Archaeologists vs. Computers: A Study Tests Who’s Best at Sifting the Past
When it came to the tedious task of categorizing pottery fragments, a deep-learning model was found to be just as accurate, and far more efficient, as four human experts.
A study focused on the painstaking work of categorizing shards of Tusayan White Ware, a type of painted hand-formed pottery used in northeastern Arizona between 825 and 1300. Credit...Leszek Pawlowicz and Christian Downum/ Northern Arizona University
May 25, 2021, 9:55 a.m. ET
A key piece of an archaeologist’s job involves the tedious process of categorizing shards of pottery into subtypes. Ask archaeologists why they have put a fragment into a particular category and it’s often difficult for them to say what exactly had led them to that conclusion.