Perspectives in translator training: knowledge-driven or tech-driven?

Perspectives in translator training: knowledge-driven
or tech-driven?

or tech-driven?
Translator training to meet the expectations of a multi-faceted
changing industry
Abstract
A widespread agreement exists within the translation industry that translators must specialize, as language service providers are
increasingly focusing on specific subject areas to meet the customers’ demand. However, the rapid growth of information and
knowledge, translation technology, and terminology resources are re-shaping the nature and meaning of specialization.
There are many new subjects to know and there is much more to know about each of them since categories are extremely broad in
themselves. No translator can be expected to have the knowledge required to translate all types of documents well and within a
reasonable amount of time.
In translation, there is no common core of education, or common standard of knowledge, or achievement, and the so-called
specialist translator might not even have the basic language skills and knowledge of the ‘generalist.’
As knowledge expands in all areas, translators can simply no longer be expected to master the large body of concepts found in most
subjects and the related terminology in two or more languages.
According to his biographer James Boswell, Samuel Johnson said that knowledge is of two kinds. We know a subject ourselves, or we
know where we can find information upon it.
Up to forty years ago, skills came from knowledge; since a decade or two, abilities have been dominating knowledge. Today, not
only is expert knowledge in a given subject very important, technological skills are becoming increasingly relevant to be capable of
accessing the appropriate resources.
Translation competence is now a combination of data, tools, and knowledge: it is less and less a question of language knowledge
and more one of knowing how to use it and the right tools to exploit it.
This shift in the way in which translators operate leads to the need for new directions for translator training.

Wording
Any skill, no matter how difficult to acquire, can become obsolete when the machines improve.
Jaron Lanier
The demand for translation has never been as high as it is now, and it is expected to continue to soar in spite of the anemic global
economy. Companies of all sizes and from all industries all over the world are being advised to find more international customers as
fast as they can, and to increase their exports even faster as the economy becomes increasingly globalized and companies sell
products and services in multiple markets.
In spite of unemployment, employers lament the shortage of qualified people. Employers in the language service industry have
always been complaining that the level of expertise of graduates (and even professionals) is far from that required.
Nevertheless, there is plenty of people offering their services in the industry, and this seems to be a major issue, leading many
people to ask for fences, barriers, and regulations. So why are really good people so hard to find?
A few years ago, when I entered the academic region of this industry with a no-profit group of professionals to help universities
forge the specialized skills that meet the industry’s demand for professional resources, Inger Larsen of Larsen Globalization, a major
staffing services company for our industry, gave us an article that I still consider valid in its entirety, titled Why we still need more
good translators.

© 2011 Luigi Muzii - All rights reserved 1

or tech-driven?

In her article, Inger reported about the outcome of a little informal poll showing a failure rate for translators passing professional
test translations about 70%, although they all were qualified translators, many of them with quite a lot of experience.
Being good in any language-related profession is quite an intellectual challenge. A challenge that no one can be educated to win.
One of the main reasons for this is the persistent shortage of modern educational programs, in the first place to prepare people to
fill language-related positions, being most of the existing programs inadequate.
Nevertheless, in the light of my personal experience in training translators for about ten years and practicing translation for nearly
thirty, I dare say there is no ideal course description to be taken into account when designing a translation course, and no ideal
approach to teaching.
What I learnt from my experience as a trainer and, lately, as a teacher is that
• Teaching everything is impossible;
• Teaching does not equal learning;
• Problem solving can’t be taught.
Before starting teaching in the university, I had long been training people from my company, my company’s customer companies,
and my customers. I thought of myself as lent to university. In fact, I was, and still am not a fan of academics, who generally show
little or no interest in the real life beyond the fences delimiting their little gardens.
Sometimes, some universities are very good at understanding what they need to teach so that their students can find their way to
success. They include practical and even hands-on sessions in their programs covering many relevant technical subjects. One major
problem, though, is often finding the right staff: professionals with a sound experience who are also good teachers.
It is also true, however, that translation schools are still focused on outdated issues, simply to recycle teachers; to some extent, I am
a product of this recycling myself. Furthermore, these teachers are language teachers, and while still important, language
knowledge is no longer pivotal. Nonetheless, a theoretical, although methodological approach is still valid. Recently, at the 6th
International EUATC Conference in Rome, I heard someone saying that the difference between a professional who studied to be a
translator and an amateur translator is the ability to give reasons for his/her choices. This is only partly true, because translation
schools still approach translation from a purely linguistic point of view, they “forget” to teach their students to face the changing
reality.
One thing I could say on translation courses is that special care should be given to methodology to pursue efficiency in translation,
but this could be achieved only from pursuing efficiency in teaching.
The first problem to deal with when teaching to freshmen is writing. Students often graduate from public schools with modest
writing skills.
Many translators, especially new translators, can’t see themselves as writers, and yet translation is writing: translating is (re)writing
a text originally written in a language in another language.
However, not only students do need to learn how to use the rules of grammar and syntax correctly, they should be taught how to
understand a text in a language other than theirs, reword it, and rewrite it according to the conventions of the intended readers.
And yet, students should be first taught to plan, structure, and develop a text on a given basis. Then they could be trained at
exploring and analyzing a given text with translation in mind. Traditional disciplines such as discourse analysis and contrastive
analysis, not to mention translation theory, could still be relevant here, but can no longer be pivotal, at least as long as they are kept
disconnected from current practice.
Another issue with freshmen is culture. Translation remains a very intellectual job where culture is crucial, but culture requires time
to be developed.
Specialized translators should be educated in special areas such as economics, finance, law, science, medicine, and the like.
Nevertheless, they do not need to be taught to become economists, lawyers, scientists, or whatever but to develop the necessary
skills to deepen each area of interest. They should be taught to detect and process different text types as they were authors in the
relevant fields.
Julie McDonough Dolmaya of York University in Toronto profiled 76 translation contributors to Wikipedia, a typical crowdsourcing
project. All of Wikipedia has been written by crowdsourcing since before the term even came into use., and a great deal of its
entries, especially in languages other than English, has been produced by translating on the same model. In general the translations


or tech-driven?

are good as regards both content and language. Nonetheless, most respondents responded that they had no formal training in
translation, and only a minor fraction is made up of expert professionals. This is probably because each article requires an advanced
education and knowledge of its subject field and of the accompanying terminology.
There are many new subjects to know and there is much more to know about each of them since categories are extremely broad in
themselves. No translator can be expected to have the knowledge required to translate all types of documents well and within a
reasonable amount of time.
As knowledge expands in all areas, translators can simply no longer be expected to master the large body of concepts found in most
subjects and the associated terminology in two or more languages.
On the other hand, the growing momentum in the volume and nature of content already requires new production models and new
approaches.
Modernization, urbanization and globalization have been affecting translation earlier and more than any other job, making people
and jobs interdependent. Fragmentation of work makes a significant number of people use only a small fraction of the information
available, and any job meaningless.
Therefore, farsighted people in those universities that are really good at understanding what they need to teach should urge
student to develop a holistic approach to translation.
Anyway, any goal can be targeted only with the evaluation criteria of the present, as an imperfect result of our knowledge, and the
closer your vision gets to a provable future, the more you are simply describing the present.
Now, technology is already playing a growing role in every area of everyday (working) life.
In the near future, translators will increasingly be asked to use new tools of even greater sophistication and new software
infrastructure for their job that enable projects and even tasks to be further parceled out.
Crowdsourcing, for example, is unstoppably leading to the ultimate success of microtasking, with players seeing only a tiny part of a
project, even if collaborative platforms allow them to have an overview and get involved with any portions they are knowledgeable
in.
As microtasking gains in adoption, more crowdsourcing platforms are seeing success with adding an extra level of quality control on
top of the basic input – output model.
The challenge for translation teachers will not be to be good at using and teaching how to use these tools, but how to shape
processes to take the most from any of them.
The smartphone app experience tells us that tools will be increasingly easy to use, and parceled out too. To be effective, teachers
will have to teach students to evolve as tasks change, and run a sustainable and efficient working system.
The problem is the approach to translation that is definitely not economic, and this is critical because most translation educators are
not real translators; they are mostly linguists, scholars and literature devotees, and are not willing to change their perspective for
the sake of their careers.
Unfortunately, the only way to become aware of the business view of translation is to be challenged by those who pay for
translation, for the product, not for the hermeneutic process, customers.
Teachers should then start teaching:
1. that quality has a different definition for different purposes, with many variables and levels;
2. that quality is the customers’ opinion and perception of the value of the suppliers’ work output;
3. that quality is to be measured on a predetermined set of requirements, and to respond to such requirements;
4. that planning is always required to achieve some quality.
Technology is advancing too fast to keep up. The new frontier is set on standards, so there’s no sense in chasing any new version of
a commercial software product whatsoever that will soon be obsolete in itself.
There was a time not so long ago, when competition favored the big against the small, then the fast against the slow. Today, even
responsiveness is no longer enough: you must be ready, fast, moneyed, and error-sensitive; humble, but not submissive, honest, but
not naive, cautious, but not fearful, astute, but not hypocrite. Can anyone teach to be so?


or tech-driven?

Today, technology is definitely in favor of the translators. Google Translate is a great example. Google has succeeded in a couple of
years to do what dozens of “experts” have not done for decades in machine translation, and for machine translation and translation
as well, more than anyone else. Google has made access to translation easy and free, and today it is less likely to run into
unsuspecting users, who go to their niece who is studying English and spent two weeks in England.
It won’t be machine translation to drive translators out of their market; translation educators will. More and more people now think
that translation theory has little to do with translation.
Under the new conditions of volume, content type, and publishing times, the founding elements of traditional education of
translators make the job simply uneconomic and inefficient, regardless of the tools and the technology used to do it.
The demand for machine translation was born here and is driven by the need to translate information quickly, as speed is
increasingly important than quality. Technology has been affecting the language services industry for two decades or so.
Technology, in the language services industry, and even more in translation schools, has always been surrounded by undertones of
general anxiety. And yet, resistance to technology in the fear of job loss is unmotivated. It could have been even more if universities,
more than professional organizations, had played their role in helping aspiring translators as well as professionals to meet the
challenges of technological development, but they missed a chance and came terribly late. Now, it is maybe the last chance to
adjust.
In an interview to Nataly Kelly of June 13, 2011, Raymond Kurzweil, author, inventor and futurist, predicted that machines will reach
human levels of translation quality by the year 2029, and yet even major technological advances in translation will not replace the
need for language learning. According to Kurzweil, we will expand our intelligence through technologies that enable us to learn
other languages more quickly.
In one of his books, The Age of Spiritual Machines, Kurzweil predicted that spoken language translation would be common by the
year 2019. When asked about this prediction, he noted, “It all depends on the level of quality you’re looking for.”
Kurzweil does not believe that translation technologies will replace human translators and interpreters. What they will do is replace
a certain way of applying knowledge.
This is why, to meet the expectations of this multi-faceted changing industry, translator training should be knowledge-driven rather
than tech-driven. Knowledge should be transferred to have would-be translators exploit technology.
Machine translation will change the translator’s work. Translators could be left with post-editing only, or could bend machine
translation to their needs, put it in the service of their customers, and help them to get the best out of it. So, translation students
should be taught to deal with “translation probability”, and to write even and possibly mostly for machine translation.
In the near future, translation tools will move gradually but rapidly in the cloud. An increasing number of translation projects will be
done on collaborative platforms, but they will not necessarily be crowdsourced. Collaborative management tools cannot be
intrinsically proprietary, even if they should not necessarily be free, indeed. These tools are, in fact, much more open and designed
to evolve with technical and process advances than industry standard (proprietary) tools that are generally inherently obsolete.
The fastest-growing areas of the industry are Internet-based, with user-generated content in the first place, and yet current
translation methods, technologies, and tools are all for traditional static content. Even when assisted by the most advanced
technologies, traditional human-generated translations are more and more costly and slow.
The need now is for real-time or near-real-time translation and for cost effectiveness, and yet human translators have been never
and are still not taught to be cost effective and to concurrently support really quick turnaround times.
Translation students should be taught, right now, to deal with very small chunks of text (microtext) and with non-text assets, as well
as to integrate several methods and tools in their practice.
Translation students should be taught to understand the data they will be called to process, analyze, integrate, and refine, to build
terminology beyond correspondence lists, to build high-volume, high-quality translation memories and (even monolingual) corpora,
to understand technology and processes.
Students should also be taught to perform text mining, customize machine translation engines, and run search engine optimization,
with no prejudice, because language keeps changing, and we will always lag behind.
One of the simplest things that can be said with respect to the profession of translator is that, over time, and especially in recent
years, translation has become increasingly simpler and easier, especially in the eyes of buyers. As a matter of fact, the variety and
availability of technological tools and their apparent simplicity make the translator’s job even more easily accessible than ever, and


or tech-driven?

this helps devalue the effort and dedication needed to acquire the specific technological skills together with the typical language
and translation skills.
Language services industry will keep flourishing, translators will hardly do as well: language services professionals are rarely
recognized, let alone compensated, at levels that match the role they play as global business facilitators, and the fear of change and
their persistent lamenting generate a further drop of respect in the business world.
On the other hand, thirty years ago, even a simple search could take a long time in a library, a translation had to be produced on
paper, perhaps with a typewriter, and errors, even typos, were a real nightmare, and liquid paper was welcomed as a miraculous
invention. Only few and expensive specialized dictionaries were available, strictly on paper and they often proved insufficient, thus
forcing translators to accumulate pages on pages of glossaries, which ended up being their wealth. Today, a complex search can still
take some time, but, in general, search engines allow any student to browse and find a huge variety of sources, while the Net
provides tons of terminology, easily accessible, when only twenty years ago it was necessary to have specific tools that were not
available to everyone. The Internet also makes the exchange (and often the interchange) of data, and working virtually anywhere
possible, with even more and more powerful and cheap tools.
According to his biographer James Boswell, Samuel Johnson said that knowledge is of two kinds. We know a subject ourselves, or we
know where we can find information upon it.
Darwin, for example, is often misquoted. The Darwin Correspondence Project has identified the source for a notorious Darwin
misquotations (It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most
adaptable to change.) This phrase is ubiquitous on the web, and was prominently placed in the stone floor of the new headquarters
of the California Academy of Sciences. The source has identified in the writings of Leon C. Megginson, Professor of Management and
Marketing at Louisiana State University at Baton Rouge. Recently, this phrase has been misquoted even on the website of the Italian
Encyclopedia of Science, Letters, and Arts, generally regarded as the most authoritative Italian knowledge institution.
But a simple search today can tell you right from wrong.
Tools are going to increase humans’ ability, with the help of machines, to command greater ability to use language. The epitome of
human intelligence is our ability to command language, and that is why Alan Turing based his test on it.
Up to forty years ago, skills came from knowledge; since a decade or two, abilities have been dominating knowledge. Today, not
only is expert knowledge in a given subject very important, technological skills are becoming increasingly relevant to be capable of
accessing the appropriate resources.
Today, translation competence is a three-legged table, based on data, tools, and knowledge: it is less and less a question of language
knowledge and more one of knowing how to use it and the right tools to exploit it. These three legs must be of the same length,
then grow at par, for the table not to wobble.
Language is just a technology as Mark Changizi, Director of Human Cognition of 2AI Lab recently suggested. Knowledge is made up
of skills that must include being able to use tools and producing data, access it and use it, and translation students should learn how
to use language as a tool not an end, maybe in itself.
A widespread agreement exists within the translation industry that translators must specialize, as language service providers are
increasingly focusing on specific subject areas to meet the customers’ demand. However, the rapid growth of information and
knowledge, translation technology, and terminology resources are re-shaping the nature and meaning of specialization.
In translation, there is no common core of education, or common standard of knowledge, or achievement, then the so-called
specialist translator might not even have the basic language skills and knowledge of the ‘generalist.’
For this reasons, university should not prepare for work, but to form knowledge and the ability to exploit it, and companies can and
actually should activate to promote this training, rather than merely state their expectations, which are doomed to be left unfulfilled
because the pace of universities is not and cannot be that of the labor market. If universities chase companies on this ground,
hoping to increase their employment rates and their prestige they are mistaking.
Therefore, rather than simply keep on complaining for the lack of qualified resources and blame translation schools, employers must
reconsider their notion of the “perfect” candidate. Instead, they should look for individuals who can grow into model employees for
their companies, including current staff, and integrate the education of new translators, rather than students, with post-graduate
courses, workshops, and conferences, and offer them discount rates to attend.


or tech-driven?

Bio
Luigi Muzii has been working in the documentation field for almost 30 years, as a translator, localizer,
technical writer, and consultant.
After 12 years in several departments of a major Italian telecommunications company and two in a
broadcasting service company as education manager, taking part in many projects, on both the domestic
and European markets, and developing a sound technical and technological expertise, some a decade ago
he started a consulting firm to act as an information design and delivery consultant.
He was a founding member of the Italian Association for Terminology and of Gruppo L10N, a group of GILT
(Globalization, Internationalization, Localization and Translation) professionals 'volunteering' in localization
educational programs.
He published a book on technical writing, and dozens of papers and articles on documentation, translation, and terminology, speaks
regularly at conferences, and holds seminars and workshops.
Recently, he has collected some articles from his blog, written between 2007 and 2011, in a book published by Lulu titled Taccuino
barbaro (A barbarian’s notebook).


Perspectives in translator training: knowledge-driven or tech-driven?

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