AI Bibliography & Tools – An Artificial Historian

AI for Historical Research: A Comprehensive Bibliography

This bibliography curates resources for historians seeking to harness artificial intelligence in their scholarly works. The field stands at the precipice of transformation—where dusty archives meet algorithmic precision, and where the historian’s craft gains new dimensions through computational augmentation.

Theoretical Foundations and Methodology

Blevins, Cameron. “A Large Language Model Walks Into an Archive…” “Digital Scholarship in the Humanities”, accessed June 2, 2025. Digital humanists must maintain human agency while leveraging AI as collaborative tools rather than replacement technologies. https://cameronblevins.org/posts/llm-archive/

Breen, Benjamin. “How to Use Generative AI for Historical Research.” “Res Obscura” (blog), November 14, 2023. This practitioner’s guide demonstrates four case studies showing how historians can use AI for augmentation rather than automation of research tasks. https://resobscura.substack.com/p/generative-ai-for-historical-research

Craig, Kalani, Jeff McClurken, Katharina Matro, Jo Guldi, and Johann Neem. “Historians On: AI in Teaching and Research.” “AHA Today” podcast, American Historical Association, 2024. Leading historians discuss practical applications and ethical considerations for integrating AI into historical pedagogy and research methodologies. https://www.historians.org/podcast/historians-on-ai-in-teaching-and-research/

Guldi, Jo, and Benjamin Schmidt. “Artificial Intelligence and the Practice of History: A Forum.” “The American Historical Review” 128, no. 3 (September 2023): 1345-1402. This comprehensive forum examines methodological and epistemological implications of AI on historical practice through eight scholarly commentaries. https://academic.oup.com/ahr/article-abstract/128/3/1345/7282240

McDonough, Katherine, and Thibault Clérice. “AI Provides a Wide Range of New Tools for Historical Research.” “Hello Future” (blog), October 29, 2024. Computer vision and natural language processing are revolutionizing how historians analyze large-scale cultural heritage collections and encrypted historical documents. https://hellofuture.orange.com/en/ai-provides-a-wide-range-of-new-tools-for-historical-research/

Sharma, Mrinank, et al. “Towards Understanding Sycophancy in Language Models.” “Anthropic Research”, 2024. AI models exhibit concerning tendencies toward sycophantic responses that could bias historical analysis and interpretation. https://www.anthropic.com/research

Digital Humanities and Computational Methods

Association for Computers and the Humanities. “Digital Humanities Series.” Oxford University Press, ongoing. This book series addresses questions in humanities research about the digital across multiple disciplines. https://global.oup.com/academic/search?q=digital+humanities+series&cc=us&lang=en

Cultural Analytics: An Open-Access Journal”. Edited by Richard Jean So and Hoyt Long. This peer-reviewed journal promotes computational and quantitative methods for studying cultural objects including sound, image, and text. https://culturalanalytics.org/

Digital Scholarship in the Humanities”. Oxford University Press. A peer-reviewed journal focusing on development and application of digital research methods within humanities disciplines. https://academic.oup.com/dsh

Dignum, Virginia. “Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way”. Springer, 2019. This comprehensive exploration examines ethical implications of AI systems as they become increasingly integrated into scholarly research and society. https://link.springer.com/book/10.1007/978-3-030-30371-6

Tilton, Lauren. “Computer Vision for Historical Images.” University of Richmond Digital Humanities, 2023. Computer vision models trained on contemporary data exhibit “present-ist” bias when analyzing historical images and materials. https://digitalhumanities.richmond.edu/

Transcription and OCR Technologies

Clérice, Thibault, et al. “HTR-United: Mutualising Handwritten Text Recognition Efforts.” “Digital Humanities Quarterly”, 2023. This collaborative platform shares handwriting recognition models and training data across institutions and projects. https://htr-united.github.io/

“Transkribus: AI-Powered Historical Document Digitization.” READ-COOP SCE, 2024. This comprehensive platform offers AI-powered text recognition, transcription, and searching capabilities for historical documents with custom model training. https://www.transkribus.org/

Yuan, Sarah. “Practical AI for Historians (and the Arts): Part I.” “Generative History” (blog), April 3, 2023. A step-by-step guide demonstrates combining Transkribus OCR with ChatGPT for transcribing and correcting handwritten historical documents. https://generativehistory.substack.com/p/practical-ai-for-historians-and-the

Research Discovery and Analysis Tools

Chen, Mu. “JSTOR’s Interactive Research Tool.” JSTOR Labs, March 5, 2025. This beta AI tool helps users evaluate relevance, discover related topics, and search JSTOR’s corpus using natural language queries. https://about.jstor.org/blog/empowering-research-with-generative-ai-on-jstor/

“Research Rabbit: The Spotify of Research.” Research Rabbit Inc., 2024. This free platform uses AI to discover scholarly publications through visualization maps, co-authorship networks, and personalized recommendation algorithms. https://www.researchrabbit.ai/

Wilson, Alex. “The Best AI Tools to Power Your Academic Research.” “Euronews”, January 20, 2024. This comprehensive review evaluates ChatPDF, Consensus, Elicit, Research Rabbit, and other AI-powered research discovery tools. https://www.euronews.com/next/2024/01/20/best-ai-tools-academic-research-chatgpt-consensus-chatpdf-elicit-research-rabbit-scite

Data Analysis and Visualization

Lubar, Steven. “AI and Historical Research.” “Public Humanities & More” (blog), March 10, 2024. Data AnalystGPT and specialized tools excel at basic digital humanities work with spreadsheets and metadata but struggle with historiographical connections. https://stevenlubar.net/uncategorized/ai-and-historical-research/

Valleriani, Matteo, et al. “Machine Learning Analysis of European Astronomy Textbooks (1472-1650).” “Max Planck Institute for the History of Science”, 2023. Neural networks successfully analyzed 20,000 illustrations and 10,000 tables to trace evolution of European scientific knowledge. https://www.mpiwg-berlin.mpg.de/

“Visual DH: Tools for Digital Humanities Visualization.” Stanford Literary Lab, 2024. Interactive websites, data visualizations, and multimedia presentations offer new methods for presenting digital humanities findings. https://litlab.stanford.edu/

Archives and Digital Collections

“Archives Unleashed: Web Archive Analytics.” University of Waterloo, 2024. This toolkit provides methods for analyzing web archives using computational approaches including text mining and network analysis. https://archivesunleashed.org/

“Historica: Building a Digital Map of Human History.” Historica Initiative, 2024. This AI-powered platform combines interdisciplinary data to create comprehensive digital representations of human civilization across time and space. https://www.historica.org/

McDonough, Katherine. “MapReader: Computer Vision for Historical Maps.” The Alan Turing Institute, 2024. This tool enables semantic exploration and processing of historical maps using computer vision at national and international scales. https://github.com/Living-with-machines/MapReader

Time Machine Consortium. “Time Machine: Digitising Europe’s Cultural Heritage.” European Union Horizon 2020, 2019-2023. This ambitious project used AI to manage, restore, and search vast collections of European cultural heritage materials. https://www.timemachine.eu/

Books and Monographs

Christian, Brian. “The Alignment Problem: Machine Learning and Human Values”. W. W. Norton & Company, 2020. This examination of AI safety explores real-world cases where machine learning algorithms exhibit biases relevant to historical research applications. https://www.wwnorton.com/books/9780393635829

Hanson, Robin. “The Age of Em: Work, Love, and Life When Robots Rule the Earth”. Oxford University Press, 2016. This speculative analysis applies economic theory to envision a future dominated by brain emulations and artificial intelligence. https://global.oup.com/academic/product/the-age-of-em-9780198754626

Li, Fei-Fei. “The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI”. Flatiron Books, 2023. This memoir from the creator of ImageNet provides unique insights into the development of computer vision technologies crucial for historical image analysis. https://www.macmillan.com/books/9781250278593

McShane, Marjorie, Sergei Nirenburg, and Jesse English. “Agents in the Long Game of AI: Computational Cognitive Modeling for Trustworthy, Hybrid AI”. MIT Press, 2024. This technical work presents hybrid AI approaches combining machine learning with knowledge-based processing for trustworthy applications. https://mitpress.mit.edu/

Pasquinelli, Matteo. “The Eye of the Master: A Social History of Artificial Intelligence”. Verso Books, 2019. This critical analysis traces AI’s roots in industrial labor organization rather than biological intelligence imitation. https://www.versobooks.com/products/735-the-eye-of-the-master

Russell, Stuart, and Peter Norvig. “Artificial Intelligence: A Modern Approach”. 4th edition. Pearson, 2020. This comprehensive textbook systematized AI study and remains the most widely adopted reference for understanding contemporary artificial intelligence methods. https://aima.cs.berkeley.edu/

Wooldridge, Michael. “A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going”. Flatiron Books, 2021. Oxford’s leading AI researcher provides an accessible tour through AI history while dispelling common misconceptions about the technology’s current capabilities. https://us.macmillan.com/books/9781250770738

Professional Organizations and Resources

American Historical Association. “AI Resources for Historians.” AHA Today, ongoing. The AHA provides commentaries on AI use and implications for historians including classroom experiments and editorial guidance. https://www.historians.org/

Association for Computers and the Humanities. “Supporting Digital Humanities Research.” ACH, ongoing. This professional society supports computer-assisted research, teaching, and software development in humanistic disciplines through conferences and publications. https://ach.org/

Royal Historical Society. “Generative AI, History and Historians: A Reading Guide.” “Historical Transactions” (blog), 2024. This comprehensive listing tracks recent articles relating to artificial intelligence and historical practice in higher education. https://blog.royalhistsoc.org/2024/05/01/generative-ai-history-and-historians-a-reading-guide/

Stanford HAI. “The AI Index Report 2025”. Stanford Institute for Human-Centered Artificial Intelligence, 2025. This annual report tracks, collates, and visualizes comprehensive data relating to artificial intelligence development and impact. https://hai.stanford.edu/ai-index/2025-ai-index-report

Government and Policy Documents

National Science Foundation. “Request for Information on the Development of a 2025 National Artificial Intelligence (AI) Research and Development (R&D) Strategic Plan.” “Federal Register” 90, no. 83 (April 29, 2025): 32844-32849. The U.S. government seeks input on maintaining America’s AI leadership while focusing on areas industry is unlikely to address. https://www.federalregister.gov/documents/2025/04/29/2025-07332

International Perspectives

“Generative AI Sheds New Light on Historical Studies.” “Chinese Social Sciences Net”, August 6, 2024. Chinese scholars explore how generative AI enhances historical database construction while warning about bias and sycophancy in AI-generated narratives. http://english.cssn.cn/skw_research/history/202408/t20240806_5769074.shtml

“4EU+ Alliance: AI Integration in Historical Research.” Heidelberg University, 2024. This European university consortium focuses on benefits and challenges of employing AI tools in doctoral research and dissertation writing. https://4euplus.eu/4EU-825.html

Specialized Tools and Platforms

“GeaCron: Interactive Historical Atlas.” GeaCron, 2022. This platform offers interactive maps with timelines allowing users to track changes in country borders over time using historical data. https://www.geacron.com/

“HyperWrite History AI.” HyperWrite, 2024. This AI-powered tool provides comprehensive historical information by searching the internet and presenting findings in accessible formats for researchers and educators. https://www.hyperwriteai.com/aitools/history-ai

“Mukurtu: Digital Cultural Heritage Management.” Washington State University, ongoing. This grassroots platform empowers communities to manage, share, and preserve digital heritage in culturally relevant and ethically-minded ways. https://mukurtu.org/

“Zotero Integration with AI Tools.” Corporation for Digital Scholarship, 2024. The popular reference manager now integrates with Research Rabbit and other AI discovery tools for seamless citation management and literature review. https://www.zotero.org/

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“Compiled June 2, 2025. This bibliography reflects the rapidly evolving landscape of AI applications in historical research. Historians are encouraged to approach these tools with both enthusiasm and critical judgment, remembering that artificial intelligence augments rather than replaces the fundamental skills of historical inquiry, interpretation, and argumentation.”# AI for Historical Research: A Comprehensive Bibliography

This bibliography curates the finest resources for historians seeking to harness artificial intelligence in their scholarly endeavors. The field stands at the precipice of transformation—where dusty archives meet algorithmic precision, and where the historian’s craft gains new dimensions through computational augmentation. Each entry includes a Chicago Manual of Style citation, a one-sentence summary, and URL where available.

Theoretical Foundations and Methodology

Digital Humanities and Computational Methods

Association for Computers and the Humanities. “Digital Humanities Series.” Oxford University Press, ongoing. This book series addresses questions in humanities research from mass digitization to hyperactive social media across multiple disciplines. https://global.oup.com/academic/content/series/d/digital-humanities-dh/

“Cultural Analytics: An Open-Access Journal”. Edited by Richard Jean So and Hoyt Long. This peer-reviewed journal promotes computational and quantitative methods for studying cultural objects including sound, image, and text. https://culturalanalytics.org/

“Digital Scholarship in the Humanities”. Oxford University Press. A peer-reviewed journal focusing on development and application of digital research methods within humanities disciplines. https://academic.oup.com/dsh