In February 2024, stock prices in three continents went to new heights, and what if I tell you it had something to do with linguists and philologists? the people who study languages?
Just about 15 to 18 months ago, Web3, comprising of the much celebrated blockchain and crypto was touted as the future of technology, they were the cynosure of all eyes amidst VCs and enterprises, until Gen AI crashed the party, dethroned web3, and soared Nvidia shares by 521%, added $277bn to market cap. Nvidia is one of the key providers of chips needed for advanced AI processing. But what does linguists have to do with AI chip making company’s soaring stock prices?
From the dawn of civilization, every major leap in language processing—whether it’s printing, transmitting, recording, or retrieving information—has significantly altered our world. In modern history, it starts with Gutenberg’s printing press, who accelerated information dissemination, by 18th century, we deciphered the Rosetta stone written in Egyptian hieroglyphics to understand an entire civilization. By end of the century, we got functional radio and telephone technology by Marconi and Bell respectively, which laid foundation to synchronous communications we take for granted today.
Just imagine, there’s no aviation, telecom, or IT as an industry without these inventions that simply made two people communicate with each other with the help of a machine. Perhaps a pigeon might have to deliver this article in your whale oil lit tenement!In the 19th century, Edison’s phonograph recorded and replayed “Mary Had a Little Lamb,” marking a significant advancement. Similarly, Alan Turing’s decryption of the Enigma during World War II was as much a linguistic feat as it was a mathematical one.
The birth of modern computer science was greatly influenced by linguistics and philology. Noam Chomsky, in the 1950s, created the phrase “Colorless green ideas sleep furiously” to illustrate the difference between syntax and semantics, challenging the then-dominant statistical approaches to grammar. This discussion paved the way for the Cognitive Revolution, integrating psychology, linguistics, computer science, anthropology, neuroscience, and philosophy.
Since them, several notable linguist such as Leonard Bloomfield, Charles Hockett have since agreed, refuted, and appended the legacy approach to understanding Syntactic Structures of languages which collectively led to the spark and growth of Cognitive Revolution which then comprised of psychology, linguistics, computer science, anthropology, neuroscience, and philosophy.
Around the same period, John McCarthy introduced the term “Artificial Intelligence” during the 1956 Dartmouth Conference, which sought to explore “how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.” Fast forward about 65 years, marked by significant milestones such as manned moon missions, the birth of the internet, and robotic rovers on Mars, we witnessed the advent of ChatGPT in November 2022.
The devilish task of getting a computer application like ChatGPT to write an essay about an imaginary island or create an image of a puppy juxtaposed with a teddy bear has taken longer than putting man on moon. The complexity has always rested with making computers understand human languages, context, hidden structures, surface structures and the nuances.
With advancement in NLP (Natural Language Processing) we got an Apple Siri as far back as 2011 and Amazon Alexa in 2014, they were reasonably capable of understanding the intent behind spoken languages and helped us get things done. But they couldn’t imagine, articulate, or reason (albeit simulation) until now.
Beyond ChatGPT, we have used NLP in various forms for the past two decades or so, the voice search on Google, the autocorrect and grammar checks, the predictive text suggestion chips on messengers and mail clients are results of progressive work in the language technologies. From helping us stay productive to ducking our heads due to autocorrect, language technologies have influenced our life and culture in many notable ways.
Notably, language technologies have often favored English, amplifying its dominance. This impact is profound, affecting individual careers and national economies.
In 1973, a 16 year old boy from Kyushu, a small obscure rural town in Japan took a flight to Tokyo to meet his idol, Den Fujita, the president of McDonald’s. He advised him to learn English and computer science; so he moved to California to faithfully follow the instructions from his hero. Over the next 18 months, the rural kid from Japan built a first of its kind electronic translator with some help from his professors and sold it to Sharp Corporation for $1.7mn. This was the founding capital for what would then come to be known as Softbank and a rural kid from Japan is Masayoshi Son.
By 1999, Son would go on to invest $20mn in a self-taught English teacher and translator turned dot com entrepreneur from Hangzhou in China who was learning the ropes of e-commerce business. The $20mn would go on to return a yield of 539,900% by 2018, or about $108bn. The English translator turned entrepreneur is Jack Ma, founder of AliBaba.
Both Ma, and Son, among the most prominent figures of technology based businesses today, have publicly and repeatedly owed their success to learning English. The lingua franca of the business world.
English, comprising 55% of the Web, dominates in the digital realm significantly, dictating who participates in globalization and who remains on the periphery.
Consider the BPO sector, India had a head start as early as the late 80s, but we conceded it to the Philippines by 2010. Industry experts cite the cost of running a call centre is similar in both nations, but according to the English Proficiency Index (EPI), India ranks 60, while the Philippines ranks.
In 2017, I had two distinct opportunities to learn about how proficiency in English or lack thereof plays a role in whether one can be part of globalization or not. First was Kazakhstan (EPI 104), who had organised a hackathon to find solutions to help in higher English literacy adoption among its people so as to enable them to participate in globalization. and second was at Indonesia (EPI 79) where I learnt software engineers have poor prospectus beyond the four local unicorns owing to their poor English skills.
Whether by design or default, English’s ascendancy in technology continues to reshape the world and influence cultures globally, a testament to the enduring impact of language technologies.
An abridged version of this article appeared on the print edition of Mint
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