Characterizing people using Game Theory
Resource: https://www.sciencedaily.com/releases/2016/09/160915085719.htm
This was a social experiment which characterized people 90% of it is participants into four personality types: optimistic, pessimistic, trusting and envious. The experiment was conducted using game theory in Universidad Carlos III de Madrid, and the findings were used to construct a computer algorithm to classify people on their behavior. The algorithm classified the most popular group of 541 participants as envious (30%) while rest of the groups were at 20%. The only problem the algorithm had was clearly identifying 10% of the population. But with this advent, it shows that there may be many more subgroups that can be identified with further studies. The study itself, showed that people go against the theory of being purely rational all of the time and hence that should be taken into account when making economic policies.
The experiment had people in groups and given tasks to perform that had different implications given on what other groups decided to do. The groups were altered and changed within each game and every game change. The results were recorded as people chose to either help or go against their partners. From the reading, there may have been some influence of networks in the experiment as it was all done in a single city with citizens as participants and set up by the council as a community event.
The experiment itself was important because of its large scale, the researchers stated that before this there were only low level (12 people) experiments done, and now with the computer algorithm it may be possible to take it to a larger scale. The results of the experiment go further than just categorize people into groups though, it may explain what moves the common or personal good and interests in negotiation. They hope to use this algorithm to develop a smarter AI, which can make “robots more humanized” going further into the study field of artificial development rather than just sociology.