A moral trade-off system produces intuitive judgments that are rational and coherent and strike a balance between conflicting moral values

妥协 困境 社会心理学 心理学 社会困境 激励 价值(数学) 认识论 经济 计算机科学 微观经济学 哲学 政治学 法学 机器学习
作者
Ricardo Andrés Guzmán,María Teresa Barbato,Daniel Sznycer,Leda Cosmides
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:119 (42) 被引量:17
标识
DOI:10.1073/pnas.2214005119
摘要

How does the mind make moral judgments when the only way to satisfy one moral value is to neglect another? Moral dilemmas posed a recurrent adaptive problem for ancestral hominins, whose cooperative social life created multiple responsibilities to others. For many dilemmas, striking a balance between two conflicting values (a compromise judgment) would have promoted fitness better than neglecting one value to fully satisfy the other (an extreme judgment). We propose that natural selection favored the evolution of a cognitive system designed for making trade-offs between conflicting moral values. Its nonconscious computations respond to dilemmas by constructing “rightness functions”: temporary representations specific to the situation at hand. A rightness function represents, in compact form, an ordering of all the solutions that the mind can conceive of (whether feasible or not) in terms of moral rightness. An optimizing algorithm selects, among the feasible solutions, one with the highest level of rightness. The moral trade-off system hypothesis makes various novel predictions: People make compromise judgments, judgments respond to incentives, judgments respect the axioms of rational choice, and judgments respond coherently to morally relevant variables (such as willingness, fairness, and reciprocity). We successfully tested these predictions using a new trolley-like dilemma. This dilemma has two original features: It admits both extreme and compromise judgments, and it allows incentives—in this case, the human cost of saving lives—to be varied systematically. No other existing model predicts the experimental results, which contradict an influential dual-process model.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
斯文败类应助沉静的梦秋采纳,获得10
刚刚
刀枪鸣完成签到,获得积分10
刚刚
windbroken发布了新的文献求助10
刚刚
烟花应助寻悦采纳,获得10
刚刚
自由琳发布了新的文献求助10
1秒前
CodeCraft应助柯达鸭采纳,获得10
1秒前
1秒前
1秒前
yfq1018完成签到,获得积分20
2秒前
虫子完成签到,获得积分10
2秒前
贪玩的秋柔应助xcy采纳,获得10
2秒前
李倇仪完成签到,获得积分10
3秒前
风中星月发布了新的文献求助10
3秒前
3秒前
whhh发布了新的文献求助10
3秒前
hh完成签到,获得积分20
4秒前
NANI发布了新的文献求助10
4秒前
4秒前
华仔应助刀枪鸣采纳,获得10
4秒前
5秒前
WLL完成签到,获得积分10
5秒前
FashionBoy应助勤恳寒凡采纳,获得10
6秒前
彩可心发布了新的文献求助10
6秒前
故槿完成签到 ,获得积分10
6秒前
7秒前
7秒前
我是老大应助雨歌采纳,获得10
7秒前
momo发布了新的文献求助10
8秒前
8秒前
欣欣发布了新的文献求助10
9秒前
9秒前
令狐远航发布了新的文献求助10
9秒前
亚琛求文献完成签到,获得积分10
9秒前
11秒前
崔啦啦发布了新的文献求助30
11秒前
11秒前
11秒前
12秒前
美好斓发布了新的文献求助30
12秒前
Gao_Z_X完成签到 ,获得积分10
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1500
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6366068
求助须知:如何正确求助?哪些是违规求助? 8180033
关于积分的说明 17244016
捐赠科研通 5420817
什么是DOI,文献DOI怎么找? 2868247
邀请新用户注册赠送积分活动 1845373
关于科研通互助平台的介绍 1692871