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            Chapter 1 Affective Forecasting and Substantial Self-Knowledge

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            Author(s)
            Tooming, Uku
            Miyazono, Kengo
            Language
            English
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            Abstract
            1. This chapter argues that our self-knowledge is often mediated by our affective self-knowledge. In other words, we often know about ourselves by knowing our own emotions. More precisely, what Cassam has called “substantial self-knowledge” (SSK), such as self-knowledge of one's character, one's values, or one's aptitudes, is mediated by affective forecasting, which is the process of predicting one's emotional responses to possible situations. For instance, a person comes to know that she is courageous by predicting her own emotional reactions to possible risks and dangers. This hypothesis explains why attaining substantive self-knowledge tends to be difficult. Attaining substantive self-knowledge is difficult because, first, SSK is mediated by affective forecasting and, second, we tend to be wrong about predicting the intensity and duration of our own emotional reactions. As a result, we can identify what is common to central cases of SSK: such cases require knowledge about complex dispositions whose manifestations involve affective responses that one is not sufficiently familiar with. One thus needs to resort to the highly fallible method of affective forecasting.
            Book
            Emotional Self-Knowledge
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/186846
            Keywords
            Alba Montes Sánchez and Alessandro Salice; thema EDItEUR::Q Philosophy and Religion::QD Philosophy::QDT Topics in philosophy::QDTM Philosophy of mind
            DOI
            10.4324/9781003310945-3
            ISBN
            9781032317106, 9781032317113
            Publisher
            Taylor & Francis
            Publisher website
            http://www.taylorandfrancis.com/
            Publication date and place
            2023
            Imprint
            Routledge
            Pages
            23
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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