Opinion

How Sanskrit came to be considered the most suitable language for computer software

Misreading of a 1995 paper in 'AI Magazine' and the sheer power of assertion repeated so often that it's never questioned seem to be responsible.

About Sanskrit in contemporary India, there are two things of note.

The first is typified by what I found in the Hindustan Timesa few days ago. When a mobile app firm observed August 15 by asking people to tweet with the hashtag #IndianAndProud, many Indians responded. A selection of their 140-or-less character epigrams covered three full pages in the paper on August 19. One repeated an assertion that’s been made so often it’s no longer even questioned: that “Sanskrit is considered the most suitable language for computer software”.

The way I’ve often seen it, that statement is usually prefixed by the words “A report in Forbes magazine in 1987 said that…”. Perhaps in this case the Twitter character limit forced their omission. But this attribution to Forbes has been made so often, it is no longer even questioned. Though if it was, we’d find that no such report was ever in Forbes, whether in 1987 or any other time.

So why do so many people appear to believe it? Or what does it even mean? Or where did this shibboleth come from in the first place?

Natural language for computers

To answer that, you have to go back about 30 years, to 1985. That’s when, in a previous life, I was writing software for a living, particularly in a field that the industry was actively trying to profit from at the time, Artificial Intelligence. That year, a researcher named Rick Briggs at National Aeronautics and Space Administration, or NASA, made waves by publishing a paper in AI Magazine, titled “Knowledge Representation in Sanskrit and Artificial Intelligence.” (Abstract and full text available here.)

This is the paper that would launch a thousand claims about Sanskrit and software.

Now a major AI goal at the time was to get computers to understand “natural language” – meaning not Lisp or C or Prolog, which they all did quite well, but languages we humans speak. Like English, or Hindi, or Tagalog – or, for that matter, Sanskrit. That you can today ask Google a perfectly grammatical English question (try “What is the temperature on Tristan da Cunha?”) and actually get meaningful results owes something to those early research efforts. And Briggs alerted AI folks to something fascinating and useful: that the grammar of Sanskrit – structured and rule-based as it was – had significant lessons for this business of natural language understanding. Studying the way ancient Indian grammarians worked, Briggs suggested, might help AI researchers “finally solve the natural language understanding [problem]”.

All of which is fascinating enough. But while his abstract does say that “a natural language can serve as an artificial language also”, nowhere in the paper did Briggs claim that Sanskrit is “the most suitable language for computer software”. That second is an essentially meaningless statement.

For one thing, different kinds of software are suited to different computer languages. Much of AI research has happened in Lisp, for example, because of its ability to manipulate words and sentences – but Lisp is nearly unheard of outside AI. So there is no such thing as the “most suitable language” for software. But for another thing, if it was indeed so spot-on suitable, we’d have seen software written in Sanskrit by now. That we haven’t is a pointer to the truth: certainly the rigorous rules of Sanskrit grammar have lessons for AI, but writing software is another challenge altogether. The way computers are built requires a certain clear and unmistakable logic in how we give instructions to them. Nobody has yet found a way to do that in any natural language, whether Sanskrit or English or Tagalog.

Elective, not mandatory

Which brings us to the other thing about Sanskrit in contemporary India: Himachal Pradesh has just announced that “Sanskrit will be made a mandatory subject in all government schools” in the state.

Why would a state force its students – or at least, the students in government schools – to learn Sanskrit? This is not to suggest that no students must learn it, not at all. After all, plenty of the collective wisdom of this country, gathered over many centuries, is recorded in Sanskrit and is, we believe, stored somewhere safe. I would have liked to learn enough Sanskrit – and maybe will someday – to read and understand even the line Rick Briggs deconstructs in his paper: “Maitrah: sauhardyat Devadattaya odanam ghate agnina pacati.” (He did kindly translate: “Out of friendship, Maitra cooks rice for Devadatta in a pot over a fire.”) And of course some of us – AI researchers, in particular – would do well to learn enough of the language’s grammar to use it as Briggs suggests.

The word, of course, is “some”. Some of us will learn the intricacies of quantum mechanics, so as to tackle the endless mysteries of our universe. Some of us will learn the ins and outs of economics, so as to understand the dynamics of trade and markets. But not all of us. Because we don’t need that knowledge to live our lives. Which is why those subjects are not taught to every school-going kid.

In the same way as it would make no sense to make quantum mechanics and economics mandatory, it makes no sense to make Sanskrit mandatory in schools. Make it available as an elective for those who want to study it; leave the rest to focus on their other subjects.

Because for all its precise grammar and its centuries of history, this is the truth about Sanskrit: few people today speak it – just over 14,000 according to the 2001 Census, in fact. And certainly computers don’t speak it.

We welcome your comments at letters@scroll.in.
Sponsored Content BY 

Behind the garb of wealth and success, white collar criminals are hiding in plain sight

Understanding the forces that motivate leaders to become fraudsters.

Most con artists are very easy to like; the ones that belong to the corporate society, even more so. The Jordan Belforts of the world are confident, sharp and can smooth-talk their way into convincing people to bend at their will. For years, Harshad Mehta, a practiced con-artist, employed all-of-the-above to earn the sobriquet “big bull” on Dalaal Street. In 1992, the stockbroker used the pump and dump technique, explained later, to falsely inflate the Sensex from 1,194 points to 4,467. It was only after the scam that journalist Sucheta Dalal, acting on a tip-off, broke the story exposing how he fraudulently dipped into the banking system to finance a boom that manipulated the stock market.

Play

In her book ‘The confidence game’, Maria Konnikova observes that con artists are expert storytellers - “When a story is plausible, we often assume it’s true.” Harshad Mehta’s story was an endearing rags-to-riches tale in which an insurance agent turned stockbroker flourished based on his skill and knowledge of the market. For years, he gave hope to marketmen that they too could one day live in a 15,000 sq.ft. posh apartment with a swimming pool in upmarket Worli.

One such marketman was Ketan Parekh who took over Dalaal Street after the arrest of Harshad Mehta. Ketan Parekh kept a low profile and broke character only to celebrate milestones such as reaching Rs. 100 crore in net worth, for which he threw a lavish bash with a star-studded guest-list to show off his wealth and connections. Ketan Parekh, a trainee in Harshad Mehta’s company, used the same infamous pump-and-dump scheme to make his riches. In that, he first used false bank documents to buy high stakes in shares that would inflate the stock prices of certain companies. The rise in stock prices lured in other institutional investors, further increasing the price of the stock. Once the price was high, Ketan dumped these stocks making huge profits and causing the stock market to take a tumble since it was propped up on misleading share prices. Ketan Parekh was later implicated in the 2001 securities scam and is serving a 14-years SEBI ban. The tactics employed by Harshad Mehta and Ketan Parekh were similar, in that they found a loophole in the system and took advantage of it to accumulate an obscene amount of wealth.

Play

Call it greed, addiction or smarts, the 1992 and 2001 Securities Scams, for the first time, revealed the magnitude of white collar crimes in India. To fill the gaps exposed through these scams, the Securities Laws Act 1995 widened SEBI’s jurisdiction and allowed it to regulate depositories, FIIs, venture capital funds and credit-rating agencies. SEBI further received greater autonomy to penalise capital market violations with a fine of Rs 10 lakhs.

Despite an empowered regulatory body, the next white-collar crime struck India’s capital market with a massive blow. In a confession letter, Ramalinga Raju, ex-chairman of Satyam Computers convicted of criminal conspiracy and financial fraud, disclosed that Satyam’s balance sheets were cooked up to show an excess of revenues amounting to Rs. 7,000 crore. This accounting fraud allowed the chairman to keep the share prices of the company high. The deception, once revealed to unsuspecting board members and shareholders, made the company’s stock prices crash, with the investors losing as much as Rs. 14,000 crores. The crash of India’s fourth largest software services company is often likened to the bankruptcy of Enron - both companies achieved dizzying heights but collapsed to the ground taking their shareholders with them. Ramalinga Raju wrote in his letter “it was like riding a tiger, not knowing how to get off without being eaten”, implying that even after the realisation of consequences of the crime, it was impossible for him to rectify it.

It is theorised that white-collar crimes like these are highly rationalised. The motivation for the crime can be linked to the strain theory developed by Robert K Merton who stated that society puts pressure on individuals to achieve socially accepted goals (the importance of money, social status etc.). Not having the means to achieve those goals leads individuals to commit crimes.

Take the case of the executive who spent nine years in McKinsey as managing director and thereafter on the corporate and non-profit boards of Goldman Sachs, Procter & Gamble, American Airlines, and Harvard Business School. Rajat Gupta was a figure of success. Furthermore, his commitment to philanthropy added an additional layer of credibility to his image. He created the American India Foundation which brought in millions of dollars in philanthropic contributions from NRIs to development programs across the country. Rajat Gupta’s descent started during the investigation on Raj Rajaratnam, a Sri-Lankan hedge fund manager accused of insider trading. Convicted for leaking confidential information about Warren Buffet’s sizeable investment plans for Goldman Sachs to Raj Rajaratnam, Rajat Gupta was found guilty of conspiracy and three counts of securities fraud. Safe to say, Mr. Gupta’s philanthropic work did not sway the jury.

Play

The people discussed above have one thing in common - each one of them was well respected and celebrated for their industry prowess and social standing, but got sucked down a path of non-violent crime. The question remains - Why are individuals at successful positions willing to risk it all? The book Why They Do It: Inside the mind of the White-Collar Criminal based on a research by Eugene Soltes reveals a startling insight. Soltes spoke to fifty white collar criminals to understand their motivations behind the crimes. Like most of us, Soltes expected the workings of a calculated and greedy mind behind the crimes, something that could separate them from regular people. However, the results were surprisingly unnerving. According to the research, most of the executives who committed crimes made decisions the way we all do–on the basis of their intuitions and gut feelings. They often didn’t realise the consequences of their action and got caught in the flow of making more money.

Play

The arena of white collar crimes is full of commanding players with large and complex personalities. Billions, starring Damien Lewis and Paul Giamatti, captures the undercurrents of Wall Street and delivers a high-octane ‘ruthless attorney vs wealthy kingpin’ drama. The show looks at the fine line between success and fraud in the stock market. Bobby Axelrod, the hedge fund kingpin, skilfully walks on this fine line like a tightrope walker, making it difficult for Chuck Rhoades, a US attorney, to build a case against him.

If financial drama is your thing, then block your weekend for Billions. You can catch it on Hotstar Premium, a platform that offers a wide collection of popular and Emmy-winning shows such as Game of Thrones, Modern Family and This Is Us, in addition to live sports coverage, and movies. To subscribe, click here.

This article was produced by the Scroll marketing team on behalf of Hotstar and not by the Scroll editorial team.