The Linguist is a languages magazine for professional linguists, translators, interpreters, language professionals, language teachers, trainers, students and academics with articles on translation, interpreting, business, government, technology
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INSPIRING A wearable 'translator' is among the newest technology on offer (left); and (right) audience members listen intently to the Threlford Lecture in September 12 The Linguist Vol/55 No/6 2016 www.ciol.org.uk FEATURES susceptible to computerisation, but with the advent of big data (such as that provided by translation memories), concomitant progress in machine learning and advances in mobile robotics, non-routine cognitive and manual work have both become more amenable to automation. In one widely cited recent study, Carl Frey and Michael Osborne estimate that, over the next two decades, 47% of American jobs are at high risk of computerisation. 7 Interestingly, the work of interpreters and translators does not fall into this category, but appears in the lower end of the medium-risk group. Their work is characterised as requiring high levels of social and creative intelligence – requirements that are seen as creating engineering bottlenecks when it comes to computerisation, even in this era of big data. It is also worth noting that translation and interpreting are labelled as 'bright outlook' occupations by the US Bureau of Labor Statistics, based on the expectation that employment in the sector will grow at a much faster rate than average over the period 2014- 2024. According to this analysis, it doesn't look like translators and interpreters should be throwing in the towel any time soon. Further insights come from analyses of the market for post-editing. While various surveys show a growing number of language service providers offering MT with post-editing as a service, it is not always clear how much money they make from this activity. The sector-wide survey conducted by Common Sense Advisory in 2014 suggested that MT post-editing accounted for around US$1.1 billion, which is a considerable amount but represents only 3% of the language services market that year, with the vast bulk of revenues coming from traditional translation. A wholesale shift from translation to post- editing does not seem to make sense, and universities need not abandon the training of translators any time soon on these grounds. On an individual level, translators might see value in integrating post-editing into their profile, while others may balk at the low rates that are sometimes offered. Comparative pay The level of remuneration appropriate for post-editing services is a pressing issue. In 2012, the translation agency Translated.net conducted an experiment to work out what would be fair compensation for post-editors. It sent out purchase orders offering different rates for two related jobs: one for translation from scratch, the other for post-editing MT output. The aim was to find the point at which at least 75% of translators would opt for the post-editing job over the translation job. For English to French/Italian, 75% opted for post-editing once it was paid at 73% of the word rate for translation. In other words, these translators were willing to give a 27% discount for post-editing MT output. The tipping point for English to German, on the other hand, came at 110%. That is, translators wanted a 10% premium for post-editing MT output. The pricing model was ultimately considered unworkable, with the conclusion that post- editor productivity could best be expressed in terms of two key performance indicators: edit time (i.e. the average number of words processed by the post-editor per unit of time); and effort (the average proportion of words changed by the post-editor in the MT output). These are metrics that can now be fairly easily captured by additions to the very software that post-editors use to do their work. They represent part of the translator/post- editor's 'data exhaust' – by-products of her digital activity as she works her way through a translation using a TM tool enhanced with SMT functions, and, crucially, a keyboard logging tool. Keyboard and mouse activity logging, as well as eye-tracking capabilities, have already been built into experimental translation environments, such as that developed for the Casmacat project. 8 Even if this project aimed to develop translation and post-editing interfaces to provide better support for human users, it may one day be seen as the vanguard of tools that bring surveillance of these users to a new level. Dumbing down But what of enjoyment in post-editing? The verdict of many practitioners is not very flattering, with Joss Moorkens and Sharon O'Brien reporting it to be "an edit-intensive, mechanical task that requires correction of basic linguistic errors over and over again". 9 As one of their informants puts it: "it's mechanics, and if it's mechanic, there must be a way it could be done by a machine." This is one of the supreme ironies of contemporary