The Role of Humans in the Language Industry While Machine Learning Evolves

Chetna Aggarwal (MATLM 2020)
Chetna Aggarwal (MATLM 2020)

How Artificial Intelligence Changes Your Decision-Making Process

The success of the Georgetown-IBM collaboration in the 1950s lead researchers to think that machine translation will replace human translation in only a few years (Kelly, 2014). Among the first things that I learned after I started immersing myself into the translation and localization industry was that this statement is not true and that machine translation will not pose a threat to the future generations of translators (Nimdzi, n.d.). A major reason for this is the fact that this technology and one of its subsets,  artificial intelligence (AI), are still developing and therefore a fully automated, high quality and unrestricted translation is currently not feasible without human intervention. How can businesses and other stakeholders in the language industry then prepare themselves for this evolution to maximize their returns and simultaneously offer the best possible service within a short period of time?

Machine Translation and the Business Model Canvas

I would like to use the business model canvas developed by Alexander Osterwalder (see appendix) to illustrate my thoughts on these processes. The reason I opted for this strategic model is because it organizes the decision-making process of a project manager (PM) in a logical and organized way and depicts all relevant areas of a business.

First, the decision-maker, who may be a freelance translator or a PM in a company, needs to consider his or her value proposition. In other words, how will machine translation change the company output that will be used by the end-consumer? There is tremendous potential and rapid growth that PMs need to be aware of, which can overall be described as a continuous exposure to AI in the next years to come (O’Dowd, 2019). What will change for the client? While companies become more agile by using new technologies, customers benefit from a more interactive, customized and high-quality product or service (Nimdzi, n.d.).

A second area that illustrates the supply side of the business model canvas includes the key partners (who am I working with), the key activities (what do I need to do) and the key resources (what do I need) that define how a company intends to offer the value proposition. While AI offers many new opportunities to grow, it also requires PMs to be on the constant lookout for new technologies and train their work force accordingly to finally create competitive advantage. The introduction of neural machine translation in the late 2000s has already been a major breakthrough in the industry that will allow PMs to allocate company resources more efficiently. Time spent on simple or cumbersome translation processes can instead be used in areas where problem-solving skills, creativity or innovation is needed (Nimdzi, n.d.).

To become more efficient, companies need a reliable labor force and trustworthy language service providers as partners who produce or contribute to the desired output. PMs need to make decisions on which tools and features they require and what kind of staff is used for each and every step in the translation and localization process. These changes, if implemented correctly, can not only reduce production time and costs but also increase the translation output. However, with the rise of modern technology, data security has become an even bigger issue. In other words, using machine translation can also harm a client when confidential data in a translation memory is disclosed or deleted. Hence, a part of all key activities and resources are the methods and tools (i.e. blockchain) used to protect sensitive data.

A third area that the business model canvas is concerned with is the demand side and therefore, the end-consumer. How do I maintain the relationship to my customers (customer relationship), who is my customer (customer segments) and finally, how do I sell my product or service (channels)? While machine learning does not directly affect these areas, it is still very important to consider these factors because bad machine translation technologies are the reason why companies choose to consult professionals to complete a job. Customers are the ones who are directly affected and the reason why translations are completed in the first place. Using modern technologies to complete a task and to store data with translation memories or term bases is ultimately beneficial to the end-consumer. Post-edited translations and / or layouts are saved and can be reused for future jobs, for which less time and money will have to be invested.

Finally, the business model canvas discusses the cost structure (how much do I need to invest) and the revenue streams (how much do I need to earn to break-even). The combination of the two result in a minimum viable product that we are able to bring onto the market. Machine translation, especially AI technology and neural machine translation are better technologies than any of their predecessors. However, the initial investment is also much higher, considering the fact that it is new technology still in the development stage (Nimdzi, n.d.). Currently, such an investment makes only sense if the amount of translations to be completed is big enough to sustain such an expense (i.e. user manuals as opposed to websites). However, is the company operating in multiple countries and translating documentation into numerous languages, it might make sense to invest in AI and the required training to operate these machines.

All of these points and the totality of the business model canvas show which decisions and processes a PM has to go through when considering machine translation in his or her business. It starts with defining how AI will enhance the end product, followed by identifying which part of the business is concerned and choosing whether these new technologies can in fact maximize the company turnover. In the case of a positive inclination for AI, a company scan needs to be completed to conclude whether a minimum viable product can be produced after having addressed all issues around the value proposition that are essentially the various areas of the business model canvas.

What Does This Mean for the Future of the Industry?

The production of the first machine translation in the 1950s was merely a start to what might become fully automated translation. It is evident that computer-assisted technology is required in a globalized world, where a vast amount of data and information crosses borders within milliseconds and the need for translated text has become more important than ever to reach the largest possible audience. However, even though technology is ubiquitous, it is clear that human translators are indispensable. Though the role of the translator is slowly shifting towards one of an editor (especially with neural machine translation), the complexity of a language cannot be mastered by a machine (Kelly, 2014). The primary reason for this is the context of a document and therefore, the translation quality. English words such as “get” or “run” have a myriad of meanings that cannot all be understood by machines, which is mostly the case with idiomatic sentences or similar texts for different industries. Therefore, the translation and localization landscape continues to become more technical, however, it won’t exist without human involvement. Translation and technical priorities will finally, allow for a different resource allocation that will increase the final output.


Kelly, N. (01/09/2014). Why Machines Alone Cannot Solve the World’s Translation Problem. Huffington Post. Retrieved from

Nimdzi. (n.d.). AI Meets Localization. Nimdzi. Retrieved from

O’Dowd, T. (01/01/2019). Localization tech predictions for 2019. MultiLingual. Retrieved from

Osterwalder, A. (2019). The Business Model Canvas. Strategyzer. Retrieved from


Journey of a Recent Graduate

Zilin Cui (MACI, 2018)

This is my interview of Zilin Cui who graciously shared her interesting career moves since graduation.

  • Tell us about what you have been doing since graduating in May 2018.

I moved to New York in June to pursue an internship with the United Nations. I started in July with the Chinese Verbatim Reporting Section (CVRS), and then moved on to Chinese Translation Service (CTS) in September 2018, finishing in January 2019. A little back story: I applied to the CVRS internship in March of my second year and was accepted in April; I had applied to a different internship with the Chinese Text Processing Unit (part of CTS) in the winter of 2017-2018 and was pleasantly surprised when I heard back in April asking if I was still interested. I said yes and the rest fell into place over time.

While working in New York, I have also been freelancing as an interpreter and translator first part-time and then full-time after my internship. I worked on some interesting assignments, including a training course at Georgetown University, two assignments at the UNHQ, and one with the Inter-American Development Bank in Costa Rica. The assignments at the UN were unexpected. I received an email one day from one of the chief interpreters asking if I’d be available for the United Nations Alliance of Civilization Group of Friends Ministerial Meeting during the last week of General Assembly. Turns out I had been recommended by a Spanish interpreter with whom I had  previously worked at a conference. The conference itself was poorly organized and what was supposed to be Chinese < > English simultaneous interpretation ended up involving a lot of Spanish > Chinese on the fly and there was no time to set up relay with the Spanish booth. Having worked as a Chinese < > Spanish conference interpreter before in Chile and trained in three languages at MIIS, I was fortunate to have no problem handling the situation. When we finished, one of the Spanish interpreters commented that she had never heard anyone work from Spanish straight into Chinese. I thanked her and thought nothing more of it until I discovered a few weeks later that she had recommended me to a colleague of hers who happened to be looking for a Chinese < > English interpreter with Spanish in their combination!

I’ve also been doing translations into Chinese and English. I am currently working on three short stories by an Argentine writer, and I translate less exciting things like contracts and investment pitches. I passed the freelance translation test for the World Bank and the International Monetary Fund in Chinese < > English, and yesterday I received news that I was awarded the second prize in the 14th UN’s St. Jerome Translation Contest for into Chinese.

As the freelancing workload comes with a lot of ebb and flow (more ebb than flow since I’m new to the market here), I’ve also been volunteering as a humanitarian translator, attending lectures and conferences, reading and exploring New York City – one of my favorite cities!

  • Why did you choose to take the internship at the UN given that it is unpaid?  How do you think it has or will benefit your career?

I chose the internship because it would help me prepare for the UN Chinese interpretation exam at that time, as one of my long-term dreams is to become a UN interpreter (the reason why I came to MIIS). Even though I did not pass and I’ve realized during my time at MIIS that it may take years before I achieve that dream (hence the importance of diversification and flexibility), I was thankful for the opportunity to learn about the UN and the challenges involved in doing T&I work there. During my internship, I translated speeches given at the Security Council and General Assembly, Main Committee meeting summary records, and worked on bi-text realignment (to improve translation memory), terminology management and proofreading. All my translations were reviewed by senior translators and there were one-on-one opportunities to discuss certain challenges, techniques and solutions, which was one of the most rewarding parts of the experience. It had always struck me how unusual “UNese” was, but it wasn’t until my time there that I learned about the multitude of challenges involved, and how a seemingly unnatural choice was usually the result of difficult negotiations where linguistic and political concerns all come into play. I learned a tiny bit about translating in a concise, precise and politically sensitive manner. It was a humbling experience, and it has given me a new appreciation for our profession.

I took this opportunity knowing that it would not come again (only available to students and recent graduates). I was lucky to have very understanding supervisors who allowed me to take on freelance assignments as long as I turned in my work on time, and former professors and fellow MIIS alums who kindly recommended me for assignments, without which I would not have been able to survive financially. A big thank-you to the MIIS Mafia!

  • Knowing what you know now from a career management perspective, what words of wisdom would you share with those MIIS students who are graduating in May 2019?

Speaking from personal experience: you may not get what you strive for on your first try, but do not lose heart. Be patient, positive and persistent. Make sure to always deliver top-quality work; this is the best marketing trick out there. Keep on learning and growing through every experience that comes your way. Once I was at an assignment when a concept came up that was not in the reference materials. I would not have been able to understand it and express it on the fly had I not read it in a book on my hour-long commute to my internship! Keep your eyes peeled, ears pricked and mind open. You will get from your career what you put into it. If you are intellectually insatiable and love helping people understand each other, you will love this profession!

  • What are your next steps career-wise? 

I am moving back to Beijing in the summer to freelance full-time as an interpreter, barring any unforeseen circumstances. Having lived abroad for 12 years now, this is exciting and scary, but I’m ready to embrace the challenge and join forces with the MIIS Mafia in China.