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The Double-Edged Sword of AI and Big Data in Historical Interpreting Interpretability Context: Tensions and Opportunities

https://doi.org/10.2139/ssrn.4733550
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Outgoing claims: the papers this work cites, builds on, or argues with.

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inferredcites →https://doi.org/10.1007/s11042-022-13428-4openalex-extracted
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inferredcites →https://doi.org/10.1007/s13347-020-00416-5openalex-extracted
Artificial Interdisciplinarity: Artificial Intelligence for Research on Complex Societal Problems
inferredcites →https://doi.org/10.1007/s42979-021-00592-xopenalex-extracted
Machine Learning: Algorithms, Real-World Applications and Research Directions
inferredcites →https://doi.org/10.1016/j.bushor.2018.03.007openalex-extracted
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Taking Temporality Seriously: Modeling History and the Use of Narratives as Evidence
inferredcites →https://doi.org/10.1017/s1049096514001784openalex-extracted
We Are All Social Scientists Now: How Big Data, Machine Learning, and Causal Inference Work Together
inferredcites →https://doi.org/10.1023/a:1006879920010openalex-extracted
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inferredcites →https://doi.org/10.1023/a:1010933404324openalex-extracted
Random Forests
inferredcites →https://doi.org/10.1086/209325openalex-extracted
Historical Method in Consumer Research: Developing Causal Explanations of Change
inferredcites →https://doi.org/10.1086/ahr/94.3.627openalex-extracted
Recounting the Past: "Description," Explanation, and Narrative in Historiography
inferredcites →https://doi.org/10.1093/acprof:oso/9780198719571.001.0001openalex-extracted
Methodological Practices in Social Movement Research
inferredcites →https://doi.org/10.1109/access.2017.2696365openalex-extracted
Machine Learning With Big Data: Challenges and Approaches
inferredcites →https://doi.org/10.1109/access.2022.3209825openalex-extracted
A Review on Machine Learning Styles in Computer Vision—Techniques and Future Directions
inferredcites →https://doi.org/10.1145/3313831.3376219openalex-extracted
Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning
inferredcites →https://doi.org/10.1146/annurev-economics-080217-053433openalex-extracted
Machine Learning Methods That Economists Should Know About
inferredcites →https://doi.org/10.1146/annurev-polisci-053119-015921openalex-extracted
Machine Learning for Social Science: An Agnostic Approach
inferredcites →https://doi.org/10.1184/r1/6491222.v1openalex-extracted
Computability and analysis: the legacy of Alan Turing
inferredcites →https://doi.org/10.1186/s40537-014-0007-7openalex-extracted
Deep learning applications and challenges in big data analytics
inferredcites →https://doi.org/10.1214/ss/1009213726openalex-extracted
Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
inferredcites →https://doi.org/10.1353/book4993openalex-extracted
Humanities, Culture, and Interdisciplinarity: The Changing American Academy
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DARPA's Explainable Artificial Intelligence Program
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Artificial Intelligence, Autonomy, and Human‐Machine Teams: Interdependence, Context, and Explainable AI: Editorial Introduction to the Special Articles on Context
inferredcites →https://doi.org/10.17705/1jais.00373openalex-extracted
The Historical Research Method and Information Systems Research
inferredcites →https://doi.org/10.21275/art20203995openalex-extracted
Machine Learning Algorithms - A Review
inferredcites →https://doi.org/10.2307/2082612openalex-extracted
History, Historiography, and Political Science: Multiple Historical Records and the Problem of Selection Bias
inferredcites →https://doi.org/10.2307/2945484openalex-extracted
Beyond the Great Story: History as Text and Discourse.
inferredcites →https://doi.org/10.2307/4144236openalex-extracted
:From Reliable Sources: An Introduction to Historical Methods
inferredcites →https://doi.org/10.26458/jedep.v7i1.571openalex-extracted
QUALITATIVE RESEARCH METHODOLOGY IN SOCIAL SCIENCES AND RELATED SUBJECTS
inferredcites →https://doi.org/10.3138/9781442682610openalex-extracted
Theorizing Historical Consciousness
inferredcites →https://doi.org/10.48550/arxiv.1907.07892openalex-extracted
Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence
inferredcites →https://doi.org/10.48550/arxiv.2109.13916openalex-extracted
Unsolved Problems in ML Safety
inferredcites →https://doi.org/10.48550/arxiv.2307.15043openalex-extracted
Code of "Sirens' Whisper: Inaudible Near-Ultrasonic Jailbreaks of Speech-Driven LLMs"
inferredcites →https://doi.org/10.54254/2755-2721/4/20230355openalex-extracted
Machine learning algorithms review
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.