用人工智能框架理解人类认知,是比喻还是可改造的思维工具?
Artificial Intelligence, conceptual metaphors and conceptual engineering: Are AI-based framings of human behaviour and cognition successful?
- 将AI概念用于解释人类认知,本质是隐喻而非真实对应。
- 错误使用会陷入‘地图即领土’的认知谬误。
- 若克服伦理与还原论难题,可成为概念革新突破口。
利用人工智能领域的概念来理解人类行为、神经科学与心理学正日益流行。随着AI技术深度融入日常生活,人们常将AI系统与人类行为、脑功能及语言习得等认知能力相类比。但科学家与哲学家也逐渐将这种类比视为字面真实。本文探讨这些‘AI框架’在认识论与实践层面的成功性:将AI概念体系应用于人类认知领域意味着什么?我们分析两种可能解释——或为概念隐喻,或为概念工程尝试。首先,若视为隐喻,则易陷入‘地图即领土’的谬误;其次,此类类比本身存在误导性的‘双重隐喻’,因计算与心理间的隐喻关联根植于概念基础。然而,也存在潜在语义契机,这正是概念工程视角所揭示的:某些AI框架或可指引概念重构路径。若能克服概念伦理与还原主义挑战,部分框架或能丰富我们的认知与实践生活。最糟情况下,它误导我们;最佳情形下,则促使我们重新审视现有概念边界及其优化可能。
原文摘要 · Abstract (English)
Understanding human behaviour, neuroscience and psychology using concepts from the domain of AI is increasing in popularity. Given the massive integration of AI technologies into our daily lives, AI-related concepts are being used to compare AI systems with human behaviour, brain functions, and cognitive abilities like language acquisition. But scientists and philosophers are also increasingly tempted to take the AI-framing of the human conceptual domain as a literal one. This paper investigates the epistemic and practical success of these 'AI-framings': What does it mean to apply the conceptual constellation of AI to the human conceptual domain? We consider and compare two possible answers: either these examples are conceptual metaphors, or they are attempts at conceptual engineering. Firstly, we argue that when viewed as conceptual metaphors, the AI-framed descriptions risk committing the ''map-territory fallacy''. Secondly, we argue the comparisons also contain a misleading 'double metaphor' because of the metaphorical connection between human psychology and computation at the conceptual foundation of computation. But we also argue that there is a possible semantic catch to the AI-framing, which is captured by the conceptual engineering view. This is that the AI-framings point towards avenues for forms of conceptual engineering. If the challenges of conceptual ethics and reductionism are overcome, some AI-framings might enrich our epistemic and practical lives. So, at its worst - as implicit conceptual metaphor - the AI-framing leads us completely astray; at its best, it prompts us to reflect anew on how the boundaries of our current concepts serve us and how they could be improved.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。