Pub Date : 2021-02-11DOI: 10.1093/oso/9780198869153.003.0003
Shaun Nichols
Commonsense, as well as experimental psychology, indicates that there are subtle distinctions in the normative domain. Many people, both adults and children, think that it’s worse to produce a bad consequence than to allow it and that it’s worse to produce a bad consequence with intent than to produce it with mere foreknowledge. People also often think that it’s forbidden to treat people of their own community in a certain way, but not that it’s forbidden to treat people in other communities in that way. It has been unclear exactly how these distinctions arise in ordinary moral thought. This chapter draws on the “size principle,” which is implicated in word learning, to explain how children would use scant and equivocal evidence to acquire these aspects of moral systems.
{"title":"Scope","authors":"Shaun Nichols","doi":"10.1093/oso/9780198869153.003.0003","DOIUrl":"https://doi.org/10.1093/oso/9780198869153.003.0003","url":null,"abstract":"Commonsense, as well as experimental psychology, indicates that there are subtle distinctions in the normative domain. Many people, both adults and children, think that it’s worse to produce a bad consequence than to allow it and that it’s worse to produce a bad consequence with intent than to produce it with mere foreknowledge. People also often think that it’s forbidden to treat people of their own community in a certain way, but not that it’s forbidden to treat people in other communities in that way. It has been unclear exactly how these distinctions arise in ordinary moral thought. This chapter draws on the “size principle,” which is implicated in word learning, to explain how children would use scant and equivocal evidence to acquire these aspects of moral systems.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125732468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/oso/9780198869153.003.0007
Shaun Nichols
Is morality prewired into our minds? The idea that morality is built into us is an old one in philosophy, and it has seen a resurgence of late. Indeed, the prevailing systematic account of how we acquire complex moral representations is a nativist view inspired by arguments in Chomskyan linguistics. If the statistical learning accounts I’ve defended in Part II of this book are right, we have the beginnings of an empiricist account of important aspects of human morality. This chapter offers a sustained defense of a moral empiricist view in the face of the Chomskyan challenge.
{"title":"Moral Empiricism","authors":"Shaun Nichols","doi":"10.1093/oso/9780198869153.003.0007","DOIUrl":"https://doi.org/10.1093/oso/9780198869153.003.0007","url":null,"abstract":"Is morality prewired into our minds? The idea that morality is built into us is an old one in philosophy, and it has seen a resurgence of late. Indeed, the prevailing systematic account of how we acquire complex moral representations is a nativist view inspired by arguments in Chomskyan linguistics. If the statistical learning accounts I’ve defended in Part II of this book are right, we have the beginnings of an empiricist account of important aspects of human morality. This chapter offers a sustained defense of a moral empiricist view in the face of the Chomskyan challenge.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128080823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/oso/9780198869153.003.0004
Shaun Nichols
People seem to expect that rules will be act-based rather than consequence-based. For instance, when people learn a new rule, given minimal evidence, they tend to think that the rule prohibits people from producing a certain consequence, rather than that the rule dictates that such a consequence should be minimized. One explanation is that people have an innate bias to think rules are act-based. This chapter suggests an alternative empiricist proposal. The expectation that rules will be act-based might be explained as a prior that is itself the result of earlier learning. In particular, given that most rules that people have learned are act-based rules, the prior for act-based rules might be acquired through a process of overhypothesis construction.
{"title":"Priors","authors":"Shaun Nichols","doi":"10.1093/oso/9780198869153.003.0004","DOIUrl":"https://doi.org/10.1093/oso/9780198869153.003.0004","url":null,"abstract":"People seem to expect that rules will be act-based rather than consequence-based. For instance, when people learn a new rule, given minimal evidence, they tend to think that the rule prohibits people from producing a certain consequence, rather than that the rule dictates that such a consequence should be minimized. One explanation is that people have an innate bias to think rules are act-based. This chapter suggests an alternative empiricist proposal. The expectation that rules will be act-based might be explained as a prior that is itself the result of earlier learning. In particular, given that most rules that people have learned are act-based rules, the prior for act-based rules might be acquired through a process of overhypothesis construction.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130293068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/OSO/9780198869153.003.0001
Shaun Nichols
To what extent is morality based on reason? To answer this question, we need to clarify which aspect of morality is under investigation, and which notion of reason is in play. Recent work in moral psychology has attempted to debunk central aspects of moral judgment and metaethical judgment. However, rational processes might play a vital role in the acquisition of moral systems. This chapter sets out the basic idea of processes and suggests that one kind of process—statistical learning—is especially significant for moral learning. Statistical learning processes are both empiricist, in that they are domain-general processes, and they are rational, in that they conform to the rules of probability theory. Thus they are poised to provide alternatives to both nativist and sentimentalist accounts of our moral psychology.
{"title":"Rationality and Morality","authors":"Shaun Nichols","doi":"10.1093/OSO/9780198869153.003.0001","DOIUrl":"https://doi.org/10.1093/OSO/9780198869153.003.0001","url":null,"abstract":"To what extent is morality based on reason? To answer this question, we need to clarify which aspect of morality is under investigation, and which notion of reason is in play. Recent work in moral psychology has attempted to debunk central aspects of moral judgment and metaethical judgment. However, rational processes might play a vital role in the acquisition of moral systems. This chapter sets out the basic idea of processes and suggests that one kind of process—statistical learning—is especially significant for moral learning. Statistical learning processes are both empiricist, in that they are domain-general processes, and they are rational, in that they conform to the rules of probability theory. Thus they are poised to provide alternatives to both nativist and sentimentalist accounts of our moral psychology.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115356484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/oso/9780198869153.003.0005
Shaun Nichols
When people learn normative systems, they do so based on limited evidence. Many of the possible actions that are available to an agent have never been explicitly permitted or prohibited. But people will often need to figure out whether those unspecified actions are permitted or prohibited. How does a learner resolve this incompleteness? It seems that at least for many people in many contexts, there is an assumption that if an action-type is not expressly forbidden, then acts of that type are permitted. This “closure principle” is one of Liberty. But how might such a principle be acquired? This chapter argues that the statistical technique of pedagogical sampling provides an answer. If one is taught a rule system via a set of prohibitions, this provides reason to think that the set of actions in the domain that are not mentioned in the prohibitions are permitted.
{"title":"Closure","authors":"Shaun Nichols","doi":"10.1093/oso/9780198869153.003.0005","DOIUrl":"https://doi.org/10.1093/oso/9780198869153.003.0005","url":null,"abstract":"When people learn normative systems, they do so based on limited evidence. Many of the possible actions that are available to an agent have never been explicitly permitted or prohibited. But people will often need to figure out whether those unspecified actions are permitted or prohibited. How does a learner resolve this incompleteness? It seems that at least for many people in many contexts, there is an assumption that if an action-type is not expressly forbidden, then acts of that type are permitted. This “closure principle” is one of Liberty. But how might such a principle be acquired? This chapter argues that the statistical technique of pedagogical sampling provides an answer. If one is taught a rule system via a set of prohibitions, this provides reason to think that the set of actions in the domain that are not mentioned in the prohibitions are permitted.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121493381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/oso/9780198869153.003.0006
Shaun Nichols
Moral judgments are often regarded as universally true, whereas judgments of taste are taken to be only true relative to some group or individual. How could such meta-evaluative assessments be acquired? This chapter argues that people use consensus information to arrive at such assessments, and that it is rational to do so. Statistical inference mandates a trade-off between the extent to which a hypothesis fits the data, and the extent to which the hypothesis is flexible in its ability to fit a wider range of data. If almost everyone agrees in their judgments, this provides some reason to endorse a universalist hypothesis, according to which there is a single fact that the majority is tracking. So if almost everyone thinks that a certain action is wrong, the high consensus provides some evidence that it’s a universal truth that this action is wrong. The inference that it’s a universal truth that an action is wrong can also ground the judgment that the action is wrong in a way that is independent of authority. Thus, this might also provide an explanation for the acquisition of the moral/conventional distinction.
{"title":"Status","authors":"Shaun Nichols","doi":"10.1093/oso/9780198869153.003.0006","DOIUrl":"https://doi.org/10.1093/oso/9780198869153.003.0006","url":null,"abstract":"Moral judgments are often regarded as universally true, whereas judgments of taste are taken to be only true relative to some group or individual. How could such meta-evaluative assessments be acquired? This chapter argues that people use consensus information to arrive at such assessments, and that it is rational to do so. Statistical inference mandates a trade-off between the extent to which a hypothesis fits the data, and the extent to which the hypothesis is flexible in its ability to fit a wider range of data. If almost everyone agrees in their judgments, this provides some reason to endorse a universalist hypothesis, according to which there is a single fact that the majority is tracking. So if almost everyone thinks that a certain action is wrong, the high consensus provides some evidence that it’s a universal truth that this action is wrong. The inference that it’s a universal truth that an action is wrong can also ground the judgment that the action is wrong in a way that is independent of authority. Thus, this might also provide an explanation for the acquisition of the moral/conventional distinction.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131454406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-02-11DOI: 10.1093/OSO/9780198869153.003.0002
Shaun Nichols
The fundamental element of a cognitive account of moral judgment will be some form of representation. Two kinds of value representations need to be distinguished: value representations and rule representations. Value representations register valence for particular courses of action. For instance an organism might represent touching a certain wire as a bad thing. Such representations feed directly into behavior. Rule representations involve more than registering a bad value. They can involve complex representations composed of abstract concepts like impermissible, harm, and knowledge. This chapter argues that value representations cannot provide an adequate account of moral judgment, and that we must invoke rule representations to explain key features of moral judgment. In particular, it is difficult to capture the distinctive nature and specificity of wrongness judgments without adverting to structured rules.
{"title":"The Wrong and the Bad","authors":"Shaun Nichols","doi":"10.1093/OSO/9780198869153.003.0002","DOIUrl":"https://doi.org/10.1093/OSO/9780198869153.003.0002","url":null,"abstract":"The fundamental element of a cognitive account of moral judgment will be some form of representation. Two kinds of value representations need to be distinguished: value representations and rule representations. Value representations register valence for particular courses of action. For instance an organism might represent touching a certain wire as a bad thing. Such representations feed directly into behavior. Rule representations involve more than registering a bad value. They can involve complex representations composed of abstract concepts like impermissible, harm, and knowledge. This chapter argues that value representations cannot provide an adequate account of moral judgment, and that we must invoke rule representations to explain key features of moral judgment. In particular, it is difficult to capture the distinctive nature and specificity of wrongness judgments without adverting to structured rules.","PeriodicalId":383766,"journal":{"name":"Rational Rules","volume":"530 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131825754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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