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By Lilian Lim

As Haugh and Head said, communicating in a foreign language 'requires that learners must also have knowledge of cultural contexts and thinking in that language in order to comprehend real communication' (Haugh & Head of School of Languages, 2018). This is precisely what I encounter daily as I live and work in a country where I am still learning the language - Vietnamese. When I rely on set language phrases or Google Translate, I run the risk of sounding too formal and distant or too casual and close in a society that is highly hierarchical. This social hierarchy is reflected in their use of suitable pronominals (pronouns) out of multiple options depending on the age, type of relationship and socio-economic status of the listener vis-a-vis the speaker. I therefore do not expect machine learning to replace actual language learning but to be an aid to language learning and practice since a machine is infinitely more patient and available than a human tutor.

I have found that learning from a machine learning app like Duolingo to take up about 20% of my language learning and I use it more for reviewing old phrases and vocabulary. I also use an online/offline language learning platform, Vietnamese Pod101, that contains topical and graded audio and video lessons with native speaker hosts. This platform has vocabulary building tools, covers all four language communication skills and has a community forum. I use this platform about 50% of the time to receive new language content which I can personalise according to my interests and pace of progression. A personal human tutor is available on paying the premium plus fee. And that will take up the next 10% of my language learning time. I use Google Translate when I need to communicate beyond what I am currently capable of doing  for about 10% of the time. Finally, I am also constantly learning when interacting with my immediate community. This multiple targetted approach has been inexpensive for me as app subscription fees are much lower than paying for a class. I can therefore see AI increasingly becoming a game changer for language learning, but not fully able to totally remove the human teacher.

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Hi Aggie, thank you for sharing your experiences here. They are very thought-provoking. AI picking up on lips and other impediments is really a good tentative idea. Besides, I agree with you that AI-powered language learning tools are targeting at low-intermediate level learners at current stage. There is no evidence showing that they have matured products that have the capability to facilitate upper level language learning.

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(Aggie Woodworth) I don't think that AI and Machine learning will replace the need for learning a foreign language. Just last week I received a new international student in my kindergarten class who only speaks Brazillian Portuguese. He is reluctant to learn English and I am communicating through google translate to help explain tasks. As a 5 year old, it is almost impossible for me to understand him (his voice is not clear enough for the microphone to pick it up) and he is unable to type and translate. In these types of situations, I wonder if machine learning will eventually pick up on lisps and other impediments.
My other comment is about the language learning tool being an asset for young families. My parents came to Canada at 24 and 27 with a 4 and 5 year old without knowing anyone here. My mom had to put me into daycare quite quickly to do English classes for about a month so that she would be able to communicate at the doctors, the store and school. However, she stopped as soon as she had a basic grasp of the language due to time restrictions and being away from us. I wonder if AI language learners were available to her then would she have a further grasp of the English language?

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Reply to Philip - I would have agreed about ten years ago, maybe even five, in the days of Microsoft Sam, but have you heard the most recent build of Google Assistant and Siri? Their English cadence is impeccable, it's nearly impossible to tell they're AI, and it's only going to improve.

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Philip Barrington   I have a hard time seeing it but I recognize that it will happen. The beauty about learning another language is hearing the cadences of the sound. This allows you to not only focus on what you hear but also focus on the rhythm of how someone is saying the phrases. Hence, it is hard to see how AI can replicate these sounds. I think back to a few weeks ago when I heard a Chinese news network introduced their 24 hour AI news broadcaster. Even though he was speaking in English, the tone and the voice was far too robotic for me. It did not sound human despite all the efforts to make the AI look and feel like a human being was talking
. However, I know that over time we as individuals will get used to the sounds of the AI and this will become a mute point in the future

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Reply to Scott: Agreed that machine language learning is already being used to supplement human or f2f language learning. It makes me wonder how long it will be until the threshold is crossed that it will no longer supplement f2f learning, but rather be the learning media. When AI can bridge cultural barriers, I'm of the notion this is when this threshold might be met. -Reg Surette

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I'm so happy to hear everyone talk about the 'art' and 'romance' of learning another language. While modern language apps are helping with accessibility, they're replacing the most boring parts of the language classroom - rules, materials, gap-fills ... (though some of us geeks may enjoy these independent learning pursuits). If this weakness hadn't already been noted by students in traditional language learning classrooms, I'm not sure these learning technologies would've come about. The idea that AI can help someone to practice or learn a language is certainly disruptive, and should be welcomed by students and teachers alike - those of us who've spent years trying to learn a language and still can't communicate in it can attest to the importance of practice. This could create more space in a traditional classroom to share ideas, to choose words carefully, and to engage spontaneously with the language – in other words, truly communicate!

In our class, we used a program called English Central – this program analyzes speech patterns and grades each student’s speaking based on their own AI systems. While it’s been useful to have students practice speaking at home (enabling them to overcome their shyness), it can be difficult for students to understand why they’re not getting the grade they want. In one situation, I tried it myself and received a low mark; when I changed the tone of my voice to match the example, I scored higher. Learning a language has a lot to do with identity creation and the L2 self – if a robot teaches me, will I end up speaking like a robot? Will I create new patterns or simply repeat those I've been exposed to?

Lastly, in each f2f course I teach, I ask students how they prefer to learn – online, blended, or face-to-face. The answer is always unanimously face-to-face. Each student is looking for spontaneous human interaction. I think we all know the difference between speaking to someone directly and speaking through a machine (though I’ll admit those machines are catching up). If someone’s purpose is to learn language quickly in order to gain a degree of professional position, I applaud their use of AI and translation tools to communicate effectively and quickly; for those people looking to truly communicate (moving to a new country or being in a relationship), I don’t think AI will replace human experiences.

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Translating between human languages is something which artificial intelligence - specifically machine learning - has proven to be very competent at.

So much so that the CEO of one of the world's largest employers of human translators has warned that many of them should be facing up to the stark reality of losing their job to a machine.

One Hour Translation CEO Ofer Shoshan told me that within one to three years, neural machine technology (NMT) translators will carry out more than 50% of the work handled by the $40 billion market.

His words stand in stark contrast to the often-repeated maxim that, in the near future at least, artificial intelligence will primarily augment, rather than replace, human professionals.

Shoshan told me that the quality of machine translation has improved by leaps and bounds in recent years, to the point where half a million human translators and 21,000 agencies could soon find themselves out of work.

He says, "The analogy that we can use is Kodak and digital photography - Kodak didn't see it coming ... and before that, Corona typewriters and word processors

"Two years ago, translation technology would produce something that at best would let you get a general understanding of what the text was about - but in most cases, a professional translator would tell you they would rather just translate from scratch because they couldn't understand a lot of the output.

"Today with neural machines, for a growing amount of material and categories, they only need to make a very small number of changes to what a machine outputs, in order to get a human-quality translation."

Quantifying this, Shoshan tells me that today on average 10% of a machine-translated document needs to be fine-tuned by humans to meet the standards expected by his company's Fortune 500 clients. Just two years ago, that figure was around 80%.

This has been made possible by the switch to neural machine translation - sometimes known as deep learning - adopted by the most advanced machine translation tools. Previously these relied on a method known as statistical translation. Google, Bing, and Amazon now all use NMT in their translation engines.

Training a neural machine to translate between languages requires nothing more than feeding a large quantity of material, in whichever languages you want to translate between, into the neural net algorithms.

To adapt to this rapid transformation, One Hour Translation has developed tools and services designed to distinguish between the different translation services available, and pick the best one for any particular translation task.

"For example, for travel and tourism, one service could be great at translating from German to English, but not so good at Japanese. Another could be great at French but poor at German. So we built an index to help the industry and our customers. We can say, in real time, which is the best engine to use, for any type of material, in any language."

This work - comparing the quality of the output of NMT generated translation, gives a clue as to how human translators could see their jobs transforming in coming years. Humans rate the output of each engine and compile the index. In the case of One Hour Translation's index, this is done once per quarter, to reflect the speed at which NMT is evolving, and new players are emerging onto the market.

If that sounds like a silver lining, however, then things may not be quite that straightforward. The level of training and expertise required to rate machine translations, or to translate while "augmented" by a machine, is far lower than for traditional, "from scratch" translation.

"You need someone smart, with good language skills - but they don't need to be a professional, traditionally-trained translator, because fixing one word here or there is much easier," says Shoshan.

So, as was the case during the first industrial revolution, are we likely to see gangs of translators rioting in the streets and smashing up the intelligent machines which are threatening their livelihoods?

"I hope not," Shoshan says. "But actually, it is an issue, just like autonomous trucking will be an issue for the four million or so truck drivers employed in the US.

"And importantly, we're not talking about five to ten years; we're talking one to three years.

"It's obvious that if machines can do what you can do, then you have a problem. A lot of translators and agencies will tell you that there are certain highly specialized translation services which will require a human touch for the foreseeable future - and that may be true.

"But for the bulk - I would estimate 80% - of the material that corporate customers pay to have translated on the market today, it will be machine translatable in the next one to three years."

Some advice for translators wanting to keep their heads above water could include specializing in languages which are less widely spoken. NMT services rely on huge bodies of literature being available, to train the algorithms - and for languages with a smaller user base, that quantity of material may not be readily available, particularly in specialist, technical or scientific subjects.

Another, as is the case with One Hour Translation, could be to get used to working alongside machines. While they will do the bulk of the work, there will be a need for people able to assess different translation technology and apply the correct tools for specific jobs.

One thing seems certain, however - hiding your head in the sand and pretending that none of this is happening is a recipe for unemployment.

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Will Machine Learning AI Make Human Translators An Endangered Species?

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AI, and more specifically machine learning, deep learning and neural machine technology, will soon take over jobs which are currently performed by experienced and well-educated humans. Here we take a look at translators and how their job will be augmented and automated by intelligent machines.

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Henna Patel: I am a Trekkie. If that means something to you keep reading. I grew up thinking the Universal Translator was one of the many incredibly cool things in the exploration of new galaxies.

Much of my fondness was because English was not my first or second language,  but my third. So often, in school, I would try to express certain thoughts(thinking in my other languages)  in ways that were not always natural to spoken English. And I think what AI in language learning has opened up is a world where we will be able to communicate more accurately with each other. It is exciting to think few things will be lost in translation. Yes I think this is a game changer. For business, doctors working across the globe with each other, pan-country research collaboration, innovating for education where there were once linguistic barriers...the list goes on.

However, I think there is a romance in the pursuit of actually speaking other languages. Forming the sounds on your own, training your ear to listen to inflections, and aspirations and the way jokes are made. That is a very human pursuit, it is full of flaws, and awkward, funny, embarrassing moments - that make wonderful stories. If we stop trying to learn how to speak other languages, because the machine does if for us,  I think we become less emotionally connected to our experiences in moving around the world.

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AI and Languages (Reg Surette)

The fact that these AI tutors have been compared to, and even score better than, human-human variance is really interesting. Using AI to enhance Language training is a great example of AI being implemented to benefit a specific niche market. I personally think it has the potential to be a game-changer, as travelling to areas requiring immediate translation would become a non-issue, and allow the communication barriers between languages to essentially erase. That said, there is still a cultural aspect that is not addressed by these products, however eliminating a language barrier could in turn improve cultural appreciation.

Big name companies such as Microsoft and Google have AI-based translation apps available, so I'm of the opinion that AI for language learning and training is definitely a disruptor in the market.

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Heeweon Joo - I also do think that AI will be a game changer in Language Learning Industry. As a second languages learner myself, I would like to speak from my experience on how language learning could have helped me. First, just like Dustin has stated, learning a second language learning should happen whenever and wherever they are. Traditionally, students usually went to language school, hired a tutor, online lecture and by other means. This was usually a planned activity, which also has a certain date they could participate in the learning. But with AI, it removes the barrier of such inconvenience. I also want to emphasize on the importance of actually using the language (communication) to improve language skills. Speaking from my background, I learned English and Japanese not much from textbooks, but from communicating with friends who speak that certain language. In the future of AI, I do believe that it will have the potential of becoming a conversational tool for students practice their speech and etc.

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(Dustin Hyde) I also think that AI is going to incredibly disruptive, and without question, a game changer to the language learning industry.  Ultimately people interested in learning languages want anytime, anywhere access to language learning.  The old concept of paying for a tutor, or downloading a computer based program, or worse, purchasing a set of CDs or DVDs is simply not going to compete with the far more convenient and affordable AI enhanced options that exist in the marketplace today. The wave has already started and it will only improve with increased technology, user feedback, and ultimately time as the AI machines improve with each learning interaction. Based on the video and text information in this page, AI is getting close and closer to providing human like teaching quality to language learners at a fraction of the price. Liulishuo, as described by its CEO and founder YiWang, is offering high quality English tutoring to Chinese people at a third of the traditional and standard cost of English tutoring -- $15 per month, not to mention that learners have 24/7 access to AI language learning. The human competition, simply cannot compete with that price point.  And while, the human competition may offer a more high quality education, the improved technology, gamification, learning analytics and other improving features coupled with the anytime access is ultimately going to tilt the scales in the favour of AI enhanced language learning over the now older, human based option.

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(Scott Skanes)
I do think AI is a game-changing for language learning. Like Winter mentioned, AI or machine learning may not replace language learning (from humans) entirely but I think it already does a dang good job of teaching, and will only get better.

Winter mentioned how nuanced language learning is, how artful it is, and how we learn is highly dependent upon our cultural background among myriad other factors. Being taught by a computer which has only learned through AI methods means we will still, essentially, be learning one specific language approach. That in itself is not a huge deal, because we all already learn language in a very specific way depending on who is our teacher. The problem here is that if an increasing number of us are taught by the same AI system, all those students will be biased in a similar way. Is that a good thing, or a bad thing? I’m not sure.

To get back to my point though - I do think AI-assisted language learning is an excellent tool for those looking to learn a language, especially those who don’t otherwise have the time, money or opportunity to learn a given language. While AI and machine learning translation machines will replace the need of learning a foreign language for some, many others will likely still use AI to do the opposite - to help them learn a foreign language.

To this end, the AI systems within many language learning tools is not just a selling point; it allows the systems to learn from its users. Take Duolingo, for example. For every user that provides a translation for a sentence, the platform learns. This counteracts one of the downsides mentioned by Winter, which is how many translators choose the simplest, most basic translation of a sentence. By gathering translation from real users and adjusting its data and translations accordingly, it can learn to generate translations which more accurately represent what was trying to be said.

The apps still don’t have a “culture assessment” feature, though. Any ideas on how this could be implemented? :D