Nurturing Knowledge: A Virtue Epistemology Approach to Explainable AI

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25210%2F25%3A39923579" target="_blank" >RIV/00216275:25210/25:39923579 - isvavai.cz</a>

Výsledek na webu

<a href="https://academic.oup.com/edited-volume/59762/chapter-abstract/538536651?redirectedFrom=fulltext" target="_blank" >https://academic.oup.com/edited-volume/59762/chapter-abstract/538536651?redirectedFrom=fulltext</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1093/9780198945215.003.0176" target="_blank" >10.1093/9780198945215.003.0176</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Nurturing Knowledge: A Virtue Epistemology Approach to Explainable AI

Popis výsledku v původním jazyce

AI technologies, particularly deep neural networks and machine learning models, have become increasingly integrated into knowledge production across diverse scientific domains, raising critical concerns about explainability and interpretability. Different disciplines and contexts require fundamentally different types of explanations, making universal approaches to explainable AI inadequate. Virtue epistemology offers a promising framework for addressing these challenges by focusing on how AI systems cultivate or undermine epistemic virtues within specific knowledge communities. Rather than seeking explanations in abstract terms, virtue epistemology emphasizes epistemic abilities and character traits as they manifest within particular epistemic cultures. Case studies from social science, neuroscience, medicine, and the humanities reveal that meaningful progress in explainable AI requires aligning computational reasoning with the cultivation of epistemic virtues and the mitigation of epistemic vices that characterize each scientific community’s specialized knowledge practices and norms.

Název v anglickém jazyce

Nurturing Knowledge: A Virtue Epistemology Approach to Explainable AI

Popis výsledku anglicky

AI technologies, particularly deep neural networks and machine learning models, have become increasingly integrated into knowledge production across diverse scientific domains, raising critical concerns about explainability and interpretability. Different disciplines and contexts require fundamentally different types of explanations, making universal approaches to explainable AI inadequate. Virtue epistemology offers a promising framework for addressing these challenges by focusing on how AI systems cultivate or undermine epistemic virtues within specific knowledge communities. Rather than seeking explanations in abstract terms, virtue epistemology emphasizes epistemic abilities and character traits as they manifest within particular epistemic cultures. Case studies from social science, neuroscience, medicine, and the humanities reveal that meaningful progress in explainable AI requires aligning computational reasoning with the cultivation of epistemic virtues and the mitigation of epistemic vices that characterize each scientific community’s specialized knowledge practices and norms.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

60302 - Ethics (except ethics related to specific subfields)

Projekt

<a href="/cs/project/GA24-11282S" target="_blank" >GA24-11282S: Neřestné epistemické kultury</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Oxford Intersections: AI in Society

ISBN

978-0-19-894521-5

Počet stran výsledku

19

Strana od-do

1-19

Počet stran knihy

100

Název nakladatele

Oxford University Press

Místo vydání

Oxford

Kód UT WoS kapitoly

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