moral expertise
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2021 ◽  
Vol 98 (3) ◽  
pp. 436-445
Author(s):  
Jakob Lohmar

Abstract Moral expertise requires a level of reliability in moral matters that is significantly higher than that of the average person. The author argues that this requirement of epistemic superiority in moral matters is sometimes fulfilled by our future selves and generally fulfilled by present moral philosophers. Our future selves are more reliable in answering moral questions than we are, when they have been prepared to answer those questions by various epistemic activities. But if our future selves are our epistemic superiors in such cases, moral philosophers are epistemic superiors in moral matters more generally since their epistemic advantages are even more significant. The author concludes by arguing that moral philosophers plausibly even qualify as moral experts.


Author(s):  
Kian Mintz-Woo

This chapter introduces several distinctions relevant to what is called the “discounting problem”, since the issue is how (future) costs and benefits are discounted to make them comparable in present terms. The author defends the claim that there are good reasons to adopt Ramsey-style discounting in the context of climate change: the Ramsey rule is robust, flexible, and well-understood. An important distinction involved in discounting—“descriptivism” and “prescriptivism”—is discussed. It is argued that, even if we adopt prescriptivism, and accept that this means there is need for moral experts in parameter assignments, there is a significant issue. The type of moral expertise required for the discounting problem will not involve knowledge of moral theory—thus making moral philosophy unhelpful in terms of making particular parameter assignments, despite these being substantive moral judgments.


2021 ◽  
pp. 737-737
Author(s):  
Henk ten Have ◽  
Maria do Céu Patrão Neves
Keyword(s):  

2020 ◽  
Vol 33 (2) ◽  
pp. 283-308
Author(s):  
Susanne M. Schmittat ◽  
Pascal Burgmer
Keyword(s):  

2020 ◽  
Vol 55 ◽  
pp. 195-221
Author(s):  
Dong-Chang Kim ◽  
Keyword(s):  

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