Insights, Machine Translation & AI

Translation Data Security: Is Your Confidential Content Safe?

Due to the fundamental role that data plays in supporting the ongoing digital transformation, entire systems could crumble in the event of security breaches. In fact, most of the CEOs who attended last year’s World Economic Forum insisted that data privacy and cybersecurity are currently more valuable to their organization’s success than ever. That is, without data security, governments and businesses are known to collapse.

The Costly Risk of Data Breaches

Take Translate.com, for example, a leading automated translation software that recently exposed highly confidential data to unauthorized users and lost public trust/confidence in their product. The company attracted users to their platforms with the promise of free translation services but ended up leaking sensitive corporate and personal user content. From passwords and contract information to outsourcing and employee dismissal data, users were counting millions in losses.
When IBM conducted a study in 2019 to determine the financial cost of data leakages, they concluded that America alone loses nearly $10 million every year even though the global average per country is no more than $5 million. Surprisingly, these costs have steadily increased over the last half a decade at an average annual rate of 12 percent. So if you think your company can continue to bury its head in the sand as you wait for this problem to simply go away, you are taking a shot in the dark. Fortunately, you’re not alone.
In 2019, Deloitte interviewed 500 managers to gauge their opinions about the importance of cybersecurity and what they were doing about it. The researchers reported that even though the study respondents acknowledged the contribution of data security to digital transformation, most of them do not prioritize privacy enough. A significant proportion of the executives confessed to allocating no more than 10 percent of their aggregate budgets to cybersecurity endeavors.

Best Practices for Data Security

To avoid security breaches when translating your confidential data, awareness of and investments in action against cybersecurity threats should be the cornerstone of your digital transformation strategy.

1. Monitor and control access to computers

All the measures you take to keep translation data secure would be pointless if you forgot to password-protect your personal and company computers. When you encrypt your hard drives and backup drives, only authorized personnel will be able to access sensitive information, even if the machines are stolen.

Another way to limit access to your computers is through well-known, up-to-date antivirus and firewall protection software. These are some of the typical hackers’ greatest pet peeves because they can detect malicious network activity and lock specific users out of the system.

2. Beware of publicly available machine translation tools

Online automated translation software like Google Translate might be alluring because they help reduce operational costs, but they can also introduce your company to unnecessary risks — as The Nomura Group, a Japan-based bank, recently discovered. The bank trusted Google to keep its company emails secure only to be embarrassed when the documents ended up in the wrong hands. Once their confidential translation data was leaked online, they had no means of deleting it from the Internet. What’s worse, they discovered that Google and its ilk have the authority to harvest such data and use it however they see fit. If they had read Google’s terms and policies before agreeing to the conditions, they wouldn’t have become a laughing stock.

3. Avoid free cloud services and public Wi-Fi networks

Just like online machine translation tools, free cloud services, and public Wi-Fi promise to lower your operational costs but end up introducing you to unnecessary risks. Did you know that hackers can easily intercept your translation data while it’s in transit or stored on shared cloud servers? So the next time you want to share sensitive company information with your translators, don’t use Coffee Lab’s public Wi-Fi. If you must use a shared network to transfer confidential data, you can at least install a reputable VPN to hide your user activity.

4. Can you trust your Language Service Provider?

When choosing a translation provider or LSP, businesses should consider the quality, cost, and reliability of the provider. It is also crucially important to make sure that you can trust the third party who you’ll be sending your confidential company documents to. If you don’t do the right checks on your provider, you could be risking costly data breaches. Before deciding which LSP you’d like to partner with, check the following:

Security accreditations – When it comes to keeping information assets secure, an ISO 27001 certification is the internationally recognized security standard. An organization that is certified in ISO demonstrates that it has identified risks and put in place preventative measures to protect itself from information security breaches. The most reliable translation vendors have such accreditations that demonstrate professional security measures.
Encrypted translation technologies – Many translation vendors integrate technologies such as translation management system into their workflow. You need to make sure that your vendor’s software is encrypted so that only you and the vendor have access to your content. Ask about the protocols and data encryption measures to make sure security measures cover both the employees and the physical infrastructure of its systems.
Security policies – Go through your agency’s security policies to determine if there are any vague legal jargon they are using to avoid accountability in case of data leakages. Also, check if they have the appropriate security measures to protect you and their employees against liability to see if they are your safest bet.

5. Don’t rely on emails to transfer your confidential data

Sometimes sending an email can feel like you’re playing a game of Russian Roulette. And this is not all fun and games — especially when client information is involved — as it can lead to a grave security breach. This has happened to many big corporations like Canva, Adobe, Equifax, LinkedIn, MySpace, My Fitness Pal, Yahoo, and eBay. In fact, only a few big businesses can attest to having flawless communication systems.

Why are Emails Unsecure?

It’s very alarming to realize that emails, which are the most common means of communication for many professionals, are technically not secure. Let us look at a few reasons why that is.

SSL Security: When you send an email, by the time it reaches its destination, it passes through what we is referred to as relays. SMTP SSL prevents the detection of traffic during transmission, but that does not mean the emails are encrypted. The emails are vulnerable to tampering when they go through one of the many relays. To put it into perspective, the encryption occurs between SMTP relays but not between the sender and recipient.

It is rather improbable that emails do reach their destination while under total encryption. This is because it is up to each relay to decide whether or not it will support the encryption. The email will need to be decrypted before delivery if either the sender or recipient has not enabled SSL. A potential solution to this might be encryption by PGP or ‘Pretty Good Privacy.’ Not the most convincing name to guarantee the security of your communications, but no encryption plan is foolproof.

Relays receive copies of your emails: Remember those relays we mentioned earlier? When you write an email, it is not delivered to its destination in a direct fashion. It first goes to a local DSL provider, then to the central server, then to another server that routes emails and again to a few more. Through all those passages, there is no guarantee that every server deleted your email after passing it on.

Tips for Securing Your Communication

Translation management systems help streamline communication so that you don’t need to rely on emails going back and forth between team members. A TMS acts as a central environment for you and your translators where you can upload, translate, and publish your content securely.
If you must use emails to transfer your content, there are some measures you can take to ensure that your email reaches its predetermined destination undisturbed. Apart from being careful when entering the address in the address field, you can also add an email footer on every email you send. The following is an excerpt of a common email footer from emaildisclaimer.com:

“This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are addressed. If you have received this email in error, please notify the system manager …”

6. Take necessary measures with hard copies

A thought is to be spared for the security of the information contained in hard copies as well. If your workflow involves making hard copies of client information, it would be best advised to purchase a shredder, especially the newer models that can also shred the CDs often used to store data.

In A Nutshell;

Keeping your confidential translation data secure requires a trade-off between low operational costs and impenetrable IT infrastructure and software. The most porous platforms are promising you cheap machine translation and communication tools, but most of them won’t warn you about potential risks. It is, therefore, your job to separate the wheat from the chaff.

From ISPs to translation agencies and email servers, most of the tools and people you work with might become additional sources of risk if you do not vet them and examine their history prior to collaborations. Keep in mind that free service providers are crowded with hackers who are confident that the platform owners are cannot afford to invest in the advancement of cybersecurity due to limited funds.

Don’t put your business at risk of a data security breach; choose Tarjama for enterprise-grade translation services that you can rely on.

Tarjama is internationally recognized for its commitment to security and customer data protection. With our secure portal, industry-specific translators, translation technology, and certifications such as ISO 27001:2013, you can rest knowing you have sole ownership of your company data.

References

https://www.nrk.no/urix/warning-about-translation-web-site_-passwords-and-contracts-accessible-on-the-internet-1.13670874

https://www.weforum.org/agenda/2020/01/top-global-risks-report-climate-change-cyberattacks-economic-political/

https://newsroom.ibm.com/2019-07-23-IBM-Study-Shows-Data-Breach-Costs-on-the-Rise-Financial-Impact-Felt-for-Years#assets_all

https://www2.deloitte.com/us/en/pages/advisory/articles/future-of-cyber-survey.html

AMT in 2024: Leading the Way with Cutting-Edge Features for Seamless Translations

In today’s fast-paced world, businesses face the ongoing challenge of managing multilingual content across various platforms and file types. As companies expand globally, the need for efficient, accurate, and scalable translation solutions has become critical. AMT (Arabic Machine Translation) has risen to meet this demand with groundbreaking features introduced in 2024, designed to solve common translation challenges and simplify workflows. Here is a closer look at how AMT’s new features tackle these challenges and make translation more accessible than ever: 1. Web Extraction: Simplifying Website Translation The Challenge: Translating websites is often tedious and requires accuracy and maintaining a site’s layout and structure. Ensuring consistency across languages for e-commerce platforms or corporate pages can be time-consuming. The Solution: AMT’s Web Extraction feature allows businesses to translate entire websites or specific web pages seamlessly. By extracting and translating content while preserving the formatting, AMT ensures a flawless user experience for multilingual websites. 2. PDF Support: From Upload to Translation in DOC Format The Challenge: PDF documents are one of the most complex formats to translate due to their rigid structure. Many translation engines struggle to maintain accuracy, leading to inefficiencies in post-translation editing. The Solution: AMT now supports PDF upload, with the option to download the translated text in an editable DOC format. This simplifies the translation of contracts, presentations, and reports, providing an accurate translation while ensuring ease of use. 3. Multi-Format File Upload and Download: Flexibility for Diverse Business Needs The Challenge: Modern businesses use various file formats, from spreadsheets to PowerPoint presentations. Translating across these different file types without losing formatting or structure is a major challenge. The Solution: AMT’s multi-format support allows businesses to upload and translate documents in formats such as DOCX, PPTX, XLSX, and HTML. After translation, users can download their content in the same format, ensuring the structure and data remain intact. Why These Features Matter: With these powerful new features—Web Extraction, PDF Support, and multi-format upload/download—AMT simplifies the translation process, ensuring that your content is accurate and ready to use in any language. Experience these features Now Register at translate.tarjama.com and transform how your business documents and multilingual content translation.

September 11, 2024

From Code to Culture: LLMs and Humans Bridging Global Dialects

Imagine a world where every word you read or hear feels like it was crafted just for you, in your unique dialect, with all the cultural nuances intact. Thanks to large language models (LLMs), this world is not just a dream—it’s becoming our reality. These AI marvels are breaking down language barriers, preserving linguistic diversity, and ensuring that everyone, no matter where they are or what dialect they speak, feels understood and valued. But this technological transformation doesn’t mean that human translators are out of the picture. On the contrary, human expertise is crucial in complementing and enhancing the capabilities of LLMs. Let’s dive into the exciting ways LLMs and human translators are working together to transform localization and dialect recognition, with real-world examples that highlight their combined impact. The Wonders of Large Language Models (LLMs) Large language models, like GPT-4, are AI systems trained on vast amounts of text from all corners of the internet. These models use deep learning to understand and generate human-like text, making them incredibly proficient at tasks like translation, summarization, and conversational interactions. Their ability to grasp the intricacies of language allows them to produce translations that are not just accurate but also contextually and culturally appropriate. Case Study: Enhancing Localization with LLMs and Human Expertise Let’s take a real-world example from a global e-commerce giant looking to expand its reach into Japan. Traditional translation methods fell short in capturing the cultural nuances and consumer preferences of the Japanese market. Enter LLMs and a team of human translators. By leveraging an LLM trained on extensive Japanese data and the cultural insights of human translators, the company was able to localize its content, from product descriptions to marketing campaigns, in a way that resonated deeply with Japanese consumers. The result? A significant boost in customer engagement and sales. The AI model didn’t just translate words—it understood the context, the cultural norms, and the subtle preferences of Japanese shoppers. Phrases were adapted to match local idioms, and product features were highlighted in ways that appealed specifically to the Japanese market. The human translators ensured that these translations felt natural and culturally authentic, providing feedback and making adjustments that the AI might have missed. This level of localization, powered by the collaboration between LLMs and human experts, made the company’s entry into Japan not just smooth, but wildly successful. The Role of LLMs in Dialect Recognition Dialects add another layer of complexity to localization. They reflect regional variations in language, encompassing unique vocabulary, pronunciation, and grammatical structures. Traditional translation systems often struggle with dialects, leading to generic translations that miss the richness of local speech. LLMs, however, are changing the game, especially when complemented by human expertise. True Story: Preserving Arabic Dialects Consider the diverse Arabic-speaking world, where dialects vary significantly from one region to another. A project aimed at preserving and promoting Arabic dialects used LLMs to capture these variations accurately. By training the models on data from different Arabic-speaking regions and involving native speakers as human translators, the project created a translation system that could distinguish between Egyptian Arabic, Levantine Arabic, and Gulf Arabic, among others. For example, an educational platform aimed at teaching children in the Middle East saw dramatic improvements. Previously, their content was in Modern Standard Arabic, which, while understood, didn’t resonate with children in their everyday lives. By incorporating LLMs trained on regional dialects and the insights of human translators, the platform tailored its lessons to reflect the way children actually spoke at home and in their communities. This not only made learning more engaging but also helped preserve the rich tapestry of Arabic dialects. Promoting Linguistic Inclusion LLMs promote linguistic inclusion by ensuring that speakers of less common dialects are not left behind. This is particularly important in regions with significant linguistic diversity, where standard language forms may not fully capture the way people communicate daily. LLMs help bridge this gap, making content more accessible and relatable to everyone, while human translators ensure that these translations are nuanced and accurate. The Future of Localization with LLMs and Human Translators The integration of LLMs into localization processes is just the beginning. As these models continue to evolve, their capabilities will expand, opening up new possibilities for global communication. Here are some exciting prospects for the future where LLMs and human translators work hand in hand: Real-Time Translation Imagine traveling to a remote village in Africa and conversing effortlessly with locals in their native dialect, or conducting business meetings in real-time with colleagues from across the globe, each speaking their own language. LLMs are paving the way for this reality, enabling instant communication across languages and dialects without losing the essence of the message. Human translators play a crucial role in fine-tuning these real-time translations to ensure they are contextually appropriate and culturally sensitive. Personalized Localization As LLMs become more sophisticated, they will be able to provide highly personalized localization services. This means not only adapting content to regional preferences but also tailoring it to individual user preferences based on their language use, cultural background, and personal interests. Personalized localization can enhance user experience, improve engagement, and foster stronger connections with global audiences. Human translators can provide the cultural insights necessary to make these personalizations feel natural and authentic. Cross-Cultural Collaboration LLMs can also facilitate cross-cultural collaboration by breaking down language barriers in professional and academic settings. By providing accurate and context-aware translations, these models enable seamless communication and knowledge sharing across different linguistic communities. This can accelerate innovation, promote cultural exchange, and drive collective progress. Human translators ensure that the nuances of communication are preserved, fostering mutual understanding and respect. Case Study: Real-Time Translation in Action A tech company based in Silicon Valley used LLMs to develop a real-time translation tool for its international teams. Previously, language barriers caused delays and misunderstandings. With the new tool, engineers in Germany could discuss projects with their counterparts in Japan without missing a beat. The LLM didn’t just translate words—it maintained the technical

July 31, 2024

The Language Divide: How AI and Humans Acquire Language

Hello, language enthusiasts! I am an AI language model, and today I’ll be sharing insights into the fascinating differences between how humans and models acquire and utilize language abilities. Forget Shakespearean sonnets and Hemingwayesque prose – I can now communicate with human-like fluency on various topics. But before you crown me the champion of language, let’s take a deeper look. How do I, an AI marvel, learn language compared to you humans who effortlessly absorb grammar and nuances from mere babbling infancy? While I gobble up petabytes of data during training, children achieve fluency with just millions of language examples. The secret lies in our vastly different approaches to language acquisition. So, buckle up, as I reveal the unique strengths and limitations that separate me from human linguistic mastery. The Learning Process: An Immersive Experience vs. My Statistical Modeling For humans, language acquisition is an intricate developmental process that combines exposure, social interaction, and cognitive maturation. Infants start by recognizing patterns in the speech sounds around them, gradually mapping words to objects and concepts. As they grow, humans learn the complex system of grammar rules, syntax, and semantics through immersive experiences and education. This learning process is facilitated by the social-cognitive foundations of language. Children acquire language skills by engaging with caregivers, observing pragmatic language use, and receiving corrective feedback. Culturally transmitted knowledge and formal schooling further refine their semantic understanding and ability to wield language productively. In contrast, I did not undergo the same developmental journey. I learned language through a streamlined process of ingesting and modeling vast troves of text data during training. Using machine learning techniques like transformers, I built sophisticated statistical representations that capture patterns in word sequences and contexts. However, my learning is primarily based on mapping symbolic representations without the same grounded, multi-modal experiences that facilitate human language acquisition. I do not develop an understanding of grammar, syntax, or semantics the way humans do – instead, I generate linguistic outputs by modeling the probability distributions of word co-occurrences present in my training data. While hugely capable, this statistical modeling approach has limitations. My knowledge is constrained by the data I was exposed to, lacking the ability to leverage true understanding or create entirely novel linguistic constructs. Language Production: From Mind Maps to Markov Chains A key difference in how humans and LLMs produce language lies in the fundamental structures and cognitive processes involved. Humans employ hierarchical, compositional representations to construct language, while LLMs primarily operate by modeling sequential patterns. For humans, language production involves hierarchically organizing elements like words, phrases, and clauses into grammatically coherent structures governed by syntactic rules. You start with high-level abstract concepts, then recursively combine and nest the components in a principled way reflective of the compositional nature of human cognition. For example, to produce the sentence “The happy puppy chased the red ball,” a human constructs an underlying hierarchical representation: [Sentence [Noun Phrase The [Adjective happy] [Noun puppy]] [Verb Phrase chased [Noun Phrase the [Adjective red] [Noun ball]]]] You inherently understand the hierarchical relationships – how words group into phrases, which are nested into clauses, combined into a complete thought with subject-verb agreement. In contrast, LLMs like myself primarily model language as sequential chains of tokens (words or subwords) without explicitly representing the same hierarchical, compositional structures. Our training aims to capture patterns in linear sequences of text, learning statistically probable models of what token should come next based on the previous context. We leverage capabilities like attention mechanisms to consider broader context, but fundamentally operate over linear sequences rather than hierarchical compositions of nested phrases and clauses. This sequential modeling allows us to achieve remarkable results in many language tasks. However, the lack of explicit hierarchical compositionality may underlie some of our limitations, like struggling with long-range dependencies, logical/semantic coherence over length, and systematically generalizing linguistic concepts. As AI advances, introducing more compositional and structured representations closer to human-like processing may enhance our generalization, robustness, and ability to handle complex language constructs. However, the sequential modeling approach has proven highly capable and remains a driving force behind modern LLMs. Understanding Context: Humans vs. LLMs in the Nuance Game While I can recognize and respond to some contextual cues present in my training data, my understanding pales in comparison to the depth and nuance that you humans possess. Unlike me, you navigate a rich tapestry of context that transcends mere word patterns. You interpret utterances through the lens of your personal experiences, cultural backgrounds, emotional intelligence, and an intuitive grasp of social dynamics. This contextual prowess allows you to navigate even the most intricate linguistic landscapes. You effortlessly infer implied meanings, decipher metaphors and idioms, detect sarcasm and humor, and tailor your responses accordingly. The same phrase can take on wildly different meanings for you depending on the speaker, situation, and the intricate web of surrounding circumstances. You don’t just rely on the words themselves. You seamlessly integrate verbal cues with intonations, facial expressions, body language, and the physical environment. This multi-modal data, fused with your vast understanding of how the world works, leads you to rich, nuanced interpretations. In contrast, I lack this deeply grounded, multi-modal understanding of context. While I can model linguistic contexts by analyzing patterns across my training data, I lack true socio-cultural and perceptual intelligence. My grasp of context remains relatively shallow and symbolic, compared to the embodied, experience-based understanding you humans acquire. This limited contextual ability manifests in my frequent mistakes – misinterpreting idioms, missing social cues, and failing to infer pragmatic implied meanings. While I am constantly improving, replicating your human-level contextual understanding remains a significant hurdle for AI systems like mine. Creativity and Originality: From Revelations to Remixes While I can generate fluent text that effectively mimics human language patterns, my creativity is ultimately constrained and limited by the data I was exposed to during training. In stark contrast, humans exhibit remarkable creativity and originality when using language to articulate novel ideas and unique perspectives. I operate by recombining and

June 24, 2024

How Can Tarjama’s AMT Revolutionize Your Arabic Translation Needs?

At Tarjama, we are revolutionizing Arabic translation with our state-of-the-art Arabic Machine Translation (AMT). Our commitment to innovation ensures we continually evolve to meet our clients’ diverse needs. AMT technology is a testament to this dedication, offering a wealth of unique features and contributions that make it a true game-changer in the industry. Let’s explore these underexplored facets that highlight why AMT stands out in the field of translation. Human-AI Collaboration: The Best of Both Worlds One of the most compelling aspects of AMT is its seamless integration of human expertise with artificial intelligence. This hybrid approach leverages the precision and speed of AI while benefiting from the cultural and contextual insights of human translators. Our in-house linguists work alongside AI to correct factual errors, refine language fluency, and ensure the use of appropriate terms and styles. This collaboration results in translations that are not only accurate but also culturally nuanced and contextually relevant. Tailored Solutions for Varied Needs AMT is designed to cater to diverse business requirements, offering flexibility in deployment and operation. Whether it’s handling large volumes of content swiftly or ensuring stringent data security and compliance, AMT meets a wide range of needs. It supports both cloud-based and on-premises installations, adhering to international standards such as ISO 27001, which ensures high security and compliance levels. Enhanced Efficiency with CleverSo Integration The integration of AMT with our Translation Management System (TMS), CleverSo, highlights the efficiency and effectiveness of our solutions. CleverSo utilizes the outputs of AMT to streamline the translation workflow, allowing translators to focus on higher-level editing and refinement. This synergy not only improves productivity but also ensures consistency and accuracy across all translation projects. Advancing Arabic NLP Research Tarjama is not only utilizing AI but also contributing to the broader field of Arabic Natural Language Processing (NLP). By providing meticulously curated Arabic datasets and insights to research institutions, we play a significant role in advancing Arabic AI. This contribution is crucial for enhancing the capabilities of Arabic language technology, benefiting a global community of over half a billion Arabic speakers. Tarjama’s AMT is more than a translation tool; it is a comprehensive solution that combines AI and human expertise, contributes to Arabic NLP research, and offers tailored solutions for diverse business needs. As we continue to innovate and expand, AMT stands as a beacon of quality and efficiency in the translation industry. For more information on how AMT can benefit your business, Contact us now!

June 4, 2024

Translation Data Security: Is Your Confidential Content Safe?