Digital tools unlock ancient texts

Zheng said that in passages involving multiple speakers or indirect quotations — including works such as Sima Qian's Shiji (Records of the Grand Historian) and Mengzi (The Works of Mencius) — quotation marks may sometimes be misplaced or omitted, making it difficult for AI systems to accurately distinguish different voices in the text.

OCR systems also face challenges when handling small print, blurred pages and overlapping handwritten notes, making human review essential.

That is why Zheng believes that the future of ancient-text preservation will require more interdisciplinary talent capable of bridging the humanities and technology.

"Ancient text organization involves processing massive amounts of data. Researchers need not only expertise in literature and history, but also the technical skills to manage information efficiently," he said.

Rediscovering lost voices

For Zheng, the value of digital archives is not limited to academic research. They can also help modern readers rediscover local history and cultural memory.

He has recently been studying historical documents on Wuhan's local life and dialects from two centuries ago, as well as photographic records of the city's devastating 1931 flood. Reading those materials, he said, gave him a more direct sense of how ordinary people in the city once lived, communicated and experienced their daily lives.

"I felt an immediate sense of familiarity and emotional connection across time," Zheng said.

Xu has experienced a similar change in perspective. What began as a personal interest in classical texts gradually became a responsibility to help these works reach a wider audience.

For him, making ancient texts readable is just as important as preserving their original images.

"If ancient texts are not carefully organized and preserved, future generations may still see them, but they may no longer be able to truly understand them or draw spiritual nourishment from them," Xu said.

That is why, for volunteers like Xu and Zheng, ancient-text digitization is more than a technological endeavor. AI can scan, recognize and sort texts at a scale far beyond human capability. But the final task — deciding what a damaged character means, where one voice ends and another begins, and why an old text still matters — remains a human one.