From shoes to clothing, from vinyl records to the latest smartphone, people have an insatiable need for the latest products.
Now researchers have used computer models to try to explain why we constantly crave more and more material things, even when they make us feel miserable.
According to the results, we seek greater rewards when we “get used to” a higher standard of living and compare ourselves to different standards.
Do you crave more and more things, even if it makes you unhappy? Well, we can probably blame our brains for our relentless pursuit of material goods, according to a computer simulation study.
The new study was conducted by researchers in the Department of Psychology at Princeton University in New Jersey.
“From ancient religious texts to modern literature, human history is replete with stories describing the struggle to achieve eternal happiness,” they write in their article.
“Ironically, happiness is one of the most sought-after human emotions, but achieving it in the long run remains a elusive goal for many people.
“Our results help explain why we tend to get trapped in an endless cycle of wants and desires and may shed light on psychopathologies such as depression, materialism and overconsumption.”
According to experts, two psychological phenomena mean that our brains relentlessly pursue material possessions.
First, human happiness is affected by a phenomenon called “relative comparisons.”
This means that we are often worried about the difference between what we have and the desired level that we want to achieve.
Second, what it takes to be happy depends on our previous expectations, but those expectations can change over time.
For example, if we had a particularly pleasant experience, such as going on a cruise, then we would rate our happiness against our expectation of repeating the same experience.
Lead study author Rahit Dubey of Princeton told MailOnline: “Our paper was inspired by discoveries about human happiness (in particular our tendency to keep wanting more) and we wanted to provide an explanation for this behavior.”
In their experiments, the team created computer-simulated agents to represent the real human “brain” and how people think, and taught them “reinforcement learning.”
Dubey said: “Reinforcement learning methods focus on training an agent (like a robot) so that the agent learns to match situations with actions (like learning to play chess).
“The guiding principle of these methods is that they train agents with rewards—they provide a positive reward for desirable behavior and/or a negative reward for undesirable behavior.”
Some brains were given a simple “reward” while others were given an extra reward when they based decisions on prior expectations and comparing their rewards to others.
The researchers found that the latter group were less happy but learned faster than the former and outperformed them on every test they took.
While we may enjoy a newly bought car, it becomes less positive over time, and we end up daydreaming about the next useful thing to do, researchers say (file photo)
This suggests that we will be less happy the more we are rewarded by comparing ourselves to different standards.
Dubey told MailOnline: “Our computer simulations show that it has advantages – if we are never satisfied, we are constantly striving to find better results.
“However, it also has its drawbacks – we constantly devalue what we already have, which in extreme cases can lead to depression and overconsumption.”
Dubey also acknowledged the question of how reliably such computer methods can map human behavior.
“Caution needs to be exercised when generalizing our simulation results to real scenarios,” he told MailOnline.
Team article published in the journal PLoS Computational Biology.
