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domains/ai-alignment/thick-models-of-value-distinguish-enduring-values-from-temporary-preferences-which-the-authors-argue-enables-normative-reasoning.md
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---
type: claim
title: Thick models of value distinguish enduring values from temporary preferences, which the authors argue enables normative reasoning
created: 2025-12-01
domain: ai-alignment
source: "2025-12-01-fullstack-alignment-thick-models-value.md"
confidence: experimental
description: This claim explores the concept of thick models of value as proposed in a single paper, highlighting their potential to distinguish enduring values from temporary preferences. The paper suggests that such models enable normative reasoning, though it lacks empirical validation. The concept of 'thick' refers to models that incorporate rich, context-dependent information, as opposed to 'thin' models that rely on minimal, context-free data. The proposal raises concerns about paternalism, as it suggests a normative framework that could impose specific values.
description: Thick models of value distinguish enduring values from temporary preferences.
created: 2025-12-01
processed_date: 2025-12-01
---
# Thick Models of Value Distinguish Enduring Values from Temporary Preferences
The paper proposes that thick models of value can distinguish enduring values from temporary preferences, enabling normative reasoning. This approach contrasts with thin models, which may overlook the complexity of human values by focusing on context-free data. The authors argue that thick models provide a richer framework for understanding and aligning AI systems with human values. However, the proposal is theoretical and lacks empirical validation. A significant concern is the potential for paternalism, as the normative framework could impose specific values on diverse populations.
# Thick models of value distinguish enduring values from temporary preferences, enabling normative reasoning
Relevant Notes:
- The concept of thick vs. thin models is crucial for understanding the depth and context-dependence of value alignment.
- The proposal is based on a single paper and should be considered experimental until further evidence is available.
The claim is based on a single paper that argues for the importance of distinguishing between enduring values and temporary preferences in AI alignment. This distinction is crucial for enabling normative reasoning within AI systems.
## Relevant Notes
- [[ai-alignment-requires-institutional-co-alignment-not-just-model-alignment]]