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Kevin McSpadden

A recent study from mainland China has highlighted the types of archaeological insights that are expected to become increasingly common as artificial intelligence (AI) technology is employed more widely.
The team, from Xi’an Jiaotong-Liverpool University in Suzhou and Renmin University in Beijing, conducted an in-depth analysis of one of the earliest forms of writing – oracle bones –to determine whether the 3,000-year-old authors were left-handed or right-handed.
In a preprint that has not yet undergone peer review, the team utilised digital copies of oracle bones and employed an unsupervised deep-learning tool called Bone2Vec to analyse the inscriptions.
Their goal was to gain further insight into whether humans were biologically predisposed to being right-handed, or if that phenomenon arose from the development of societies.
Wang Hefei, a study author and associate dean at the International Business School Suzhou (IBSS), told the Post that the research “indeed suggests that handedness might be rooted in biology”.
The paper added that, given the prevalence of right-handedness among most primates, the fact that most people are right-handed was likely the result of human nature, and not millennia-long nurture.
“From this assertion, we hope people appreciate the depth and intricacy of human evolution and how our biological traits have been shaped over time,” said Wang. “It’s fascinating to consider that something as seemingly simple as the hand preference reflected in ancient writings could offer insights into the neurological and genetic fibres that weave our history.”
Beyond the research results, the study is intriguing because of its ability to reach back 3,000 years and identify patterns that would be extremely difficult to pinpoint manually, especially on the scale of the over 1,000 characters needed to make broad determinations.

It points to the value AI-driven pattern recognition can bring to archaeology and other similar historical analyses.
“The ability of AI, especially unsupervised learning models like Bone2Vec, to systematically analyse vast datasets and reveal patterns that might not be visible to the human eye opens new avenues for discovery and analysis,” said Wang.
To determine that most ancient scribes were right-handed, the researchers built a data set of over 1,000 images of oracle-bone inscriptions that the Oracle Museum of China had manually scanned. This archive is now the largest data set of its kind, which aids in the long-term preservation of historical information.
Bone2Vec extracted the horizontal and vertical features of the characters and applied a model that the researchers said could also be applied to handwriting identification and art authentication. The algorithm could then cluster the characters into discernable patterns that indicated handedness.
The team used artificial data to teach the model the difference between right-handed and left-handed writers. The algorithm could then identify the dominant hand when it was applied to real oracle bone characters.
“A significant portion of our effort was devoted to preparing the dataset – collecting, scanning, and processing the oracle bone images. This highlighted the critical importance of high-quality, well-documented data in AI-driven research,” said Wang.
“Moving forward, establishing more systematic methods for data collection and preparation in archaeology will be essential to leverage AI effectively.”
Elic M. Weitzel, a Peter Buck postdoctoral research fellow at the Smithsonian National Museum of Natural History, who was not involved with the study, agreed and said that teaching algorithms properly will be crucial for AI-driven work.
“I expect that most arguments over whether archaeologists using AI are drawing correct interpretations will hinge largely on the training data employed,” he told the Post.
Weitzel cautioned that the technology is susceptible to implicit biases that may find their way into AI algorithms, or, as the adage goes, “garbage in, garbage out”.
But AI is already providing archaeologists with “new and useful tools” said Weitzel.
“Most archaeologists using AI today are attempting to identify and classify two sets of data: artefacts and archaeological sites. In the near future, these uses of AI will certainly expand into any area of archaeology where pattern recognition is needed.”

As an example of recent AI-driven breakthroughs, Weitzel shared how an archaeologist named Dylan Davis published a paper in June 2024 in which he outlined how machine learning analysis of Rapa Nui – Easter Island – suggested that its peak population was far lower than initially believed. His findings challenged the mainstream understanding that Easter Island experienced a population collapse.
Beyond the technology or the discoveries it could create, the research project from China showcased that AI in academic research necessitates evermore interdisciplinary collaboration.
Wang is not an archaeologist. Her day job is spent at the Liverpool University business school in Suzhou. But, she has a strong background in computer science, so she had the skillset required to help build an algorithmic model and could partner with colleagues to investigate the oracle bones.
“It underscores how modern academic research is increasingly crossing disciplinary boundaries, integrating diverse fields to explore and solve complex questions with new technologies,” she said.
Wang added that, by flattening academic silos, researchers will be in a better position to use modern tools to enhance our knowledge of the past.


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Recent study into ancient Chinese oracle bones highlights how AI is changing archaeology

Researchers use AI to determine if left or right-handed people wrote ancient oracle bones. Photo: SCMP composite/Shutterstock/Wikipedia

The research team analysed oracle bones to determine if their 3,000-year-old authors were left-handed or right-handed. Photo: Wikipedia 

Going forward, it will be crucial to establish more systematic methods for data collection and preparation in archaeology to effectively leverage AI. Photo: Wikipedia 

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People & Culture

Pattern recognition algorithm could determine if a 3,000-year-old oracle bone was written by someone left-handed or right-handed


Pattern recognition algorithm could determine if a 3,000-year-old oracle bone was written by someone left-handed or right-handed.


Archaeology and palaeontology

Artificial intelligence (AI)

Recent study into ancient Chinese oracle bones highlights how AI is changing archaeology

.css-1c6uqr6{color:inherit;font-weight:inherit;font-size:inherit;font-family:inherit;line-height:inherit;overflow-wrap:break-word;}Pattern recognition algorithm could determine if a 3,000-year-old oracle bone was written by someone left-handed or right-handed

Pattern recognition algorithm could determine if a 3,000-year-old oracle bone was written by someone left-handed or right-handed