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Journals / Tarih ve Gelecek Dergisi - Uluslararası Hakemli Tarih Araştırmaları Dergisi / 2026 / Cilt: 12 Sayı: 3

How Can Historical Knowledge Be Validated in the Age of Artificial Intelligence? Reconstructing the Historical Profession and Source Criticism at the Algorithmic Threshold (2022–2026)

Yapay Zekâ Çağında Tarihsel Bilgi Nasıl Doğrulanabilir? Tarihçilik Mesleği Ve Kaynak Tenkidinin Algoritmik Eşikte Yeniden Kuruluşu (2022–2026)

Sinan Işıldak0000-0001-6969-8070
Pages
808–840
Publication Date
2026-10-02
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It concludes that the future historian will be distinguished not by an exclusive capacity to generate prose, but by the ability to audit chains of evidence, preserve uncertainty, test counter-evidence, and assume responsibility for historical claims.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study examines how the rapid expansion of generative artificial intelligence, large language models, automated transcription, and digital provenance technologies between 2022 and 2026 affects the validation of historical knowledge, the boundaries of the historical profession, and the method of source criticism.
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Key Findings & Data:It compares philosophy of history, classical historical methodology, digital history, archival studies, and recent history-and-AI scholarship through a critical integrative document analysis, focusing on evidence, context, narrative, error, and accountability in human-machine research workflows.
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Conclusion & Impact:It concludes that the future historian will be distinguished not by an exclusive capacity to generate prose, but by the ability to audit chains of evidence, preserve uncertainty, test counter-evidence, and assume responsibility for historical claims.
🔬Design:Modeling & Simulation
📍Scope:2022 Verileri
⚙️Variables:tarih · yapay zekâ · tarihçilik

Abstract

This study examines how the rapid expansion of generative artificial intelligence, large language models, automated transcription, and digital provenance technologies between 2022 and 2026 affects the validation of historical knowledge, the boundaries of the historical profession, and the method of source criticism. It compares philosophy of history, classical historical methodology, digital history, archival studies, and recent history-and-AI scholarship through a critical integrative document analysis, focusing on evidence, context, narrative, error, and accountability in human-machine research workflows. The analysis shows that AI should be understood less as an autonomous substitute for the historian than as an epistemic mediator that lengthens the chain between source and claim. Classical external and internal criticism therefore remain necessary but must be extended to digital surrogates, machine reading, data models, algorithmic inference, narrative synthesis, and accountability. The article’s original contribution is an eight-layer Transformational Source Criticism Model that systematizes this enlarged field of criticism. It concludes that the future historian will be distinguished not by an exclusive capacity to generate prose, but by the ability to audit chains of evidence, preserve uncertainty, test counter-evidence, and assume responsibility for historical claims.

Özet

Bu araştırma, 2022–2026 arasında hızlanan üretken yapay zekâ, büyük dil modeli, otomatik transkripsiyon ve dijital provenans uygulamalarının tarihsel bilginin doğrulanması, tarihçilik mesleğinin sınırları ve kaynak tenkidinin yöntemi üzerindeki etkisini incelemektedir. Çalışma, tarih felsefesi, klasik tarih metodolojisi, dijital tarih, arşiv bilimi ve güncel yapay zekâ-tarih literatürünü eleştirel-bütünleştirici doküman analiziyle karşılaştırmakta; insan ve algoritma arasındaki iş bölümünü kanıt, bağlam, anlatı, hata ve sorumluluk kavramları üzerinden çözümlemektedir. Analiz, yapay zekânın tarihçinin yerine geçen özerk bir fail olmaktan çok, kaynak ile iddia arasındaki dönüşüm zincirini uzatan bir epistemik aracı olduğunu göstermektedir. Bu nedenle klasik dış ve iç tenkidin korunarak dijital vekil, makine okuması, veri modeli, algoritmik çıkarım, anlatısal sentez ve sorumluluk düzeylerine genişletilmesi önerilmektedir. Makalenin özgün katkısı, bu dönüşümü sekiz katmanlı Dönüşümsel Kaynak Tenkidi Modeli içinde sistemleştirmesidir. Sonuç olarak geleceğin tarihçisi, metin üretme ayrıcalığıyla değil; kanıt zincirini denetleme, belirsizliği görünür kılma, karşı kanıtı tartma ve nihai tarihsel iddianın sorumluluğunu üstlenme kapasitesiyle tanımlanmaktadır.

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Cite This Article

Işıldak, S. (2026). How Can Historical Knowledge Be Validated in the Age of Artificial Intelligence? Reconstructing the Historical Profession and Source Criticism at the Algorithmic Threshold (2022–2026). Tarih ve Gelecek Dergisi - Uluslararası Hakemli Tarih Araştırmaları Dergisi, Cilt: 12 Sayı: 3, 808–840. https://doi.org/10.21551/jhf.2046022

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