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

Öz

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.

Anahtar Kelimeler

• tarih
• yapay zekâ
• tarihçilik
• kaynak tenkidi
• provenans

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)

Öz

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.

Anahtar Kelimeler

• history
• artificial intelligence
• historical profession
• source criticism
• provenance

Kaynakça

1. American Historical Association. “Guiding Principles for Artificial Intelligence in History Education.” August 5, 2025. https://www.historians.org/resource/guiding-principles-for-artificial-intelligence-in-history-education/. American Historical Association. “Statement on Standards of Professional Conduct.” January 7, 2023. https://www.historians.org/resource/statement-on-standards-of-professional-conduct/.
2. Anderson, Benjamin G. “Kindred Contexts: Archives, Archaeology, and the Concept of Provenance.” Archival Science 24 (2024): 761–781. https://doi.org/10.1007/s10502-024-09459-5.
3. Ankersmit, Frank R. Historical Representation. Stanford, CA: Stanford University Press, 2001.
4. Arrow, Michelle. “Historians and Generative AI.” History Australia 22, no. 4 (2025): 586–589. https://doi.org/10.1080/14490854.2025.2570452.
5. Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. New York: ACM, 2021. https://doi.org/10.1145/3442188.3445922.
6. Bilgin Taşdemir, Esma F., Zeynep Tandoğan, S. Doğan Akansu, Fırat Kızılırmak, M. Umut Şen, Aysu Akcan, Mehmet Kuru, and Berrin Yanıkoğlu. “Automatic Transcription of Ottoman Documents Using Deep Learning.” In Document Analysis Systems, 422–435. Cham: Springer, 2024. https://doi.org/10.1007/978-3-031-70442-0_26.
7. Bloch, Marc. The Historian’s Craft. Translated by Peter Putnam. New York: Knopf, 1953.
8. Burzlaff, Jan. “Fragments, Not Prompts: Five Principles for Writing History in the Age of AI.” Rethinking History (2025). https://doi.org/10.1080/13642529.2025.2546174.

9. Campbell, Chris. “The Historian in the Age of AI.” Transactions of the Royal Historical Society (2025): 1–11. https://doi.org/10.1017/S0080440125100509.
10. Canning, David, and Lise Jaillant. “AI to Review Government Records: New Work to Unlock Historically Significant Digital Records.” AI & Society 40 (2025): 4433–4455. https://doi.org/10.1007/s00146-025-02221-0.
11. Carr, E. H. What Is History? Basingstoke: Palgrave, 2001. Originally published 1961.
12. Coalition for Content Provenance and Authenticity. “C2PA Technical Specification, Version 2.4.” April 2026. https://spec.c2pa.org/specifications/specifications/2.4/specs/C2PA_Specification.html.
13. Collingwood, R. G. The Idea of History. Oxford: Clarendon Press, 1946.
14. Danto, Arthur C. Analytical Philosophy of History. Cambridge: Cambridge University Press, 1965.
15. Drucker, Johanna. “Humanities Approaches to Graphical Display.” Digital Humanities Quarterly 5, no. 1 (2011). https://digitalhumanities.org/dhq/vol/5/1/000091/000091.html.
16. Faroqhi, Suraiya. Approaching Ottoman History: An Introduction to the Sources. Cambridge: Cambridge University Press, 1999.
17. Fickers, Andreas. “Towards a New Digital Historicism? Doing History in the Age of Abundance.” VIEW Journal of European Television History and Culture 1, no. 1 (2012): 19–26.
18. Fickers, Andreas. “Update für die Hermeneutik: Geschichtswissenschaft auf dem Weg zur digitalen Forensik?” Zeithistorische Forschungen/Studies in Contemporary History 17, no. 1 (2020): 157–168. https://doi.org/10.14765/zzf.dok-1765.
19. Fickers, Andreas, Juliane Tatarinov, and Tim van der Heijden, eds. Digital History and Hermeneutics: Between Theory and Practice. Berlin: De Gruyter, 2022.
20. Ginzburg, Carlo. History, Rhetoric, and Proof. Hanover, NH: Brandeis University Press, 1999.
21. Hughes-Warrington, Marnie. “Toward the Recognition of Artificial History Makers.” History and Theory 61, no. 4 (2022): 107–118. https://doi.org/10.1111/hith.12278.
22. Hughes-Warrington, Marnie. “Ethics for Artificial Historians.” History and Theory 64, no. 2 (2025): 159–177. https://doi.org/10.1111/hith.12377.
23. Hughes-Warrington, Marnie. History and Artificial Intelligence. Cambridge: Cambridge University Press, 2026. https://doi.org/10.1017/9781009572187.
24. Jaillant, Lise, and Kim Aske. “Are Users of Digital Archives Ready for the AI Era? Obstacles to the Application of Computational Research Methods and New Opportunities.” Journal on Computing and Cultural Heritage 16, no. 4 (2024): Article 87. https://doi.org/10.1145/3631125.
25. Jaillant, Lise, and Anna Rees. “Applying AI to Digital Archives: Trust, Collaboration and Shared Professional Ethics.” Digital Scholarship in the Humanities 38, no. 2 (2023): 571–585. https://doi.org/10.1093/llc/fqac073.
26. Jo, Eun Seo, and Timnit Gebru. “Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning.” In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 306–316. New York: ACM, 2020. https://doi.org/10.1145/3351095.3372829.
27. Kiessling, Benjamin, Robin Tissot, Peter Stokes, and Daniel Stökl Ben Ezra. “eScriptorium: An Open Source Platform for Historical Document Analysis.” In 2019 International Conference on Document Analysis and Recognition Workshops, vol. 2, 19–24. IEEE, 2019.
28. Koolen, Marijn, Jasmijn van Gorp, and Jacco van Ossenbruggen. “Toward a Model for Digital Tool Criticism: Reflection as Integrative Practice.” Digital Scholarship in the Humanities 34, no. 2 (2019): 368–385. https://doi.org/10.1093/llc/fqy048.
29. Kütükoğlu, Mübahat S. Osmanlı Belgelerinin Dili (Diplomatik). İstanbul: Kubbealtı Akademisi Kültür ve San’at Vakfı, 1994.
30. Langlois, Charles-Victor, and Charles Seignobos. Introduction to the Study of History. Translated by G. G. Berry. London: Duckworth, 1904. Originally published 1898.
31. McLean, Mark A., David A. Roberts, and Martin Gibbs. “Ghosts and the Machine: Testing the Use of Artificial Intelligence to Deliver Historical Life Course Biographies from Big Data.” Historical Methods 57, no. 3 (2024): 146–162. https://doi.org/10.1080/01615440.2024.2398455.
32. Muehlberger, Guenter, Louise Seaward, Melissa Terras, Sofia Ares Oliveira, Vicente Bosch, Maximilian Bryan, et al. “Transforming Scholarship in the Archives through Handwritten Text Recognition: Transkribus as a Case Study.” Journal of Documentation 75, no. 5 (2019): 954–976. https://doi.org/10.1108/JD-07-2018-0114.
33. Öncel, Fatma, Ali Yaycıoğlu, and Ezgi Çolakoğlu. “Data Modeling for Historical Manuscripts: Relational Database Design for an Ottoman Fiscal Codex.” In DH2024 Book of Abstracts. Zenodo, 2024. https://doi.org/10.5281/zenodo.13761079.
34. Putnam, Lara. “The Transnational and the Text-Searchable: Digitized Sources and the Shadows They Cast.” American Historical Review 121, no. 2 (2016): 377–402. https://doi.org/10.1093/ahr/121.2.377.
35. Ricoeur, Paul. Time and Narrative. Vol. 1. Translated by Kathleen McLaughlin and David Pellauer. Chicago: University of Chicago Press, 1984.
36. Rosenzweig, Roy. “Scarcity or Abundance? Preserving the Past in a Digital Era.” American Historical Review 108, no. 3 (2003): 735–762. https://doi.org/10.1086/529596.
37. Simons, Arno, Michael Zichert, and Adrian Wüthrich. “Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives.” Studies in History and Philosophy of Science 117 (2026): 102151. https://doi.org/10.1016/j.shpsa.2026.102151.
38. Stewart, Spencer Dean, and Sanskriti Sinha. “Retrieving Information from Unstructured Historical Sources Using Large Language Models.” Computational Humanities Research 1 (2025): e17. https://doi.org/10.1017/chr.2025.10019.
39. Stoler, Ann Laura. Along the Archival Grain: Epistemic Anxieties and Colonial Common Sense. Princeton, NJ: Princeton University Press, 2009.
40. Trouillot, Michel-Rolph. Silencing the Past: Power and the Production of History. Boston: Beacon Press, 1995. Tucker, Aviezer. Our Knowledge of the Past: A Philosophy of Historiography. Cambridge: Cambridge University Press, 2004.
41. White, Hayden. Metahistory: The Historical Imagination in Nineteenth-Century Europe. Baltimore: Johns Hopkins University Press, 1973.
42. Yaycıoğlu, Ali, Antonis Hadjikyriacou, Fatma Öncel, Erik Steiner, and Petros Kastrinakis. “Mapping Ottoman Epirus.” Journal of the Ottoman and Turkish Studies Association 9, no. 2 (2022): 145–152. https://doi.org/10.2979/jottturstuass.9.2.20.