From shoes to clothes, from vinyl records to the latest smartphones, humans have a seemingly insatiable desire 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 pursue more rewards when we “get used to” a higher standard of living and are confronted with various standards.
Do you want more and more things even if they are making you miserable? Well, we can probably blame our brains for our relentless pursuit of material goods, according to a computer simulation study.
The new study was led by researchers from Princeton University’s Department of Psychology in New Jersey.
“From ancient religious texts to modern literature, human history abounds with tales describing the struggle to achieve eternal happiness,” they state in their article.
“Paradoxically, happiness is one of the most sought after human emotions, yet achieving it in the long term remains an elusive goal for many people.
“Our findings help explain why we are prone to being trapped in an endless cycle of desires and desires and may shed light on psychopathologies such as depression, materialism and over-consumption.”
According to experts, two psychological phenomena mean that our brains relentlessly pursue material goods.
First, human happiness is affected by a phenomenon called “relative comparisons”.
This means that we often worry about the difference between what we have and the desired level we wish to achieve.
Second, what it takes to be happy depends on our previous expectations, but these expectations can change over time.
For example, if we have had a particularly pleasant experience, such as being taken on a cruise, we will judge our happiness against the expectation of having a similar experience again.
Lead author of the Princeton study Rachit Dubey told MailOnline: “Our article was inspired by discoveries about human happiness (particularly our propensity 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 real human ‘brains’ and the way humans think, and taught them ‘reinforcement learning’.
Dubey said: ‘Reinforcement learning methods focus on training an agent (e.g. a robot) so that the agent learns how to map situations to actions (e.g. learning to play chess).
“The guiding principle of these methods is that they train agents using rewards: they provide positive rewards for desired behaviors and / or negative rewards for unwanted ones.”
Some brains were given a simple “reward”, while others were given an extra reward when they based their decisions on previous expectations and comparing their rewards with others.
The researchers found that the second group was less happy but learned faster than the first and passed them in all the tests they took.
While we may enjoy a newly purchased car, over time it brings fewer positive feelings and eventually we start dreaming of the next rewarding thing to pursue, researchers say (archive photo)
This suggests that we will be less happy the more rewarded we are when we are confronted with various standards.
Dubey told MailOnline: “Our computer-based simulations suggest it has advantages: if we’re never satisfied, we’re constantly pushed to find better results.
“However, this also has drawbacks: we constantly devalue what we already have, which in extreme cases can lead to depression and excessive consumption.”
Dubey also recognized the question of how reliably such computer methods can map human behavior.
“Care must be taken when generalizing our simulation-based results to real-world scenarios,” he told MailOnline.
The team’s article was published in the journal PLoS Computational Biology.
