Academia

From an academic perspective, we believe that History should be a computational discipline. We pursue two vectors:

Education.  We advocate that all undergraduate majors should include a perspective of computation, data, and artificial intelligence. Curricula should incorporate classes that view their discipline from this lens.  A computational view is an alternative perspective that provides valuable insight different that traditional approaches to history.  Further, computational skills (including data science and artificial intelligence) are useful tools in the "real world." Teaching computational techniques readies those in the liberal arts with valuable skills that they will use in their professional careers once they graduate.

At the University of Washington, there exists data science option and minors to support this. We've advocated for these inclusions specifically in the American Ethnic Studies department but for all majors in the liberal arts.

Research. History as an academic discpline has followed a well define process over the years. In simple terms, this process involves these steps:

1. Identify a topic or research question

2. Conduct background research on the topic or question

3. Refine or narrow research topic or question based on background research

4. Identify primary and secondary sources

5. Evaluate the sources for relevancy, authenticity, and accuracy. 

6. Analyze sources and form an argument based on information gathered 

This approach is antiquated and does not address and the capabilities and possibilities of using compuation, data, and artificial intelligence. The Institute of Computational History explores how such capabilities can be used to change, evolve, and enhance the process of historical research.

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