Dil, Düşünce ve Turing: Davidson'ın Makine Zekasının Sınırlarına İlişkin Görüşleri

Year 2024, Issue: 79, 147 - 164, 15.07.2024

Cansu Akoglan

https://doi.org/10.58634/felsefedunyasi.1481945

Cited By: 1

Abstract

Bu makale, ilk olarak 1950 yılında Alan Turing tarafından önerilen ve makine zekasını dilsel iletişimde insan davranışını taklit etme becerisine göre değerlendiren Turing Testi'ni incelemektedir. Turing Testi yapay zeka araştırmalarının temelini oluştururken, önemli felsefi itirazlarla da karşı karşıya kalmıştır. Bu makalenin odak noktası, Turing Testi'nin, temelde sosyal ve iletişimsel olan düşünce ve önermesel tutumların karmaşıklığını açıklamakta başarısız olduğunu savunan Donald Davidson'ın eleştirisidir. Tartışma, sofistike dil modelleri gibi bazı yapay zeka teknolojilerinin bu felsefi itirazlara ne şekilde yenik düştüğünün bir analizini içermektedir. Makalede, Turing Testi'nin makine "zekası" için pragmatik bir ölçüt sunmasına rağmen, Davidson tarafından öngörülen insan düşüncesinin nüanslı yeteneklerini tam olarak yakalayamadığı, dolayısıyla makine düşüncesini değerlendirmek için daha geniş kriterlere ihtiyaç duyulduğu sonucuna varılmakta ve makine bilişini değerlendirirken etkileşimsel ve bağlamsal dinamikleri göz önünde bulunduran bir yaklaşıma duyulan ihtiyacın altı çizilmektedir.

Keywords

Turing Testi, Önermesel Tutumlar, Donald Davidson, İnsan-Makine Etkileşimi, Üçgenleme

Language, Thought and Turing: Davidson's Views on the Limits of Machine Intelligence

Abstract

This article examines the Turing Test, initially proposed by Alan Turing in 1950, to assess machine intelligence by its ability to mimic human behavior in linguistic communication. While Turing's Test has been foundational in artificial intelligence research, it has faced substantial philosophical scrutiny. The focus of this paper is on Donald Davidson’s critique, which argues that the Turing Test fails to account for the complexities of thought and propositional attitudes that are fundamentally social and communicative. The discussion includes an analysis of how some AI technologies, such as sophisticated language models, challenge and yet fail to overcome these philosophical objections. The paper concludes that while Turing's Test provides a pragmatic measure for machine "intelligence," it does not fully capture the nuanced capabilities of human thought as envisioned by Davidson, thereby necessitating broader criteria for evaluating machine thinking. The implications for future AI development and testing are considered, underscoring the need for an approach that integrates interactional and contextual dynamics in assessing machine cognition.

Keywords

Turing’s Test, Propositional Attitudes, Donald Davidson, Human-Machine Interaction, Triangulation

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