Friday, January 8, 2027: 9:30 AM
Mardi Gras Ballroom E (New Orleans Marriott)
Databases of ancient evidence routinely focus on collecting specimens within a particular category of sources – such as cuneiform tablets, stone inscriptions, papyri, coins, or other artifacts – in the hope that users will find them useful for their own research. Large databases are rarely designed specifically for the purpose of addressing historical questions and testing hypotheses. One recent exception is Seshat (https://seshat-db.com/), a ‘global history databank’ with a strong emphasis on the premodern period that has gathered more than 50,000 records from 862 societies by coding a range of social, economic, political, technological and ideational variables that capture different forms of complexity. The project’s objective is to accumulate standardized data from around the world to test hypotheses, especially about cross-cultural trends and differences, causal relationships, and drivers of development. It provides a new and concrete foundation for addressing the kinds of big questions that the historical profession has increasingly abandoned. Early payoff has been considerable: recent papers drawing on this material demonstrate that different characteristics of social complexity are functionally related and have co-evolved in predictable ways across space and time, and test competing theories about the drivers of socio-political scaling-up or religious change over the long run. This matters for two reasons: comprehensive datasets and systematic analysis are the only means of assessing rival claims and preventing opportunistic cherry-picking from dominating the debate; and they allow us to gauge the potential and limits of generalization. Historians would do well to engage with this material instead of ceding ground to quantitatively oriented economists and political scientists. This is all the more true as advances in AI suggest that we are only at the very beginning of a new era of massive data collecting and processing (including agent-based simulation) that may enable us to comprehend historical dynamics with unprecedented clarity.
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