This piece, by Onno Berkan, was published on 11/12/24. The original text, by Jie Hu, was published by Nature Computational Science on 09/12/24.
Scientists have long been fascinated by why people help others, especially when there's no direct benefit to themselves. While previous research tried to explain altruistic behavior using just one or two reasons, a new study from East China Normal University suggests that human kindness is actually much more complex.
The researchers conducted experiments with over 1,400 people, showing them more than 100 different scenarios in which they could either help victims or punish wrongdoers. What they found was fascinating—people don't make these decisions based on just one factor but instead consider what they call a "motive cocktail."
This motive cocktail includes several key ingredients that influence our decision to help others:
How uncomfortable do we feel about inequality
Whether our actions will maximize overall benefits for everyone
How much it will cost us personally
Whether our actions might completely reverse the situation between the wrongdoer and the victim
Interestingly, the study found that people generally prefer to help victims rather than punish wrongdoers, which goes against some earlier theories about human behavior. The researchers also identified different types of helpers in the population:
"Justice warriors" who strongly want to fix any inequality they see
"Pragmatic helpers" who carefully consider the impact of their help
"Rational moralists" who try to do the right thing while minimizing their personal costs
This research has important implications for artificial intelligence and technology. By better understanding how humans make moral decisions, we can develop AI systems that make more human-like choices and better align with our values. The results also have implications for other fields, such as game theory and economic models.
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