Blackout Redaction is Making Your Job Harder than it Needs to Be

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How blackout redaction is making your job harder

When it comes to protecting classified data, blackout redaction has been in use for at least a century. While it is not the only acceptable form of data sanitization, it is historically the oldest and most commonly utilized by eDiscovery firms. This is despite the fact there are more modern and easy-to-use alternatives that save time and reduce errors. The two main data sanitization alternatives that meet legal requirements include anonymization and pseudonymization

In the past, the organizations most concerned with data sanitization including government agencies and law firms. Over the past few years, privacy protection has taken a global stage. The European Union’s General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) now put legal parameters in place for data privacy protection. These laws affect not just how companies collect and use data, but also how they store and share that data. 

Could your eDiscovery operation benefit from incorporating more blackout redaction alternatives into your day-to-day? 

Need help navigating your compliance requirements? Download our in-depth guide to cross-border discovery under GDPR here.

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The California Consumer Protection Act’s (CCPA) Impact on eDiscovery Firms

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As noted by Anju Khurana, Head of Privacy of the Americas, Bank of New York Mellon, “There are now over 100+ privacy laws in the world and GDPR is driving other countries to adopt similar regulations.” (corpcounsel.com, Oct. 2019). The California Consumer Protection Act (“CCPA”) which comes into effect on January 1, 2020, is the latest, and very likely not the last. Most data privacy experts anticipate additional states enacting data privacy regulations and think it likely that Congress will eventually do so at the federal level.

While modeled on the General Data Protection Regulation (“GDPR”), which came into effect in May 2018, there are differences, both small and substantial. A comparison of many of the key requirements from Thomson Reuter, Practical Law can be found here. 

Need help navigating your compliance requirements? Download our in-depth guide to cross-border discovery under GDPR.

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OpenNMT-tf 2.0: a milestone in the OpenNMT project

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OpenNMT-tf 2.0 workshop. Red Kakemonos and French Tech Central logo in front of the entrance door of Station F held in Paris in March 2018.
OpenNMT workshop held in March 2018 at Station F in Paris // Copyright SYSTRAN

SYSTRAN has been wholeheartedly involved in open source development over the past few years via the OpenNMT initiative,whose goal is to build a ready-to-use, fully inclusive, industry and research ready development framework for Neural Machine Translation (NMT). OpenNMT guarantees state-of-the-art systems to be integrated into SYSTRAN products and motivates us to continuously innovate.

In 2017, we published OpenNMT-tf, an open source toolkit for neural machine translation. This project is integrated into SYSTRAN’s model training architecture and plays a key role in the production of the 2nd generation of NMT engines.

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Beyond the AI Hype – Neural Machine Translation Is Production Ready

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AI programs background with the article title "Beyond the AI Hype – Neural Machine Translation Is Production Ready" in front - Systran
A SYSTRAN Blog for the US Government Community

Since the publication of the Executive Order on Maintaining American Leadership in Artificial Intelligence by the White House this past February, many government agencies are struggling with getting started in AI. They realize use of this technology will help them be more efficient. However, finding those tasks that will be “quick wins” in moving towards AI adoption is the main challenge.

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“So, You Think Your Game Is Localized?”

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Game Is Localized? Player holds a controller and plays video game - Systran
Highlights from Webinar with Elizabeth Senouci And Victor Ramirez

Last month, we conducted a webinar “So, You Think Your Game Is Localized?”, the first of a 3-part-series given by Elizabeth Senouci from XTM International, and Victor Ramirez from SYSTRAN.

If you couldn’t guess by the title, “So, You Think Your Game Is Localized?” was a webinar focused on Video Game Localization. Senouci and Ramirez are both experts on the topic and thus decided to share their knowledge with the video games community.

In the webinar, Senouci and Ramirez discussed the need for game localization, some basic terminologies associated with it, user interfaces, global marketing, and the importance of customer service.

“Localization isn’t just one thing you can do and just get done with it. It’s a holistic process and it’s actually customized based on your game, your product,” Elizabeth said in her intro.

Why Localize?

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Four Ways SYSTRAN’s Neural Machine Translation Supports Global Commerce

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Explatory infographic the neural machine translation through Systran pure neural server and its process.
SYSTRAN Pure Neural Server Process // SYSTRAN

For staff of multinational companies who want to translate a simple phrase or word, systems like Google or Microsoft come in just handy. They help you order a taxi in Japan, pay your restaurant bill in France, and impress your clients with a hearty “jó reggelt” (“good morning”) in Budapest. The problem is such tools are notorious for imprecise translations and data leaks.

Would you really want to use Google Translate for that internal email to your affiliates in another country?

On the other hand, research from the European Parliament shows that on average a common language increases trade flows by 44%. So, how do you – and your staff – hack through language barriers and achieve professional communication in the business world?

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The art of speeding up NMT with SYSTRAN 2nd generation engines

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Machine Translation users care about quality and performance. Based on our own observations and the feedback we’ve received; the quality of our Neural MT is impressive. Evaluating performance is a stickier subject, but we’d like to dig our hands in and present our innovations and achievements and how it benefits NMT users.

By performance we mostly mean the manner in which a system performs in terms of speed and efficiency in varying production environments. It is important to note that performance and quality in Neural MT are tightly connected: it is easy to accelerate a given model compromising on the quality. Therefore, when evaluating performance improvement, we always check that quality remains very close to optimal quality.

Since switching to NMT at the end of 2016, we’ve invested our R&D efforts into optimizing our engines to be more efficient, while maintaining and even improving translation accuracy. Our latest, 2nd generation NMT engines, available in our latest release of SYSTRAN Pure Neural® Server, implements several technical optimizations that make the translation faster and more efficient.

New model architecture

The first generation of neural translation engines was based on recurrent neural networks (RNN). This architecture requires the source text to be encoded sequentially, word by word, before generating the translation.

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Online Translation Tools and Data Breaches

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Man is holding a tablet through which he has access to users data.

Is Your Team Violating Data Compliance Laws?

Data leakage and lack of information are two critical issues that can harm businesses. Nonetheless, due to the ever-growing global marketing and communication needs, the temptation to use the fast and free online translation tools are rising.

Apart from the apparent dangers that these tools pose to businesses such as miscommunication, loss of business, and cultural insults, there is critical important threat that many enterprises often fail to recognize. 

Whenever an employee uses a free online translation tool, they may cause massive data privacy breaches by making the consumer data searchable. Data breaches as such mainly happen due to employee negligence looking for quick machine translation, and it can often put millions of customers’ sensitive data at exposed on the internet.

Companies thus struggle to find the right balance between enabling business and securing information. Without the capability of translating software, potentially hundreds, if not thousands, of employees could turn to free translation tools to get their content translated in turn making the content available online.

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Four Reasons to Use NMT for Translation Work in the U.S. Federal Government

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Reading a Czech book through eye glasses. Systran gives 4 reasons why NMT is primary for such complex & important structure as the U.S. Federal Government

Until recently, using machine translation (MT) was considered a hindrance by serious translators.  Now that machine translation is powered by artificial intelligence, translators in the government are intrigued by this new technology.  Forward-thinking linguist programs recognize the value of MT, and it’s only a matter of time when others will follow suit.  Consider these four reasons as motivation for modernizing the status quo:

1. Translate Smarter

As with many other skilled professions – accountants, doctors, analysts – technology is a time-saver.  Translators now have the same benefit.  In fact, commercial benchmarks show that neural MT helps translators post-edit at 2000 words per hour.  Without technology, which is typically the case in the government, translators translate at 300 words per hour.  Imagine the time-savings — the same 6000-word document can now be translated in 3 hours instead of 20.   Additionally, SYSTRAN MT will retain the formatting of the original document, which further saves time.

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Our Neural Network just learned Syntax!

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Experience unprecedented integration of customer terminology with neural networks!

SYSTRAN Pure Neural® Server, our state-of-the-art translation technology tailored for businesses, delivers quality, fast, and secure translations using Neural Networks and Artificial Intelligence. We have just added support for a unique feature that takes it a step further. Users can now add custom terminology to be used in their translation tasks. Seasoned users know about User Dictionaries in our previous rule-based and hybrid technology, but this feature was not fully implemented by the Neural Networks. Until now.

A book in which the word "translation" is highlighted in green. SYSTRAN show the importance of translation in business & in life in general.

Translation tailored to your need

User Dictionaries (UDs) are key in customizing translation to users’ needs by allowing them to determine their own terminology and ensure that it is translated as such regardless of context. They can also be used to disambiguate between a word with multiple meanings. In this case, translation profiles can be created that apply user dictionaries with the ambiguous term translated differently in each. For example, “mettre sous tension” would be translated from French as “to turn on” in a Generic profile, but a user could create an Aeronautical profile and add the entry to a UD as “to energize” and if needed create an Electronics profile for the term to be translated as “to apply power.” User Dictionaries can also quickly correct any translations that are not accurate for the user’s context. User dictionaries are primarily used so that industry jargon and brand, model and product names are translated accurately.

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