The TvL (Talent versus Luck) model is a simulation that studies the evolution of people's careers over time and how they are influenced by random events that can be either lucky or unlucky. The model is based on the idea that there are a certain number of individuals, each with their own level of talent (intelligence, skills, ability, etc.), who are placed in a virtual world with periodic boundary conditions (meaning it wraps around, like a torus). This virtual world also contains a number of "moving" events, some of which are lucky and some of which are unlucky.
These events move randomly around the world and can intersect with the position of an individual.If an event intersects with an individual, it can either have no effect, double the individual's success with a probability proportional to their talent if it's a lucky event, or halve their success if it's an unlucky event. The simulation runs for a period of 40 years, with each time step representing six months. The goal of the model is to understand how luck and talent interact to influence an individual's career success over time.
In this study, the TvL model was used to simulate the careers of 1000 individuals over a period of 40 years, with each time step representing six months. Each individual had a different level of talent, which was normally distributed with a mean of 0.6 and a standard deviation of 0.1. The simulation also included 500 "event points" that moved randomly around the virtual world, with 50% of them being lucky events and the other 50% being unlucky events. At the end of the simulation, it was found that the model produced an unequal distribution of career success, with a small number of very successful individuals and a large number of unsuccessful ones.
This distribution followed a Pareto-like power lawMany things in life have a disproportionate relationship between cause and effect.20% of the people own 80% of the land, Just 1.4 percent of tree species account for 50 percent of the trees in the Amazon, 77% of Wikipedia is written by 1% of its editors (vice), with the top 20% of individuals holding 44% of the total wealth. Interestingly, the most successful individuals were not the most talented ones, and vice versa.
In fact, the most successful individual had a talent level only slightly above the mean, while the most talented individual had a very low level of success. These results suggest that luck plays a significant role in determining an individual's career success, even when talent is taken into account. Additionally, the number of lucky and unlucky events experienced by each individual was found to be correlated with their final level of success, with the most successful individuals also being the luckiest ones.
When looking at the talent distribution of the most successful individuals, it was found that they were more likely to be moderately talented rather than very talented. In fact, the probability of finding a moderately talented individual at the top of success was found to be higher than that of finding a very talented individual there. This suggests that luck plays a significant role in determining an individual's career success, even when talent is taken into account. To further explore this idea, the authors conducted additional simulations in which they averaged the results over 100 runs.
They found that the distribution of talent among the most successful individuals was shifted to the right of the talent axis, meaning that individuals with medium to high talent levels were more likely to be the most successful than those with very high talent levels. The authors also found that the probability of finding a moderately talented individual at the top of success was higher than that of finding a very talented individual there. This indicates that luck matters more than talent in reaching very high levels of success.
These results were consistent even when the model was run 10,000 times, further supporting the idea that luck plays a major role in determining career success.To illustrate these concepts with an example, imagine that you are a research grant funding council with a fixed amount of money to distribute. Would you be more likely to achieve a higher average impact by giving large grants to a few apparently excellent researchers, or small grants to many more apparently ordinary researchers? According to the findings of this study, it might be more effective to give small grants to a larger number of researchers, as impact is only weakly related to funding and the concentration of research funding can produce diminishing marginal returns.
Additionally, the most funded researchers do not necessarily stand out in terms of output and scientific impact. In this case, a meritocratic strategy of giving the largest grants to the most excellent researchers may not be as effective as a strategy that focuses on diversifying ideas through smaller grants to a larger number of researchers. This is because luck plays a significant role in determining success, and a more diverse group of researchers may be more likely to benefit from random events that lead to important discoveries.
This section discusses the concept of serendipity, which refers to unexpected and beneficial discoveries made by chance, and its role in scientific research. They propose using the TvL model, which incorporates luck as a factor, to explore the effectiveness of different funding strategies in preserving a minimum level of success for the most talented individuals while also promoting serendipity and diversity. The authors consider four different funding criteria: distributing funds equally to all individuals, only to the most successful individuals, distributing a premium to the most successful individuals and the rest in equal parts to all others, or randomly selecting a percentage of individuals to receive funding.
The authors find that the selective random criterion is the most effective in preserving a minimum level of success for the most talented individuals while also promoting serendipity and diversity. The TvL model takes into account the role of luck, or serendipity, in determining success and allows for the exploration of different funding scenarios. The model is used to investigate the effectiveness of policies targeted at increasing the average level of education or at reinforcing the training of the most gifted people.
The results show that such policies can have beneficial effects on the social system, but the enhancement in the average percentage of highly talented people who are able to reach a good level of success is not particularly remarkable. The importance of the abundance of opportunities offered by the social environment plays an important role in determining success, and the potential for policies targeting the distribution of wealth to increase the overall level of success in the system.Overall, the results suggest that policies aimed at strengthening the training of the most gifted people or increasing the average level of education can have beneficial effects on the social system, as they increase the chances for talented individuals to take advantage of opportunities presented to them.
However, the enhancement in the average percentage of highly talented people who achieve a good level of success is not particularly significant in either scenario. The results also suggest that the abundance of opportunities in the social environment is another important factor in determining success. This paper presents an agent-based model to understand how talent and luck contribute to an individual's success. The model shows that the most successful people are often not the most talented, but rather those who are around the average of the talent distribution.
It also demonstrates the significant impact of lucky events on an individual's level of success and how a "naive meritocracy" can fail to recognize and reward true competence, leading to a lack of opportunities for the most talented individuals. The authors propose strategies to counterbalance luck and give more opportunities to the most talented individuals, which they argue would be beneficial for society as a whole by increasing diversity and fostering innovation.