AI and the translation industry – the 2026 Israel Translators Association Conference

 

[AI image]

“People out of my industry love to tell me how AI has eliminated my profession…” one lecturer said. Today, it seems that the most commonly known “fact” about being a translator is that it is no longer necessary. After three days of lectures at the 2026 ITA conference, it is possible to clarify that the reports of our death have been greatly exaggerated. Granted, AI is transforming the process and business of translation but that statement applies to numerous professions. For three days, the attendees gain a wide-angle perspective not only on the potential impact of AI but also how to use it for their own advantage. The quality of these lectures was exceptionally high but certain speakers stood out, in my opinion, in terms of the practicality of their approach. It should also be noted that the presentations as a group provided a roadmap or at least a guiding flashlight of how to proceed into the uncertain future.

While the topic, AI and translators, was narrow, the approach was all-encompassing. Some lecturers focused on the actual methods of using AI, showing prompts and approaches in various AI programs,  while others presented their method of using it in certain fields, including technical and creative writing. Two translation teachers detailed how they instruct their students how to use AI properly in order to attain the best possible translation. Another series of lectures dealt with the ethics and security problems posed by AI, an important factor for many translators. Many speakers discussed the need for translators to change their role from converters of languages to language/culture experts. Finally, a few, including myself, had the chutzpah to talk about non-AI translation matters, just to relieve the AI-created tension if you will. The conference provided a multi-perspective survey of the AI-translation scene.

Having attended many conferences, I can say that the quality of the lecturers and lectures was outstanding. Three presentations stand out, one for each day. Naomi Shenkar in her presentation entitled “ Prompt Engineering for Translation” was not only organized but provided a clear and simple approach to writing prompts and efficiently achieving the most relevant results. I plan to put her method to the test very soon. The star of the second day was Danny Verbov with this presentation “Your Greatest Marketing Tool is Right Under Your Nose!” Not only did he remind everybody that it is important to market yourself if you want business, regardless of your knowledge of AI, and how to do so efficiently and effectively, but he also had, in my estimation, the most effective and humorous PowerPoint slides. His pictures were worth a thousand words. They were pure added value to his well-executed lecture. Finally, on the last day, Orly Kyram gave a workshop on “Getting to know Gemini and NotebookLM In Depth”, a valuable hands-on experience for those lacking the courage and faith to learn by trial and error. As I said, the other lecturers were also quite effective and relevant. I am just presenting my personal three favorites.

It may be difficult to remember any specific points after three days of AI overdosing but three messages are clear. A translator that fails to apply AI where applicable will be replaced by one that does. That said, effective AI requires well-thought-out prompts and human editing. A simple command does not produce a professional translation. Finally, AI does not reduce the requirements of the profession. Translators still need to know how to transmit the message, linguistic and cultural, of the source language into the target language and convince customers that language makes a difference. AI, just like all previous machine translation technologies, is merely a tool, not a replacement for human thinking. Alas, it will take time before translation buyers realize that AI “good enough” is not good enough. In the meantime, translators are not in danger of extinction.

As a final point, many young professionals, including translators, do not see the value in professional organizations. The ITA once again organized and brought together a large and varied group of excellent professionals, who enriched the perspective of all the attendees. This event alone justified the membership cost. Add the energy and synergy of group interaction. I strongly recommend the benefits of joining professional associations. At a minimum, you can hear colleagues who are still alive and well in your profession and learn from them. Next year in Tel Aviv.

When the going gets tough… - A call to translators and other freelancers to join associations

 

In November and December, many professional associations, including those of translators, begin their annual membership campaigns. In recent years, the results have been disheartening to one degree or another. At least among translators, fewer and fewer freelancers choose to join even their national association, let alone a foreign-based organization. The reasons for this decline are both technical, economic and social. Yet, joining a national professional association is, in fact, a way to address those economic and social issues as well as to maintain creativity in the long term. All freelancers should seek that connection for both their personal benefit and the collective good.

Membership in professional associations is declining in most fields due to changes in technology, economy and social structure. AI is the mammoth in the China shop, reshaping the entire landscape of how businesses, big and small, work. Clearly, most freelance translators do not have a high degree of certainty about their own future or the future of the profession in 5-10 years. At the same time, rates continue to decline or remain static while many translators are experiencing a decrease in volume, a deadly combination. Paying association fees seems an ill-justified luxury. On a more general scale, many younger professionals grew up with the Internet and consider it their community, convenient and undemanding. The time and energy demands of physical participation, even by Zoom, feel uncomfortable. It is far easier and often more than sufficient in the short term to use one’s Internet persona and make connections. Thus, many newer and even not-so-new translators choose to avoid professional membership.

However, conversely, joining a professional association is an effective response to those issues. First, as nobody seems to understand exactly when and how to use AI, learning from the experience of others in the same position provides a wide-angle and more comprehensive picture of the situation at any given time. A word to the wise is sufficient. Furthermore, even more than ever, associations bring work. More and more buyers, struggling to identify worthy service suppliers in the chaos of the Internet, consult professional associations, seeking some kind of certification or recognition to help them in their choice of supplier. Personally, most of my new customers have found me on association lists. Furthermore, the official recognition allows freelancers to charge higher rates, increasing income. No less importantly, in the long term, the major challenge for any freelancer is to maintain enthusiasm and flexibility. Even if a participant at a conference technically learns nothing new, they leave the event with renewed energy, the result of being around so many talented people. Thus, professional associations actually help freelancers deal with technology, find customers and grow professionally.

Therefore, I believe that when the going gets tough, the tough get joining, gathering the strength, business and knowledge in uncertain times. There is strength and synergy in numbers.  I strongly recommend joining relevant associations at all levels, local, national and foreign, and physically participating in their events.

My robotic friend? – My (belated) foray into Machine Translation POst Editing (MTPE)

 

As I wrote a few weeks ago, I have made the strategic decision to focus on my competitive advantage – Hebrew to English legal translation. The practical significance of that decision is that I must maximize its potential. Thus, this last week I took on a project involving editing machine translation of an insurance contract. I had previously avoided such projects due to their idiot-savant nature. The project confirmed many of my concerns but, in contrast, demonstrated the advantages of working on machine translation. I discovered that they could indeed be satisfying, both financially and emotionally.

In explanation of the term, machine translation does not necessarily refer to AI engines such as ChatGPT and may include older methods such as Google Translate. The term machine translation designates the initial use of a digital linguistic tool that translates the source text by applying similar patterns in a database, whether vetted and closed or open, Internet-based. Machine translation has existed for several decades, initially through translation memories developed by translators, agencies and companies and expanding to more sophisticated ones based on neural networks. The European Community has developed one of the most specific and sophisticated ones based on previous translations of all EU laws into all of the languages of the community. The open machine translations, notably Google Translate and AI, use statistical probability to choose the most probable translation available on the Internet. The quality of machine translation varies depending on the algorithm, language combinations and sources.

The resulting translation generally resembles one produced by an idiot-savant, which requires neither pure translation nor pure editing. To explain, if a human produces a poor text, it is far more economical in time and energy to retranslate from scratch. Simply put, the editor does not trust anything the original translator did. On the other hand, an editor, identifying an excellent translation, trusts the resulting text in terms of content and merely makes tweaks to improve the language. Furthermore, the editor learns to find a pattern of these mistakes and focus on them. In any case, two pairs of eyes are always better than one, regardless of the skill level. By contrast, machine translation, in my limited experience, produces highly uneven and unpredictable results. One sentence can be perfect, even better than one the editor could write. The next one can be a complete disaster and require complete rewriting. Even more difficult, a given translation may appear correct but closer analysis shows small but significant errors. It requires careful attention to identify those issues. Thus, machine translation is not consistent in quality nor are its mistakes predictable.

In the text I did, the translation engine, DeepL, produced a mixed bag. On the one hand, there were very few content mistakes, i.e., a reader could correctly understand the meaning of the vast majority of the provisions, albeit with a bit of effort and a few terminology errors. On the other hand, it was clear that a human translator had not produced the text. Here is a partial list of the error types:

1.     Articles (he vs. it)

2.    Modals (misuse of “shall” to indicate future instead of legal obligation)

3.    Literal translation of phrases (has the right to instead of may)

4.    Inconsistent capitalization (company and Company)

5.    Translation of the name of the Company

6.    Keeping sentence in the passive (The premium will be paid… vs the Policyholder must pay……

7.    Misplaced adjective (the benefits retained vs the retained benefits)

Thus, the machine translation, while accurate, was not correct.

Upon completion of the project, I decided that I would take on more such projects. Granted, it required great attention, with many breaks, to catch the issues and improve the text. However, the original text was better in some ways than that produced by far too many human translators. Moreover, as I knew that no human was responsible for it, I did not get annoyed. Since I had priced the project by projected time after viewing the translation beforehand (which turned out to be fairly accurate) and offered two different quotes, light and heavy editing, the compensation was more than acceptable. Most importantly, the final text read well, always a satisfying result. Thus, I will now take on more such projects. Maybe robots could be our friends.

Rebranding or nostalgia ain’t what it used to be

 

This last week, linguists celebrated International Translation Day. Many translator organizations and sites marked the occasion, notably Proz.com, which featured two days of lectures and discussions on the state of the profession. Of course, the speakers mentioned AI numerous times, often in the context of how it impacts the profession. Most importantly, the various speakers analyzed the different ways that translators can continue to make a living given an uncertain future that will definitely include AI. One sentence struck a strong chord: whatever you do, do what you love because your passion affects the quality, which is the most important advantage human translators can have over AI. Furthermore, one lecturer noted there will always be a need for expert translators in specialist fields even with improved AI. In that light, I understand that I need to react to the changes in the market in my over 22 years of translation before it is too late. Unfortunately, I do not receive much pleasure when editing or using AI. Thus, I have decided to embrace my experience, drop my other areas of translation and specialize in one field, specifically Hebrew to English legal translation, as it provides the base for my future in all respects.

When I first started translation in 2004, I knew little of my skills or the translation world and chose to cast a wide net. I started my journey by preparing an inventory of my knowledge, specifically four languages, specifically English, Hebrew, French and Russian, and two areas of knowledge, law and finance. Small translation agencies dominated the market at the time. Thus, it seemed logical to create a multilingual brand with several specializations to catch the most fish. I did not know enough to identify any specific target markets and thus created, in effect, a more general brand.

The market had changed radically since then, primarily due to technology and conglomeration. AI and machine translation of all types have eliminated many market niches, including email and personal translation. At the same time, the same technology has created a strong demand for machine translation post editing (MTPE). On an organizational level, large international corporations have gobbled up one small agency after another, creating large volume, low-cost translation venues at the expense of translator rates. At the same time, it should be noted that many well-paying niches not only exist but are thriving, notably legal, medical, marketing and transcreation, which provide ample opportunity for qualified linguists.

As I considered my future (Yom Kippur is an ideal day for doing that), I finally understood that my initial approach, however relevant it was at the time, is no longer effective. I am now choosing to formally embrace the field I enjoy the most, work most efficiently and am most proficient at [Winston Churchill said it was proper to end a sentence with a preposition]. I will solely focus on Hebrew- to-English legal translation, which is mainly what I have been doing for some 10 years now. I have studied legal writing, especially Plain English. Moreover, I am not only quite efficient in translating and editing legal translation but am more proficient at them than many other translators. Thus, as far as anybody can foresee the future, I feel my career has a solid basis.

Giving up the past is never easy. For that reason, people hold on to objects that no longer have any practical value. I still enjoy reading and speaking French. As for Russian, it is quite a useful language in Israel. I may choose to take on a small appropriate task in those languages. However, there is no feeling like doing a task very well especially if it is something that you enjoy. As for the price of rebranding, it requires redoing my marketing approach but better late than never. It may be fun to look back from time to time but success requires forward-looking.

AI and the future of freelance translating – a perspective

 

Freelance translators, like many other professionals, see dark clouds. The media feeds stories on the ever-improving ability of AI to translate. Strangers innocently ask why anybody needs translators anymore. Customers and income decrease month to month. It is all quite depressing but not necessarily a full or accurate picture in the long term. On the contrary, paid translation needs are actually expanding. Moreover, the market niches that AI is destroying have been in decline for over a decade due to technological changes. In practice, AI changes the translation business but not only does it not eliminate freelance business but can even provide an opportunity to expand. It is reasonable to be cautiously optimistic despite all the apparent omens.

In terms of current trends for language service providers, which includes both agencies and freelancers, the future seems quite optimistic. Based on the total volume of the worldwide agencies, demand for linguistic services continues to increase steadily. Experts predict that the value of these services will increase approximately 28% from 2024 to 2027 to around 90 billion USD. World trade and the needs of international commerce will continue to feed the demand. To be fair, international agencies are taking a lion’s share of business with freelancers struggling with downward pressure on their rates. B2B business, without agencies, requires more marketing effort, skill and confidence, which many freelancers lack. Yet, in practice, there is a steady demand for translators.

It is important to note that translation technology, which includes but is not limited to AI, shapes which niches will remain and even expand and which ones will decline and disappear. For ten years, machine translation of all types has automated the translation process. Computer Assisted Translation (CAT) and translation memory began defining the work process over 15 years ago. Machine translation, most notably Google Translation, has made simple translation accessible and free to the average person for almost 20 years. More specialized translation memories, in particular neural translation in recent years, make it possible to effectively translate large masses of specialized legal and other material in a short time. There is less and less work available for a general translator because of the plethora of no-cost and sufficiently effective alternatives. By contrast, these machine translations, including AI, struggle to produce effective results when the message goes beyond mere understanding but requires precision or a human touch.  Some fields suffering from a lack of proficient human translators include medical, marketing, legal and technical translation. Furthermore, the need for official certification of government documents for court and bureaucratic purposes creates a steady market for certified translators of all types. Specialists can find lucrative niches.

The various language technologies have changed the whole panorama of translation in terms of methods and tasks. The use of CAT tools is a requirement for many projects and has significantly increased productivity and shaped its rates. Machine translation serves as a basis for many initial drafts, either in terms of suggestions or complete translation. AI can instantly produce a large-scale translation, albeit of highly uneven quality. Thus, the translator’s work may involve editing machine translation, actual translation or both. Clearly, not every freelancer wishes to be involved in editing but those that accept it and do it efficiently and effectively are in demand. By contrast, those freelancers that completely reject technology find their market shrinking. The name of the game is constant adaptation.

Thus, it is clear that translation is not only not a dying profession but instead one with a future. Technology will shape its future, as it has done in its past and present. Specialized and flexible translators can find an opportunity to make a living. The most difficult period is the transition during which the advantages and limitations of each new digital tool emerge and define the market. AI is not the end of human translators just as Google Translate and its cousins were not. They merely shaped the profession. It is most probable that for the foreseeable future human translators will continue to handle those tasks where it is important to fully convey the meaning of one language in another language and where approximation is not sufficient as well as ensure that machine translation does not create unnecessary or even dangerous mistranslations. Many current AI uses will return to human translation as issues arise from AI translation.  I am cautiously optimistic about the future of translation despite AI.

Text-book perfection – in search of a QA panacea for revising long texts

 

Long translations pose special problems for translators. The intensive process involved in translating a long legal document or multipage text leaves little time and freshness for the no-less-crucial process of QA. Simply put, by the time the hard-pressed translator gets to the editing stage, the text is already embedded in the mind as basically acceptable, limiting the translator’s ability to identify syntactic errors. This problem is not new, with translators having long used a set of tools, some old and some new, to overcome it to varying effectiveness. I will discuss some traditional QA methods, some recently developed ones and my experience with Grammarly. Whatever the individual choice of tools, professional translators and writers must employ them to properly check their work.

To illuminate the problem, the act of translating a long text, whether a legal document, a set of technical instructions or personal journal, involves multiple hours and multiple readings. Working from first draft to non-QAed finalized version may require the linguist to read through the original and source four or more times. Aside from the time invested, the creation process creates a sound and vision in the mind, which become de facto acceptable. Professionals are aware that many areas for correction and improvement lurk in the text and strive to find them in the jungle of text. However, the longer the text, the more difficult it is to locate them. The moment of truth is when the customer or translation agency editor sends back a document riddled with red marks, a truly unpleasant and often embarrassing experience. The question that most translators and editors ask is “How did I miss that?”. It often was not from lack of effort but  due to the tools they used.

The tools of translators and other linguists at minimum include
Word “spellcheck” (F7), printing and reading and use of outside editors. The Spellcheck function in Word identifies the most basic of errors with the failure to use it bordering on professional incompetence. A more comprehensive manner of editing is to print and read a text. For some reason, a text appears differently on paper than on a screen and, thus, fresher to the eyes. I personally read the text backward, i.e., from the last paragraph to the first paragraph, in order to render the document even more different and prevent me from going into “read a story” mode. Ideally, all linguists would employ outside editors, a fresh pair of eyes, to review any resulting text. In practice, the time and cost factors limit this practice from becoming standard except in literary translation. Translation agencies employ editors, especially those applying the various ISO standards. As I wrote, it is unpleasant to receive red-dotted corrections even if such a result does not affect future work. As for direct customers, the linguist is solely responsible but most technical translators do not use outside editors as a standard practice.

Two more modern and comprehensive methods are text-to-speech and AI. The text-to-speech function in Word is a simple manner of reviewing a document using a completely different method. Instead of having the eyes read a given sentence for the umpteenth time, the ears filter the sentence. Thus, poor-sounding phrases and structure immediately hit the linguistic warning bells and cause the translator or editor to reconsider the wording. It is a tool that I may try in the future. Another trendier tool is AI editing. Using one of many applications, it is possible to have AI analyze a document, identify possible errors and suggest solutions within seconds. On the surface level, it sounds quite magical, even ideal. My serious issues with this method are the lack of confidentiality, the actual process and results. First, as of today, in most cases, once a text, even without any identifying names, is posted to AI, it enters the public realm, which may be a breach of the confidentiality conditions. Some writers may be risking their copyright privilege if they use AI. Furthermore, I personally find the process of writing prompts to define and limit the range of errors as well as desired style I seek to be overcomplicated. Even when a person overcomes that difficulty, the suggested changes represent some collective image of the ideal such text, much of which is not relevant objectively and/or subjectively. In other words, the benefits, i.e., AI’s comprehensive and standardized approach, do not justify the risks, i.e., the loss of confidentiality and hassle of writing prompts. Thus, I do not use text-to-speech or AI.

However, recently faced with specific challenges, I applied Grammarly to two especially long and complicated texts and found the results positive on the balance. One text was a 20,000-word personal journal while the other was a 5000-word contract. As time and energy were short, I sought a tool that would identify phrasing errors and improve my translation in my text without risking confidentiality. I used Grammarly, an application that does involve a user fee. The process was simple, merely uploading or dragging the text into the editing box. I then selected the type of text, e.g. informal or formal. The result was a long list of possible errors and suggestions for improvement. To give a perspective, the program created 500 comments for a 5,000-word text. The vast majority, around 80%, were false positive either because of context or personal choice. For example, the program was not familiar with legal language and questioned many acceptable terms. In terms of subjective choices, I personally do not apply the Oxford comma, the comma before the word and, nor place a comma before the word but. Thus, I ignored those comments. On the positive side, it did identify many passive sentences that I could render in the active voice. This comment was of great value in the personal document but less so in the legal document even if I  try to limit use of passive structure in legal documents. Grammarly also identified sentences that could be joined or split, suggestions that I adopted several times. Overall, review of these long texts using the program involved several hours but produced better results in less time as compared to rereading.

It is clear that linguists, especially translators, must provide high quality products, meaning documents as clean of errors as possible, especially in the light of AI-created documents. The longer the document, the more difficulty that task is. Thus, translators and writers must use a wide variety of tools to achieve the required quality. I intend to use Grammarly on longer texts where a lack of time and freshness may harm the quality of revisions. While linguists can choose their preferred tools, it is clear that no specific method is a complete panacea.

Bonne route – Process, pleasure and AI

 

[Painting by Dina Levin]

In one of La Fontaine’s fables, a pig, sheep and goat are on a wagon on their way to the market. The pig squeals in fear (justified in the case) but the sheep and goat prefer to enjoy the view. I cannot say who is more correct or whether this fable applies to AI. However, after listening to my engineering students make oral presentations about processes pre- and post-AI, I definitely understand that there is a certain pleasure in the actual process independent of the result as I will demonstrate with three examples provided by my very talented engineering students.

Among the many lectures were presentations on the revolution in  travel planning, translation and image creation. Specifically, before AI, travel planning necessarily involved either consulting a travel agent or spending hours finding appropriate flights, assessing hotels and investigating potential tourist sights. With AI, a series of prompts with follow up questions can theoretically create a complete vacation plan in minutes. Likewise, as I know too well, human translation involves a significant investment of time and effort to reproduce a given text into another language. With AI, this same process can take less than a minute and involves almost no effort at all, leaving plenty of time and energy to edit and improve the created text. Even more extreme, AI makes it possible for the artistically-limited to create any image, real or imagery, without any skill  in graphic arts or software. AI can take over the process of creation, benefiting people by saving time and effort.

Granted, at least at this point, AI often produces a flawed product, sometimes to the point of non-relevancy. For example, the AI engines I tried for finding flights failed to identify the most convenient flight of a given route (Tel Aviv, Israel to Portland, Oregon) , which I was able to find. It may be a matter of the nature of the prompts or the type of AI but the results do not seem sufficiently exhaustive. In language, AI translations of specialized texts exhibit far too many serious terminology and syntax issues. This tendency means that a skilled human translator must invest time and energy in reviewing the text before the text is relevant. AI images quite often look artificial, which can be a detrimental feature in many of their uses, especially commercial. Furthermore, humans creates images that are much more individual and unique. Thus, AI is not yet capable of  fully replacing the process of human creation.

For me, the greatest issue is that I enjoy the challenge of creation both despite and because of its challenges and investment. It is strange but one of the greatest pleasures of traveling is planning it, including finding the “best” flight. My father took great pleasure in that art as do I. It is my trip as I have invested in it. Similarly, translation is an act of writing and creation just as much as writing the original version. The transformation of a text from one language to another can be challenging but that aspect is precisely what I seek, at least up to a certain degree. It is the pleasure of learning and testing oneself. As for pictures, I find an artist’s rendition of a scene in pencil, oil, watercolor or even using a digital photograph is far more impressive than any AI image. The reasons may be that I have no talent in that direction and find the process magic or that I seek the privilege of seeing the scene exactly how the artists viewed it. Human creation has a far greater impact on me regardless of whether the creator is someone else or myself.

It is clear that there are solid economic reasons for adopting AI processes whether on an industrial or smaller scale. However, as a matter of personal taste, I tend to focus on the experience of the process more the result. In fact, I wish myself and others what Serge Reggiani sang in “Ma fille” (admittedly in another context): “Bonne route” – a good journey.

AI and I – an attempt at perspective

 

I admit to feeling somewhat hostile about the idea of using AI in my work as a professional translator.Thus, I felt (and still feel) a need to ascertain whether my internal resistance is stubbornness or intuition, two similar but not identical impulses. Consequently, I invested the time to listen to Doron’s Tzur excellent 2-hour presentation to the Israel Translators Association on March 26, 2025 on the subject of AI for translators. He gave an excellent introduction to the approach of AI as well as its practical use in translation, providing examples using several different AI applications. Granted, this presenting does not make an expert on the subject but the lecture did provide me with some updated data. I thus feel more at ease discussing my perspective. I now understand that an AI-based translation method does not fit me in terms of task/time allocation, the resulting standard and the produced style. Yet, while I do not see AI as a practical tool in the initial translation phase, I definitely can see its value in the editing stage, when it is possible.  In short, my personal answer is: “No, but”.

One of the Doron’s first points is that AI can and does change the time relationship between translation and QA, which include both finding errors and improving style. Specifically, he noted that the initial translation process, what he called the white paper stage, using AI takes minutes, if not less, allowing translators to focus their energy and skill and improving the text, rendering it both accurate and human. It should be noted that many translators, including myself, actually prefer the creative stage, the writing of the first draft, over the editing stage. An important passion in translation is the joy of playing with words, preferably in at least two languages. Thus, as demanding and time-consuming as translation can be, the work is fascinating and satisfying. By contrast, editing is a technical skill requiring great attention to detail and great discipline. Consequently, as I have no great desire to specialize in editing, I prefer the traditional method of translation, i.e., without AI.

Another point made by Doron is that AI is becoming or has become the new standard. He noted that it is possible to produce a workable translation of even long texts in hours, not days. I certainly do not dispute his assessment of time requirements or creation of a standard. However, I do challenge the worthiness of the standard. Written communication, especially in English, necessarily involves polishing and repolishing. Each QA session reveals more underlying issues, theoretically infinite but in practice limited by delivery deadlines. Clearly, any translation produced and edited in three hours lacks that polish if even it suffers from no concrete language error. Thus, it is possible to produced rushed translation but the issue is to what standard.  I am aware that, historically, people have come to accept lower quality standards, e.g. cars and clothes, but I find that disturbing.

Finally, AI, because it is based on statistics, not intelligence (Doron’s words), produces a clear but somehow flawed text based. To paraphrase Doron, average is never good as the 50% of the other texts are better.  The actual level of finishing depends on the skill and knowledge of the editor, many of whom are not even native speakers. Consequently, the AI-produced and human-edited translation often is correct but off, like a fluent but non-native speaker telling a story. Everything is clear but a real person would not write that. For many purposes, this artificialness is not an issue, in particular when a person only requires the translation to ascertain the main idea or find a detail. However, if the writer wishes to move the reader to buy, be inspired or any other action, this dissonance ruins the effect. People believe writers and speakers because they are authentic even if their facts are not quite accurate. Effective written communication must reflect the writer’s voice, not the statistical average. Therefore, I feel that using an AI-produced translation does not serve the needs of most if not all my customers’ needs.

One of the most attractive features of AI was its editing capacity. The ability of AI to identify errors of all types, including context-based spelling errors on some applications, is highly useful and a significant improvement on Word’s Spellcheck and even Grammarly, to name a few non-AI applications. However, to use these AI-tools efficiently requires consistent effort and time investment in attaining the computer skills and keep up with the weekly changes and newest versions. Moreover, translators cannot upload many legal, commercial and medical documents  due to confidentiality issues. I would love to upload the first draft 18,000 words I am working onto AI but will not do so because of the fear of it entering the public realm. Finally, it should be noted that most older people and quite a few younger people are not native to technology.  Yet, for many translators, using AI for editing makes sense both in terms of effectiveness and economics.

If I view the translation economic equation as time/effort as compared to income, at this moment at least, I feel that it is correct decision for me is to ignore AI but to keep an eye on it. AI is not the end of translation just as Computer Aided Translation and Google translations did not destroy the profession. Clearly, AI will change the industry but in what manner and which degree, nobody can say. It remains for each translator, or any other professional for that matter, to examine and decide, as Kirstie and Phil would say, to love it or leave it. I am leaving it for the moment.

A catfish perspective – understanding bottom feeders in the translation market

 

[catfish]

“The agency offered three cents a word! How shameful! Even worse, there are translators that will agree to it!” Almost every experienced and not a few not-so-experienced translators have expressed that anger and probably quite often. The existence of the rock-bottom market creates the hostile angry thoughts that high street stores have in reaction to a Walmart branch. This low-price niche seems an insult, if not a threat, to the profession. However, putting emotion side, there are solid, if not always justifiable, reasons, why certain agencies offer so little and certain translators are willing to take those offers. In practice, the “high street” translator can and should ignore this market as it does not actually pose an actual threat.

There is an economic basis for agencies offering low rates, whether it is type and location of their customers, their business location, their marketing limitations or their business strategy. Many agencies, especially small ones outside of the expensive European/US markets, work with customers that have low demands in terms of quality and even lower budgets in terms of their ability to pay for translation. A classic example is Russia, where traditionally business used Russian native speakers to translate into English and, in many cases, t at local rates. Furthermore, for agencies working in countries with low-costs, notably in many parts of India and China, agencies earn reasonable profit even if they do not add excessive profit in the price-to-customer. A far more common cause of such rates is the inability of an agency to negotiate higher rates. For example, in Israel, some agencies succeed in attaining much higher rates than others even if they work the same market. Finally, of growing importance, worldwide LSPs (Language Service Providers), such as RSW and TransPerfect, use volume to cover their expenses and make profits, with their revenue reaching very high levels. Of course, some agencies do offer low rates to translators but charge high rates to the customers, earning disproportionally high profits, but this is not always the case. Thus, many agencies often offer low rates for legitimate business reasons.

Many translators often accept these rates for legitimate business reasons as well as ignorance First, newcomers to the professions often treat these low-paying jobs as a practical way to gain experience. If translation is a second income, the amounts they earn, however low, may provide a significant boost to their income, especially in poorer countries. As a primary income, the cost of living varies significantly between country to country, meaning that these rates may be higher than other available income options where they live. Sadly, many translators have no margin for slow months and must take on any relevant job.  Of course, many translators taking on these jobs are unaware that they can attain higher rates through active marketing in their country or abroad. They erroneously believe that these low rates are the market. Still, one person's "shocking rates" is another's way out of poverty.

If, as in all markets, the low budget niche exists and may be expanding, experience translators need to stop wasting energy on decrying it and focus on the better-paying niches. First, low-cost translating has always existed to one extent or another with Google Translate, machine translation and AI expanding customer options. There is no point in complaining about the rain. That said, many specialist niches not only involve deep-pocketed payers but also require high quality translation. Such niches include the medical, legal and financial fields. Another strategy is to leverage AI in translation and/or administrative tasks to increase productivity, thus creating more opportunity for high income. Translators that are so interested have a wide choice of webinars and methods. In the long term, it is possible that AI will not be able to provide the quality required by many translation buyers, causing disappointment and leading these customers to return to reliable human translators, this time with a better understanding of the cost/quality payoff. Finally, as there is no translation market in the sense that translation buyers and providers lack convenient and complete access to all offers, translators have to seek out those customers that are willing to pay the rates they wish to receive even if they are higher than the budget ones too often seen in forums. Many customers still value quality and reliability. It is a matter of finding them. That is a far better use of one’s time and energy.

Catfish are a very successful species of bottom feeders. They may look ugly (unless you are fond of long fish whiskers) but not only do they thrive, they serve an important purpose in the biosystem. Likewise, inexpensive rates interest a wide community of translation buyers and providers. At the same time, numerous companies in many industries worldwide need and demand high quality translators and are willing to pay for it. It takes effort and knowledge to reach them but they are a better option for many experienced translators. As Voltaire would say, cultivate your garden.

The ITA 2025 Conference – a multi-perspective view of the translator/interpreter client challenge

 

Last week, the Israel Translators Association (ITA) held its 2025 conference in Tel Aviv with the theme being the customer challenge, or more specifically how find and retain customers in a changing market. The two-day event was packed with lectures, each offering a different point of view and series of suggestion on how to create and maintain a successful language provider business. The speakers ranged from experienced translators and interpreters in Israel and abroad to professional marketers. Of course, some, but far from all, of the presenters discussed the application of AI with an emphasis on using it for administrative and creative tasks. Overall, it was an enriching and enjoyable experience.

Over the two days, many experienced linguists shared their wisdom on how to seek new customers in a market in which some niches are shrinking. One important theme was the necessity for active steps to remain relevant. Hadassah Levy noted in her presentation “Marketing Your Translation Business in 10 Minutes a Day” that creating content and then automating their publication renders digital marketing much more time-efficient in the long term and creates a vital effective online presence. Helen Baker discussed a weekly time investment in business networking groups as a means of building productive business connections. Finally, Tess Whitty discussed the attaining additional skills, in her case SEO, to add value to her services and income to her business. Other relevant lectures include Chiara Vecchi on her effective reaction to reduced business volume, Miriam Blum on the importance of the ITA “Recognized Translation” and Mikhal Heffer on working with agencies. I contributed a presentation on how to prepare a professional presentation to clients and colleagues. Overall, the lectures provided a bounty of ideas.

The conference also featured presentations by professional marketers. Dotan Grably provided a strong theoretical and practical approach to the general principle of how to attract customers. He focused on two concepts and explained how to apply them in practice. Yarden Lerer went into great detail on content creation and its effect use for marketing. Both of these presenters provided great food for thought.

Of course, as in any professional conference today, AI was on the agenda. Aliza Berger showed and compared translation of a short legal title using various AI engines as well as human translation. Uriel Shuraki discussed the characteristics of several AI applications. Beyond the use of AI as a translation tool, Alfonso González Bartolessis and Dominique Bohbot related AI to business management and its benefits in increasing efficiency.  These and other lectures helped reduce the “flight or fight” reaction to AI in many of the attendees.

To those presenters whose name I failed to mention or whose content I did not do justice, I apologize and remark that both space on this post and in my brain’s memory is limited. The two days were truly packed with information and ideas, the recipe for an ideal conference. Chapeau to the organizers, who organised the event. I strongly recommend any translator or interpreter that is feeling nervous about the market to attend such events. The meeting of minds and people opens up great opportunities because it provides a multi-perspective view of what is and what can be. I am looking forward to further events on the same subject as well as the conference next year.

Is 2025 a good time to become a translator – an auguring tale

 

[ruins of Greek temple]

Many linguists, young and old, are considering whether it is a good time to begin a translating career in 2025 with AI shaking the foundations of the linguistic world, among others. It is clear that nobody can see the future but in ancient Greece, there was a special group of priests, augurs, whose task was to answer vital questions about the future. The responses were often vague and sometimes not encouraging. For example,  the parents of Oedipus asked and didn’t enjoy the answer, i.e., that he would kill his father and marry his mother. (Apparently, they did occasionally get it right.) It is said that these priests would take these questions and go into a deep cave and then breath in radon gas or take a hallucinogen to sharpen their vision. As modern methods for predicting the future are no more effective than the old way, let’s imagine the answers a hesitant linguist would receive if s/he would ask the augurs whether to start a career in translating in 2025.

The first augur would enter the cave and become quite euphoric. He sees a future filled with work booked in advance for two weeks and a large positive balance in the bank account. His/her answer might be:

a.   I see endless growth in the language service sector.

b.   I see the world becoming more and more connected.

c.    I see masses of disappointed AI users seeking you.

In short, our augur with pink glasses would say: go study translation and start a business.

 

The second augur is a dourer type and had a bad morning. Upon entering the cave of seeing, his/her visions becomes dark, stating:

a.   I see AI taking over each and every sphere of translation.

b.   I see masses of translators slaving over machine-translation versions trying to justify their existence.

c.   I see translators joining the ranks of blacksmiths on the extinction list of professions in six years.

This bringer of dark omens would say: he who approaches the island of the Sirens [possibly the island of Capri] should not be surprised if his ship crashes into the rocks.

The third augur takes some natural version of Ritalin instead of the usual mushrooms and tries to analyze all of the facts. After a while (no computers at the time), a confusing set of statements would emerge:

a.   I see that AI is fundamentally shaking up the language service market, which was already being transformed by neural translation and other forms of machine translation.

b.   I cannot predict the long-term viability of AI translation, i.e., to quote a certain translator, whether people will learn to accept lower quality in exchange for lower price or return to human translators.

c.   I see that translators with the appropriate skills will find fruitful islands in the technological storm.

In short, this non-committal augur paints a foggy picture and tells the linguist: beware of the storm but listen to your heart. Prepare for but do not fear the future.

As an experienced translator and not a fortune teller, my “reading” is that the world will continue to need translators but their role and skills are changing, just as they it has in the past. What is constant is the need to attain skills beyond linguistic ones. These additional anchors include deep familiarity with a specific field of knowledge such as law or medicine, solid computer skills (including but not limited to AI), digital marketing experience and knowledge of business management. We all learn some of these skills “on the job” but just knowing two languages is not sufficient, especially now. The more skills a person has before starting, the greater chance of success there is.

As I look at the grounds of my Turkish coffee (as there are no augurs in my neck of the woods), I see a future with many shades of grey, with some intense black where the coffee grounds are thicker and off-white where the bottom of the cup  is visible. I imagine the augurs would give a similar answer with equal confidence. The one certainty is uncertainty. Physics even has a law for that. Thus, I would advise uncertain translators to follow their ambition if their heart says to become a translator but also their head by gaining expertise in some if not all of the required skills. Time will tell what will happen even if the augurs generally did not. Whatever the result, I hope the decisions of the these future translators augur well.

AI writing – fancy or highfalutin?

 

[rainbow over my parents' house]

I had the peculiar experience of seeing my parents’ house advertised for sale after my mother died. I have to admit that I found it difficult match the description of the property to the actual house. It read:

“Nestled within the Encino Hills, near Mulholland Dr, in the acclaimed Lanai Road Elementary school district, sits this charming mid-century 4 bedroom, 2 bath 2,202 sq. foot home ready for its new owner. Don't miss the chance to reimagine this nearly 16k lot surrounded by flourishing foliage and citrus. Enter through double doors into a foyer which connects to a spacious vaulted ceiling formal living room with a fireplace and adjoining dining area….”

In reality, it was an expanded but simple aging wooden house but clearly the AI-created description makes it seem far more attractive to buyers.

This personal example highlights the strength as well as the dangerous temptation of AI writing. On the one hand, it is an expert-system, creating a text that only highly experienced and talented copywriters can write. On the other hand, in many cases, the resulting text is not actually effective in communicating the message as many English speakers consider overly fancy language either exaggerated or intended to deceive.

To be clear, AI produces text according to the prompts that the writer enters. The parameters include, among other, level of vocabulary, purpose of the document and educational level of the reader. Thus, in theory, AI should be able to produce a text that is tailored for the intended goal. Accoridingly, the skill of the programmer has a dominant influence on the relevance of the text.

One of the major problems is that a significant percentage of those using AI to write their texts are not fully fluent in the language and often unaware of the nuances of communicative language. Thus, based the concept that more the better or, as in the case of writing, the higher, the better, users tends to aim to write highly sophisticated texts. The resulting copy thus chooses the elegant and indirect route instead of the simple and direct approach. For example, compare “visitors have the possibility of observing a myriad of animal species at the local zoological center” and “visitors can view a wide variety of animals at the zoo.” Clearly, the first shows a far richer level of vocabulary but many adults, even some native speakers, not to mention children, would struggle to understand the meaning or find it off-putting.

The cultural background affecting this reaction to high-level language partly stems from a preference in English for content over style. For many English speakers, using sophisticated language in terms of vocabulary and structure is viewed as an attempt to prove personal superiority or hide the truth. In simple terms, English speakers often expect to a person to say something directly and not decorate it. Americans in particular expect their leaders to “tell it like it is” and value that type of communication even if the form is rather simplistic, even crude. For example, many voters truly respect Trump because of his manner of answering questions but he is not the first president to be overly direct. Even modern legal language strives to be simple and direct and drop its pretensions as many modern scholars consider the use of legalese as an elitest and dangerous practice.  See my previous post.

This insistence on clarity at the price of elegance is contrast to the situation in many other countries and cultures. In France, for example, listeners are often quite willing to forgive a complete lack of content if the language is elegant enough. Almost all French politicians and even masters of ceremonies sound almost royal in their speech. It is hard to name one French president that was not an elegant speaker. Thus, AI creates more benefit in some languages than in others.

Thus, an AI user without the knowledge of when high-level language is appropriate can unintentionally create an artificial and/or ineffective text. People seeing a marketing text with such language know that it is not written by a human as almost no one can or wants to write in that style. Thus, the alien text only highlights the fact that they cannot write. Even worse, if the purpose of the copy was to sell or persuade, the AI-generated copy will tend to create distrust, the exact opposite.

To give a concert example of power of short direct speech, note that most Americans know by heart at least a part of Abrahams’ Lincoln’s Gettysburg address  (1863), which totals 272 words, while nobody remembers a single word from the preceding two-hour speech by Edward Everett. English speakers prefer, to paraphrase Lincoln, English “of the people, by the people, for the people.” It does not mean that that there is no place of AI texts. My parents’ house sold quite fast in fact. However, direct plain English, edited until it is clear and smooth, often produces better results. Simply put, highfalutin AI English is often not an appropriate manner of expression.

Talking about the elephant in the China shop – should translation buyers use AI/machine translation?

 

[elephant]

The most common question non-translators ask (in one form or another) after I say that I am a professional translator is whether anybody needs me anymore. Likewise, when translators gather, the hot topic is the impact of AI on the business in general and the person in specific. AI carries the image of a drum roller machine, flattening anything in its path and whose existence many prefer to ignore out of dread. Going beyond this fear, it is legitimate to consider the role of machine translation, whether of the simple Google translation, more complex neural network or Hogarthian ChatGPT type. More specifically, I will address the blunt question when a translation buyer should pay money and employ a human translator.

As a matter of introduction, each of the three main machine translations types in their various guises attain their translation results in slightly different ways. The simplest, Google Translation and its cousins, search for the most common translation of the term as it appears in bilingual texts in the Internet and any online glossaries. The results are free but not always very relevant for the context. Neural translation and other more specialized methods selectively pick corpuses, including approved high-level bilingual texts such as from the European Community or the UN, and search for terms based on the type of the texts, e.g. legal and financial. This data base is more precise but is time-consuming to build. However, the results are generally far more relevant Accordingly, this method often involves some buyer cost to cover the development costs. Finally, AI translation uses a probability algorithm based on a broad internet data base and uses prompts to fine tune the results. The costs vary on the engine. Accurate results are somewhat dependent on the ability of the person to write prompts and specify the desired result. Even in the best circumstances, AI results tend to be a bit idiot-savant, i.e., ranging from brilliant to imbecile.

Here are some pointers regarding the appropriate use of machine and human translators:

·   To state the obvious, there is no need to pay a human translator to translate most texts for private use. If the goal is to understand more or less the content of an email or website text, any of the three types of machine translation will produce a sufficiently clear result, albeit occasionally with amusing terminology errors.

·   For longer texts, when time is a premium, it is possible to use a neural network or ChatGPT to produce a reasonable translation for a small internal audience. The purpose of such translations is essentially to share information, reducing the impact of any inaccuracies.

·   For mass translations where the cost of human translation is prohibitive, such as in identifying the content of  a large volume of legal documents or producing descriptions for a multilanguage low-cost online site that does not have the profit margin to employ human translators, machine translation might be a solution although the poor quality of the less expensive options may negatively affect results.

·   For texts aimed to make an impression on the public, including marketing and menus, businesses should employ a human translation. In these cases, it is not sufficient to transmit the facts. There is a need to persuade and impress. The public often equates the care invested into the text with the care invested in the product. Seller, beware.

·   For texts with legal and medical consequences, among others, translation buyers should avoid using machine translation. The consequences of a poorly translated legal brief or medical device instruction manual far outweigh the cost of a proper technical translator.

·   In some cases, government authorities require human translation and a signed certificate of accuracy. They do not accept self or machine-made equivalents. In these cases, read the requirements very carefully. For more information on what exactly a certified translation is, see here.

In summary, if you desire more than to attain information, employ a human translator. The costs of the poor results will far exceed any savings from free or low-cost machine translation. In other words, to talk about the elephant that is machine-translation, it should not be let into a china shop of fragile words as it tends to be somewhat clumsy but it is acceptable to let it into the gym as long as you clean it up afterwards, no bull.