PCI Archaeology

307

Title *

Archaeology, Typology and Machine Epistemologyuse asterix (*) to get italics

Authors *

Gavin LucasPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

Year *

2023

Picture *

Abstract *

<p>In this paper, I will explore some of the implications of machine learning for archaeological method and theory. Against a back-drop of the rise of Big Data and the Third Science Revolution, what lessons can be drawn from the use of new digital technologies and computational approaches as they are applied to archaeological typologies? In this paper, I explore two key aspects of these approaches - automation and epistemic novelty – and attempt to unravel their implications for archaeological practice. Furthermore, the paper will situate these topics within developments of the philosophy of science and technology and suggest an alternative way to think about machine learning that draws on re-thinking what we mean by machines and automation. </p>

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Keywords (optional)

None

Methods that require specific expertise (optional)

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Thematic fields *

Computational archaeology, Theoretical archaeology

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e.g. John Doe john@doe.com

No need for them to be recommenders of PCIArchaeology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct

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Submission date

2022-10-31 15:25:38

Recommender

Shumon Tobias Hussain

Reviewers

Anonymous, Rachel Crellin

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