitivity and risk perception and norm sensitivity. Risk sensitivity is usually measured experimentally by looking at the range of individual decisions. Specific risk perception can be measured through questionnaires and [INAUDIBLE] where individuals are asked about what is likely to happen if a non-deviation occurs, varying the number of deviators. Norm sensitivity can be measured by presenting individuals with hypothetical scenarios in which we systematically induce different empirical and normative expectation and assess whether their behavior would change. The less it would change, the more sensitive one is to the particular norm. Once perspective trendsetters have been identified, intervention should target them first because they have the highest likelihood of actually changing their behavior when no-one else is willing. Beware that what I'm showing here is a simplified explanation of the dynamics of trendsetters and conformists. It is important to remember that we may face more extreme situations in which the distribution of norm sensitivity with respect to particular norm is not normal. For example, well entrenched norms maybe cherished by the population and therefore, the distribution of the case will be skewed to the right. This means that the average norm sensitivity will be quite high. In such a case, the likelihood of encountering a substantial number of trendsetters is low and norm change will be unlikely to occur. In summary, people will have different thresholds for action based not only on their personal sensitivity to a norm, their k, but also the risk sensitivity and their particular risk perception in that situation. A person's choice to abandon a norm will thus depend on her sensitivity to it, on her risk sensitivity, and risk perception, and of course, on how many others are following the norm. As we've seen, a person with low norm sensitivity but high risk perception will probably have a high threshold. So the proportion of transgressors will have to be quite high to induce her to change behavior.