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This article examines how artificial intelligence is changing historiography by helping to interpret ancient texts, translate languages, and create new historical narratives. It considers the impact of AI on historical accuracy, the challenges posed by the digital divide, and the evolving future of history writing in a technology-driven world.

This article explores how AI is revolutionizing efforts to preserve endangered languages and protect cultural heritage and diversity.

Discover how AI transforms historical research, from deciphering vast colonial archives to mapping forgotten geographies. Using cutting-edge tools like NLP, computer vision, and GIS, researchers uncover hidden narratives in 16th-century documents like the Relaciones Geográficas de Nueva España. This fusion of technology and collaboration with Indigenous communities is reshaping our understanding of history, making the past more accessible.

This article explores how AI can help address the problem of “historical silence,” where marginalized voices are excluded from narratives. Drawing on Michel-Rolph Trouillot’s framework, it highlights the potential of AI to expose biases and create counter-narratives, amplifying overlooked perspectives such as Indigenous resilience.

This article explores the cultural history of artificial intelligence, from ancient myths to contemporary advancements. Learn how AlphaGo and GANs emphasize the connections between technology, philosophy, and culture. It advocates for a transcultural understanding of AI, addressing societal anxieties and aspirations in a narrative that humanizes technology.

This article explores the transformative impact of 3D technologies on archaeological research and documentation. It outlines three primary sensing tools used in modern archaeology: photogrammetry, Lidar scanning, and 3D cameras. Each method's strengths and applications are discussed, highlighting their roles in creating accurate digital representations of artifacts, sites, and landscapes. The integration of artificial intelligence in processing 3D models is examined, including element classification and the conversion of outdated maps into vector polygons.

Digital technologies are transforming cultural heritage preservation, making history more accessible and engaging. From virtual reality experiences to AI-powered restorations, innovative tools are breaking down barriers and allowing deeper connections with historical narratives. Discover the projects and technologies leading this digital revolution in heritage preservation.

This article explores the potential of conversational AI to revolutionize how we interact with large data sets. Such tools could improve research, learning, and global development by allowing users to create personalized maps and data visualizations.

AI could transform how we engage with history by creating social media accounts for historical figures. Users could follow explorers like Columbus or Lewis and Clark in real-time, experiencing their journeys through AI-generated posts based on historical data. This innovative approach offers a new, interactive way to explore the past.

Uncover how Eurocentric bias in AI impacts historical research by marginalizing non-Western histories. Learn about the colonial roots of this bias and the need for diverse datasets to ensure accurate and inclusive historical insights.

AI tools like Transkribus and Whisper transform historical transcription by automating handwritten text and speech recognition. These technologies save time and reduce reliance on volunteers, making historical data more accessible for researchers.

Works of visual art are among the first attempts of human beings to express themselves and probably to leave a long-lasting message...

Modern artificial intelligence tools are changing our understanding of ancient civilizations using advanced satellite data and detailed digital models.

As AI-generated content becomes more prevalent, historians face new challenges in determining the true authorship and reliability of sources. How will future historians navigate this evolving landscape?

This article, featuring the University of Kentucky's award-winning ancient scrolls-deciphering AI software and the author's experiments with AI transcription, reveals how modern technology is bringing new clarity to history. Learn how AI is reimagining our understanding of the past.

Learn how AI revolutionizes historical research with interactive tools like GeaCron and Running Reality. Discover how these cutting-edge applications improve the visualization and analysis of historical data, making the past more accessible and engaging for everyone.

AI brings new life to historical documents. By automating the extraction of addresses from 100,000 historical postcards or converting old maps into satellite images, AI optimizes and reveals new historical facts, making history more accessible and interesting.

This article explores how artificial intelligence is changing the way we think about old portraits. Using advanced technology, old images can now be made more realistic, helping us see historical figures in a new light.

In this feature, the author examines the transformative influence of generative AI on historical scholarship. Discover how this innovative technology is reshaping traditional research methodologies, from data analysis to knowledge dissemination.

Historians are integrating predictive analysis into their research, uncovering hidden patterns in historical data and even forecasting future trends. This approach, notably used to reconstruct ancient texts, presents challenges such as bias and data availability but offers immense potential for deeper historical insights.

In this article, the author explores how AI's capabilities in data analysis, virtual reconstructions, and personalized learning reshape historical education, offering new perspectives and fostering greater engagement.

This article explores the intersection of literature, history, and artificial intelligence through George Orwell's experiences during the Spanish Civil War and his enduring views on language and propaganda.

This article examines the educational implications of using AI in historical research and classroom teaching. Learn how AI is reimagining research methodologies and advancing critical thinking skills and how AI can be used to empower educators and students to navigate the complexities of the past.

In this blog post, author explores the delicate balance between performance and safety in AI applications, focusing on extracting narratives from school history learning materials. The author discusses responsible AI development, favoring transparency and cautious experimentation.

Do large language models possess any kind of “identity”? On the one hand, such models ostensibly stand apart from the identity formations of human life; on the other, they are trained on texts and images derived from a world that understands identity – both claimed and attributed – as an inherent element in navigating social space. This article addresses how far this tension may undermine some of AI’s grander claims, but nonetheless offers distinct ways of thinking about our position in the world, and our relationship to history.

This article explores how Artificial Intelligence (AI) is reshaping archival and historical scholarship, focusing on Handwritten Text Recognition (HTR) systems and ChatGPT.

This article starts from a recent paper on the application of large language models to mathematical problems, to ask how far “evaluating” and “solving” are conceptually useful in understanding the past. It explores whether the idea of knowledge as “discovery” can be applied to history, and, if so, what that would mean for the parameters invoked by, and applied to, machine learning.

Discover the impact of AI on art and history through insightful axioms. Explore ethical considerations, AI's role in historical research, and the balance between human and AI capabilities.

Developing an ontology for AI in human history, crucial for a digital footprint, involves interdisciplinary challenges: diverse data, multiple interpretations, expanding datasets, language barriers, standardization issues, and ethical considerations.

In the quest for an unbiased Digital Footprint of Human History, the emphasis is not on achieving a singular, definitive history but on embracing the multitude of human experiences and perspectives. AI, when harnessed to present multiple viewpoints, becomes a catalyst for a more inclusive and dynamic dialogue about the past.

How do maps created fixed points, and what do those points reveal about history? This article explores how the information provided by maps can be rendered flexible and responsive throughAI-generated models, and so open up new avenues of historical research. 

McKinsey addresses algorithmic bias in AI neatly and structurally but overlooks inherent philosophical paradoxes and complexity dynamics. A multidisciplinary, agile model that incorporates ethical pluralism and continuous adaptation better suits today's AI landscape. Revisiting older frameworks is essential due to shifting societal norms and emerging regulations.

The intriguing confluence of machine learning and history, where trust plays a central role. With its historical significance in both medieval and modern contexts influences our understanding of the past. The article discovers the challenges and far-reaching implications of trusting machine learning as effective arbiters of history.

Incomplete knowledge of history shapes strategic advantage and de facto freedom in a deterministic world. The tension between predestination and free will resolves through the sustaining power of historical ignorance.

What is the transformative potential of generative AI like ChatGPT in historical research? Beyond its writing abilities, generative AI can analyze data, summarize text, and create visual aids like graphs and charts. This technology promises to revolutionize historical research, simplifying data processing and opening new avenues for exploration in the digital era of history.

Discover the mathematical underpinnings behind AI hallucinations and the significance of latent spaces. Despite the ability to handle vast datasets efficiently, generative models sometimes produce "hallucinations," creative but inaccurate outputs.

Artzrouni and Komlos's 1996 spatial model visually represents territorial dynamics in Europe from 500 to 1800 AD using a grid system. The model underscores the influence of a state's border position and suggests coastal countries form more predictably than inland ones. However, it highlights the limitations of solely using geopolitical mechanisms to predict empire dynamics. Turchin believes other factors, like Ibn Khaldun's concept of "asabiyyah" (collective solidarity), play a significant role in empire rise and fall.

Peter Turchin utilizes the Lotka-Volterra (predator-prey) equation, originally designed to model population dynamics between predators and their prey, to understand the complexities of medieval agrarian states. These states, according to Turchin, can be viewed as oscillating systems influenced by variables like territory size and military success. Drawing from Randall Collins' geopolitical theory, Turchin identifies key parameters such as geopolitical resources, logistic loads, and peripheral position. The interplay of these variables results in non-linear relationships between territory size and rate of change, suggesting there's an equilibrium point beyond which territorial expansion becomes inefficient for the state.

The University of Barcelona's team is exploring how combining AI, digital technology, and archaeological methods can provide a deeper understanding of history. Their research introduces concepts like Units of Topography and Actor to enrich archaeological standards. This approach aims to make history more accessible and better understood through modern technology while valuing human interpretation.

Introduced by Peter Turchin in 2003, cliodynamics uses mathematical models to analyze long-term historical trends. Drawing from the concept of “asabiyyah” (social solidarity), Turchin focused on medieval agrarian societies, using differential equations and multi-agent modeling. He identified various growth patterns in state dynamics and emphasized the need for negative feedback in models, highlighting the cyclical nature of historical growth and decline.

In an era fuelled by the might of big data, the question arises: can the blossoming field of event prediction enrich the realm of historical research? Delving into this interdisciplinary area, while recognizing its inherent complexities and potential setbacks, could be a stride towards constructing a higher quality historical timeline.