Learning from outcomes shapes reliance on moral rules versus cost-benefit reasoning

Area of Science:

• Cognitive Science
• Moral Psychology
• Neuroscience

Background:

• Moral decision-making often involves conflict between deontological rules and utilitarian cost-benefit reasoning (CBR).
• Individual differences in reliance on rules versus CBR are not fully understood.
• Understanding the mechanisms of moral learning is crucial for explaining these differences.

Purpose of the Study:

• To investigate how moral learning from consequences shapes individual differences in rule-based versus CBR decision-making.
• To explore the role of metacognitive learning in moral judgments.
• To examine the transferability of learned moral strategies.

Main Methods:

• A novel experimental paradigm with 2,328 participants facing moral dilemmas.
• Sequential decision-making with feedback on consequences after each choice.
• Computational modeling to analyze decision strategies and learning processes.

Main Results:

• Participants adaptively adjusted their decisions based on the experienced consequences of rule-based versus CBR strategies.
• Computational modeling revealed that participants engaged in metacognitive learning about strategies, not just specific actions.
• Learned moral decision-making transferred to new contexts, including donation choices and expressed moral convictions.

Conclusions:

• Metacognitive learning from experienced consequences is a key mechanism shaping moral decision-making.
• Individual differences in morality are malleable and can be influenced by learning from experience.
• Moral learning can generalize beyond the specific context of the learning experience.