The AI Historian – Teaching Machines to Understand the Past
Supervisor
Suitable for
Abstract
Background Reading:
https://www.engineegroup.com/tcsit/article/view/TCSIT-7-148
https://openreview.net/pdf?id=EO8mTLqDuT
https://openreview.net/pdf?id=EDWTHMVOCj
https://www.amazon.co.uk/Causality-Judea-Pearl/dp/052189560X
How can we build an artificial intelligence that thinks like a historian?
This project will develop AI systems that
can interpret historical evidence — texts, maps, artefacts, and data — to test causal explanations for how societies
evolve, collapse, and endure. Students will work at the intersection of machine learning, causal inference, simulation,
and digital history, developing methods that let AI reason about events, uncertainty, and human behaviour across time.
Collaborations with anthropologists and historians at Oxford (including the Seshat and CSSC teams) offer unique access to
structured historical datasets. Ideal applicants have strong technical skills in AI/ML or simulation and curiosity about applying
them to the grand questions of human history.