Technology

Of bots, bräuhauses and AI: GALA conference 2019

GALA conferences are intense. And the GALA Conference in Munich held from 24 to 27 March 2019 was no different. Whether it be the chock-a-block conference programme, filled with hugely enlightening sessions, networking with like-minded people during breaks, making new friends and laughing with old ones, or staying up until the wee hours contemplating the industry over Reinheitsgebot beer, you always leave with the realisation that you were part of an educational experience like no other. GALA conferences always have one objective in mind ─ creating a space to share ideas, advice and lessons from experts in the field. All to the benefit of the industry as a whole and the attending individuals and companies in particular.

This year’s theme, “The Changing Role of the Human Being in an AI-driven Language Service Industry”, addressed the biggest question in our working lives, namely how can we prepare for the impending onslaught of the machines? To put it bluntly, “How can I make sure that I’ll still have a job tomorrow?”. Although this question has certainly been asked at previous GALA conferences, delegates at this year’s conference had a much greater sense of urgency to have this question answered. And answered in a way that cuts through much of the haziness that we sometimes feel when speaking about AI.

So what are the main things I took away from the Munich conference besides the keynote speaker’s fascinating talk about the hundreds of daily online contracts we enter into without a second thought (all of those lightning Yes-clicks to cookies, terms and conditions, etc.).

  • I quickly realised there is a huge need to better understand what we are talking about when we discuss artificial intelligence, machine translation, machine learning, neural networks and natural language processing. Using these terms interchangeably (as attendees and sometimes even different speakers did) only adds to the confusion and seriously hampers the creation of a strategy for implementation and future-proofing your business.

 

  • It is no longer enough to just talk about implementation in the future, you’ll have to start swimming with the AI, machine and automation current sweeping across the industry. Either that or be swept away along with everyone who still clings to the idea that machines cannot influence the way they do their jobs. As one speaker put it, “How many of those LSPs who didn’t believe in CAT tools, terminology software or electronic quality assurance checkers are really still relevant today?”.

 

  • Video remote interpreting as a service is exploding and will only get bigger as people realise the tremendous impact it can have, both in giving access to interpreters around the world and as aid tools for hard-to-reach communities. AI is also having an impact here, as things like vendor selection and technology to enhance quality in the booth are beginning to play a role.

 

  • AI and automation are revolutionising sales: customer or potential client research, sifting through an overwhelming amount of data and saving time by automation of certain tasks. Having said this, sales departments will have to find a way to use AI and data processing machines to their advantage, without ever losing sight of the end client’s needs. As technology become smarter, preserving the human element becomes harder. But being customer-conscious is often the driving force behind growth so it is non-negotiable.

The 4th Industrial Revolution is here and these are exciting times. With the human aspect featuring equally in discussions on AI, machine learning and neural networks at GALA Munich, there shouldn’t really be any doubt that humans will remain crucial in the shake-ups we are facing in our industry. But, as with any technological change, people have to realise that adaptation is key. Yes, a lot of the current roles, job descriptions and responsibilities will fall away completely as they are replaced with machines. Yet just as many new ones can be created if people and companies are willing to shed their old skins and embrace the endless possibilities of AI, automation and machine translation in the language service industry.

  herman.botha@foliotranslations.com botha   Apr 05, 2019   News, Technology, What's New   0 Comment Read More

Two Rosettas, One Mission

On 12 November 2014 a space module bounced gently in the vastness of space before settling down on a comet millions of kilometres from Earth. Philae had hitched a ride on the European Space Agency’s Rosetta probe to analyse and photograph 67P/Churyumov-Gerasimenko.

On 19 July 1799 Pierre-François Bouchard inspected building rubble near the town of Rosetta in Egypt, thousands of kilometres from France, when he discovered a black stone covered in three ancient scripts. As an army engineer Bouchard had hitched a ride on Napoleon’s war machine and unwittingly stumbled upon the key to deciphering a 3 500-year-old language.

Now there may be a slight difference in the technologies involved, but both rocks helped us to piece together a fundamental portion of our past. 67P/Churyumov-Gerasimenko improved our understanding of planet formation and without the Rosetta Stone, Egyptologists may still have been searching the heavens for the architects of the pyramids.

Mission firsts

Rosetta spacecraft:

  • The first European spacecraft to brush past the primordial objects in the asteroid belt.
  • The first spacecraft to fly next to and orbit a comet headed towards the sun.
  • Rosetta’s Philae lander performed the first controlled touchdown on a comet.
  • The first probe to examine a frozen comet as it is thawed by the sun.

Rosetta Stone:

  • The first trilingual stela discovered by a colonial power in the Middle East.
  • The first time demotic and hieroglyphic text was translated into French.
  • Provided the first direct glimpse of Ancient Egyptian officialdom.
  • The first time Middle Eastern war booty changed hands between the French and English.

Left: Pierre-Francois Bouchard; Right: Johann Dietrich Wörner (Director General of the European Space Agency)

Facts written in stone

67P/Churyumov-Gerasimenko:

  • An analysis of the composition of water vapour on 67P/Churyumov-Gerasimenko disproved the hypothesis that comets of this nature bequeathed mother earth the gift of water ─ the ratio of deuterium to hydrogen in the water from the comet is three times that found in terrestrial water.
  • The absence of a magnetic field around the comet suggests that magnetism did not play a role in the formation of planetary building blocks ─ at least not once they reached a certain size.
  • Solar radiation, not photons from the sun, is responsible for the electrons within a 1 km radius of the comet.

Rosetta Stone:

  • The presence of Greek on the stela confirms the fact that Egypt was under the Ptolemaic yoke in that time.
  • The stone proclaims that “[Ptolemy V] possessed a divine heart which was beneficent towards the gods; and he hath given gold in large quantities, and grain in large quantities to the temples.” From this we can deduce that even the foreign rulers of Egypt, such as Ptolemy, derived their legitimacy from the local gods, more specifically the priests.
  • The demotic script separating the Greek and hieroglyphics contains ideographs that represent ideas or concepts independent of any particular language. “Demotic” denotes a kind of language used by ordinary people.

Even though the tablets that linguists and language lovers consult these days are not made from granite, the information they contain would not have been available without the contributions of amateur archaeologists and linguistic savants such as Piere-François Bouchard and Jean-François Champollion*, or the engineering feats of the Johann-Dietrich Wörners whose futuristic inventions illuminate our past.

*One of the founding figures in the field of Egyptology credited with deciphering hieroglyphics.

  herman.botha@foliotranslations.com botha   Feb 14, 2019   History, Technology   0 Comment Read More

Arms, Algorithms, and Qualifying Clauses

“A well regulated Militia, being necessary to the security of a free State, the right of the people to keep and bear Arms, shall not be infringed.”

To say this sentence has found itself under the same powerful microscope as some foundational sentences in the Bible ─ “Thou shalt not kill” being the first that springs to mind ─ would not be an example of hyperbole.

Crossfire and Contention

Gun-control activists insist the first clause (“A well regulated Militia”) acts as a qualifier for the second (“the right of the people to keep and bear Arms”). For them the link between the two is obvious ─ the founding fathers wanted to guarantee the freedom of citizens against tyrannical governments by giving the people the right to form a militia, and you cannot form a militia without “the right to keep and bear Arms”. For gun-rights activists, however, the opposite is true: “the right of the people to keep and bear Arms” just happens to find itself in this particular Amendment and is not fundamentally connected to the right to form a militia.

Now while it is true that forming a militia without the right to keep and bear arms would be difficult, taking on drones, nukes and tanks with any sort of militia would be impossible. The advent of these modern weapons in the arsenal of the US military should have destroyed any sentiments about a militia, and along with it “the right of the people to keep and bear Arms”. Or so the gun-control argument goes. But the point of this blog is to describe how algorithms have found their way into the court and why they belong in the toolboxes of translators too, so let’s get to that.

All rise

The last time US jurisprudence got serious about the gun issue was in 2008, when, during the course of DC v. Heller, the link between the “Militia” and “the right to keep and bear Arms” came under scrutiny in the Supreme Court. Oral and written arguments were tossed back and forth, and when the dust settled the link had been weighed and found too light. The late judge Antonin Scalia, who wrote the majority opinion, consulted Samuel Johnson’s dictionary from the 18th century, as well as period prose, to defend the conclusion that “to bear Arms” in the time of Jefferson did not imply a militia.

Algorithm Appeal

Now it’s all good and well to consult prose and dictionaries from a certain epoch, but it is simply beyond the powers of any judge (or panel of judges) to process the entire corpus of text generated in any given epoch. At least not if they plan to reach a verdict before the end of their own epoch (or “prehumously” for that matter). In practical terms they’re always going to end up with selective quotations, and selective quotations employed to prove a point is called cherry picking. Algorithms provide a much more powerful way to search for patterns of word use. Dennis Baron, a linguist at the University of Illinois Urbana-Champaign searched “bear Arms” in the Corpus of Founding Era American English (139 million words from 1760 to 1799) and the Corpus of Early Modern English (1.3 billion words from 1475 to 1800). “To bear Arms” appeared 1 500 times and only in a few cases not in the context of organised armed action.

Set the dials to 1787

In DC v. Heller Scalia’s attempt to “travel” to the 18th century to verify the context of “to bear Arms” failed because he didn’t employ the latest technology, a grave mistake for any time traveller. As translators we should heed the implications of Baron’s research. Any translator worth her salt relies on context to determine the meaning of words and phrases before attempting a translation. In the past translation choices could be defended with the help of dictionaries, prose, acquired knowledge of a culture, and substantiated with well-chosen quotes only. As Google expands its corpora, the time is near when any translation choice not backed up by the superior search skills of algorithms will always be open to the charge of cherry picking, especially where historico-cultural distances between the source and the target are involved. One small consolation is that the mistranslation buck will then stop somewhere between the (wo)man and the machine.

  • This blog is based on an article that was published in The Economist (June 9th -15th 2018).
  herman.botha@foliotranslations.com botha   Aug 03, 2018   Technology   0 Comment Read More