AI and the Resurrection of Lost Languages: The Future of Historical Decipherment

AI in Deciphering Ancient Languages: A New Frontier

The challenge of deciphering lost languages lies in the scarcity of data and the absence of modern linguistic relatives. Historically, this process relied on human intuition, historical records, and comparative linguistics, where known languages were used as a reference. However, many languages, such as the Iberian language or ancient Linear B, were only partially deciphered after decades of laborious analysis. AI is fundamentally altering this dynamic by offering new methods to analyze linguistic data faster and more efficiently.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have pioneered a system that uses AI to automatically decipher lost languages without prior knowledge of their relation to known languages. This system, led by Professor Regina Barzilay, builds on the principles of historical linguistics. It analyzes the phonetic shifts languages undergo over time and incorporates predictable linguistic patterns, like how sounds evolve. For example, a sound like "p" in a parent language might evolve into "b" in a descendant language, but unlikely into a "k".

One of the key breakthroughs of Barzilay’s system is its ability to work with very limited data sometimes only a few thousand words and its capacity to infer relationships between entirely unknown languages. Using these methods, the system has even shed light on controversial linguistic questions, such as whether the Iberian language is related to Basque, suggesting that they are not as closely connected as previously believed.

Techniques Behind the AI Decoding Process

The AI system utilizes several innovative techniques that distinguish it from traditional methods. One critical component is the use of "cognate-based decipherment." This approach tries to identify cognates words in different languages that have a common etymological origin. The system projects linguistic features into a multi-dimensional space, where the distance between words in different languages reflects their phonetic and semantic similarities. This allows the AI to map ancient words to modern counterparts or related languages, even if the script is unfamiliar.

Another critical technique involves "entity recognition," a method often used in natural language processing (NLP) for modern languages. This approach allows the AI to identify proper nouns, such as names of people or places, even when their meanings are not immediately apparent. By cross-referencing these terms with historical records, researchers can better understand the context of ancient texts.

One of the most remarkable successes of these methods was demonstrated in deciphering Ugaritic, an ancient Semitic language, and Linear B, which was used by Mycenaean Greeks. While Linear B took decades for human scholars to decipher, AI systems have managed to replicate this process in much less time, offering hope for other undeciphered scripts.

From Decoding to Understanding

The implications of AI-driven decipherment are profound. Beyond just reading ancient texts, AI can offer insights into the cultural, historical, and social contexts of ancient civilizations. For example, understanding the linguistic structure can reveal much about a culture’s trade, governance, or religion.

In the future, researchers hope to expand AI's capability beyond cognate-based models. For languages that have no known relatives, AI could start recognizing broader semantic patterns, such as identifying recurring themes or categories in ancient texts. This would allow the system to infer meanings of unknown words based on contextual clues rather than direct translation.

AI as the Key to Forgotten Histories

The application of AI to decipher lost languages not only accelerates the discovery process but also opens new frontiers in understanding human history. By leveraging sophisticated algorithms and linguistic patterns, AI is bridging the gap between ancient civilizations and modern scholarship. As this technology continues to evolve, we may one day be able to fully decode the languages and cultures of societies long lost to time, providing invaluable insights into the origins of human civilization.

In the end, AI is not just a tool for the future it's becoming a powerful lens through which we can reexamine and reconnect with the past.