ULG's Language Services Blog

Authority Magazine: Blanca Vidal Of United Language Group On Five Things You Need To Create A Highly Successful Career In The AI Industry


As seen in Authority Magazine

Artificial Intelligence is now the leading edge of technology, driving unprecedented advancements across sectors. From healthcare to finance, education to environment, the AI industry is witnessing a skyrocketing demand for professionals. However, the path to creating a successful career in AI is multifaceted and constantly evolving. What does it take and what does one need in order to create a highly successful career in AI?

In this interview series, we are talking to successful AI professionals, AI founders, AI CEOs, educators in the field, AI researchers, HR managers in tech companies, and anyone who holds authority in the realm of Artificial Intelligence to inspire and guide those who are eager to embark on this exciting career path.

As part of this series, we had the pleasure of interviewing Blanca Vidal.

Blanca Vidal is currently the Machine Translation (MT) Production Manager at United Language Group (ULG), a leading language service provider with global reach and a focus on outcomes. In 1993, she began her career in AI and MT by way of linguistic studies and has been learning and growing in the industry ever since. She received her Bachelor’s degree in English Philology from Universitat de Barcelona and her Master’s degree in Knowledge Based Systems from University of Sussex, Brighton.

Thank you so much for joining us in this interview series! Before we dive in, our readers would like to learn a bit about your origin story. Can you share with us a bit about your childhood and how you grew up?

I was born in Barcelona and have lived there on and off most of my life. In my childhood, I enjoyed outdoor play, but also, I liked reading. As I grew up, I remember taking every opportunity to travel and these experiences shaped my fascination for language. I have always been curious about learning linguistics and the interaction of culture and language. When I found out that technology could help connect people through language, I was hooked.

Can you share with us the ‘backstory” of how you decided to pursue a career path in AI?

I have been in the machine translation (MT) industry since 1993. I came to the industry after I attended a university class when MT was first emerging, and I found it very interesting. My class was small (less than ten people) so we were able to dive into syntax and really learn how machines were able to replicate human thinking. The opportunity to spread multilingualism and be part of a highly specialized field has kept me interested and invested in AI.

When I was starting out, the typical career path for linguists was to teach language. I saw opportunity when I discovered there was an emerging area of study that focused on creating programs that could perform a syntactic analysis of a sentence just like we did when we were young in school. So, I chose that subject, and it changed the course of my studies and then my professional life.

Natural language processing was the beginning of my career, quickly evolving to focus on how to train machines to do language tasks and the categorization of terms according to meaning or semantics. As a junior programmer focused on quality assurance, I was serving as the bridge between sales and technology. This was good training, and I enjoyed the role, but I also knew that it was not the best use of my skills, so I found a mentor and continued to forge my path to a career that aligned more closely with my interests.

Flash forward to today, and I am a senior member of a team delivering machine translation solutions. I truly enjoy the product we’re creating, the field that we’re leading in and the fact that I am utilizing language focused tools each day. Both AI and the language services industries are always evolving, which keeps me engaged and eager to continue my growth. Finding commonalities in the data and rolling out projects while ensuring our services are useful to clients and their business is why I work at ULG.

Can you tell our readers about the most interesting projects you are working on now?

Utilizing technology to take projects further and faster, while connecting cultures around the world, is inspiring to me and what keeps me interested in this work and this industry. There are two exciting projects that we’re focused on right now:

  1. Studying cultural engagements and outcomes.

    We are using the cultural drivers of engagement to help our customers connect and engage faster and better with their multicultural, multilingual consumers. We utilize AI to look at large data sets and make sense of them so we can see how and where these diverse communities are engaging. This allows us to produce stronger outcomes more efficiently for our partners and customers. This is one of our largest undertakings as a team and an exciting endeavor that requires an investment in resources and a strategic focus on results.

  2. Using contextual data to convey accuracy of multilingual conversations and documents (aka multilingual natural language processing).

    Utilizing context, Large Language Models (LLMs) can improve the fluency and accuracy of generative outputs, which is a huge opportunity. Where before it was a sentence-by-sentence connection, now it’s about contextual accuracy through translation by machine learning. This is a step closer to replicating human language. Each day we ask ourselves, “How can we train technology to utilize context clues more effectively?” as we create solutions for our customers.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful for who helped get you to where you are? Can you share a story about that?

I have been fortunate to have managers at various companies who have both inspired and supported me. One of my early managers took the time to offer me new opportunities and roles that I wouldn’t have seen or pursued on my own. I am grateful to have been trusted to make progress in my career.

From another manager, I learned the power of a respectful leadership style and unwavering curiosity. This curious approach extended beyond technological or linguistic subjects. I believe it’s crucial for companies to have not only top specialists but also individuals with a broad passion for knowledge.

At ULG we are committed to innovation, and I am proud that my team and I were responsible for the integration of MT into ULG’s production processes. With continued support from leadership, we have been pleased to see more and more deployment of MT into our team’s workflow as technology and time progresses. We currently offer MT solutions in 300+ languages and unique verticals and continue to see growth in this area as we meet the market where it is.

As with any career path, the AI industry comes with its own set of challenges. Could you elaborate on some of the significant challenges you faced in your AI career and how you managed to overcome them?

AI is ever-changing, which is part of the largest opportunity for growth. If I think of AI as an industry, a major challenge that arises is having a career where most people can clearly see the benefit of utilization, yet may not understand the steps, processes, or requirements to achieve those benefits.

Our customers are not always certain how or when to utilize AI technologies and functionalities to support language access. To solve this problem, our team has developed a methodology to determine which content is best suited to AI and NMT (Neural Machine Translation). Because many of our customers deal with complex security requirements, compliance regulations and more, our role as a partner in the field is to help them navigate the technology in a way that works best for their business goals and objectives and link the function to the outcome.

Our biggest challenge in this area as an LSP is embedded bias. Helping my team to understand how to manage data volume and import it so that cultural nuance doesn’t become an embedded bias in the data (where a majority answer becomes the only effective answer) ultimately required a unique workflow methodology developed specifically to avoid it in the content we work on. This had to be designed, checked, and approved by upper management — it was a lot of education and time as a team, but it has made a dramatic difference to the outcome, and that difference helps to drive career opportunity for our team.

Ok, let’s now move to the main part of our interview about AI. What are the 3 things that most excite you about the AI industry now? Why?

  1.  AI tools are more effective than ever.

    It’s amazing to see the evolution of the industry, and how AI and things such as Chat GPT are now in the lexicon and utilized in everyday communication. There is a fluency and accuracy that is emerging in this technology that is almost unbelievable- and was frankly unthinkable until recently.

  2. There are more use cases for AI utilization than ever.

    We are just seeing how far this can go and how to use data sets for multiple uses. We can do more, faster, and must try to use these integrations for good. Utilizing AI to help patients with neurological disorders communicate is just the tip of the iceberg and an exciting addition to the industry and a useful output.

  3. AI allows us to be nimble + consistent as an LSP.

    We can create style guides that mimic human language that can connect remote employees, provide healthcare information to multilingual patients or other applications we’re not thinking of yet, all with the touch of a button. Global connection is key in the modern market, and we’re able to use AI technology to empower outcomes.

What are the 3 things that concern you about the AI industry? Why? What should be done to address and alleviate those concerns?

  1. Tech evolving very quickly.

    Not only is technology rapidly advancing but the use cases are changing and growing. Businesses feel the need to integrate AI in their processes just to make sure they are keeping up with the market. Our team is continually learning and evolving our approach as we keep up with industry standards and continue to be a resource for our customers while putting security and quality first.

  2. Bias is inherent and must be stopped at the root.

    Bias in AI technology is a huge issue. For example, cultural biases are a persistent problem for machine translation. Translations may align with a societal or country norm rather than taking cultures into consideration. In certain cultures, social hierarchy is extremely important, and this carries over into language. Our experts work diligently to infuse our MT with culture competence to support meaningful language access.

    AI system designers can reduce bias in their products by hiring more diverse team members and seeking out diverse training data when it is available. Translators can post-edit MT output to correct biased or inaccurate translations. This gives the benefits of machine translation — improved speed and efficiency — while still maintaining quality and cultural competence.

  3. Another area that creates a challenge in AI is fake data.

    In the rush to capture as much data as possible, a company may push for increasingly large data sets — but not all data is equal and our role as a partner is to be the mediating voice to identify the best data for the job.

    Europe is leading on protection legislation currently, but large companies are ahead of this guidance with their current utilizations so are using data in ways they might someday become illegal based on new regulatory control; thus, it is a very difficult area to provide guidance on.

For a young person who would like to eventually make a career in AI, which skills and subjects do they need to learn?

I would recommend studying Computer Science and diving into programming, with a particular emphasis on Python, given its current dominance in the field. I would also mention building a foundation in mathematics, especially in areas like statistics, as something to consider. Training on Machine Learning and Deep Learning is a direct path to AI projects. Data Management and Data Engineering are other key areas in AI. You must not only know data and how to work with it, but also be able to disseminate information while producing outcomes.

Additionally, acquiring specialized knowledge in areas where AI can be applied, such as Natural Language Processing, Computer Vision, Robotics, or Biology, will further enhance your expertise, making you an attractive candidate or strong employee. AI is a piece of the puzzle, not the be all end all. Engineering, project management, and other subjects will keep you on top of the field and will support your global career.

As you know, there are not that many women in the AI industry. Can you advise what is needed to engage more women in the AI industry?

We need to band together to engage and empower women, starting early. We need to showcase female identifying workers in the field and make sure their stories are not only told but they are held in high regard. We must make sure there are professional groups and networking opportunities centered on females that give space for young professional women to learn and grow together in community. These opportunities need to happen in the classroom and at the office. We must show that young women can do anything and ensure that they have training and support they need to thrive, no matter their level. We need to have female centric training and networking organizations and opportunities so that younger females feel included. Visibility is critical in supporting empowerment. I look forward to seeing the next generation grow.

Ethical AI development is a pressing concern in the industry. How do you approach the ethical implications of AI, and what steps do you believe individuals and organizations should take to ensure responsible and fair AI practices?

Approaching the ethical implications of utilizing AI requires a multi-faceted strategy. There should be educational awareness for both developers and users, so they are informed and understand the data AI systems use and their potential impact. There should also be more transparency on AI Models. For instance, certain environments allow you to see the data where the model output comes from. Regulation is the final key to ensuring the safety and quality of data. Governments need to take this topic seriously and must implement regular audits of AI systems to ensure adherence to established ethical guidelines.

Ok, here is the main question of our interview. Can you please share the “Five Things You Need To Create A Highly Successful Career In The AI Industry”?

  1. Technical expertise and education.

    There are various disciplines and skills that are at the basis of AI technology (listed above) and the route to get there is up to you. It’s an exciting, evolving industry that you can make your own, knowing that it will never be dull.

  2. Ability to learn new skills.

    AI is continually and rapidly evolving, and it is crucial to stay updated and learn the latest technologies and methodologies. What works one day may not be in fashion the next, so trends, education and market research are critical.

  3. Ability to stay on top of trends.

    AI is changing so quickly that formal education is not enough, and AI pros must engage in continuous learning through online courses, workshops, conferences, and research papers. This not only provides learning opportunities but also opens doors for collaborations and career advancements. Networking formally and informally is a way to keep up with trends and technology as well.

  4. Creative bent to solve problems and try new things.

    A solutions-oriented, forward-thinking approach is important in an AI career. AI involves pure research, which means that many ideas don’t work on the first try and new solutions must be brought to the table again and again (over and over). A positive outlook will get you far in life and at work, so find the good in each day and learn from each project.

  5. Ability to collaborate and give clear direction.

    Technology only works as well as the human who is using it. To be successful, you must be able to collaborate well with humans and technology, bridging gaps and finding opportunities to connect dots. Teamwork is a part of most projects, which involve a multidisciplinary approach. You must be an expert in your field who is comfortable with your role and knows how to connect people and things.

Continuous learning and upskilling are vital in a dynamic field like AI. How do you approach ongoing education and stay up-to-date with the latest advancements in the AI industry? What advice do you have for those looking to grow their careers in AI?

One must possess leadership skills to thrive in this industry. In this remote-first, ever evolving market, it’s important to be able to work multi-functionally. AI teams can’t do everything on their own- they must know how to take an interdisciplinary, collaborative approach to the work.

If I was to describe a top candidate, I would say that they must be willing to test new things, think big and be free! These are some of the key attributes that I am looking for when I bring a new colleague to the team. The sky is the limit in this industry, and it takes a creative, fearless person to thrive. I want to work with people who are thinking outside of the box and ahead of the curve when it comes to the industry.

It’s fundamental to keep taking classes after you graduate and to be part of professional groups. This helps you continually network while staying on top of industry trends. Attending conferences (whether virtual or in person) is a necessary part of the role that also supports learning.

What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?

Oscar Wilde’s quote is on my refrigerator: “Be yourself. Everyone else is already taken.” I purchased a magnet with this famous saying after visiting ULG’s Galway office and it made me smile. Remembering that your distinct value is ingrained from childhood is something I think about often.

Seneca wrote some wise words that resonate with me: “No wind is favorable if one does not know to which port one is sailing,” is something that I turn to always. Many leaders are asked why some people get what they want and why others don’t, and I always come back to Seneca’s quote as it’s a thought worth remembering. In short, if you don’t focus on outcomes, your energy won’t flow forward to support your goals.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

What a great question- very thoughtful. One thing that I have learned over my career is that thinking big but focusing small is the key to anything. I may not be here to change the world, but I believe the work I am doing with machine translation has the power to help people communicate across cultures and languages and that can hopefully make the world a bit better. The 1% rule fascinates me, and I aim to keep it in mind as I approach each day. It says that you don’t have to overwhelm yourself trying to do everything perfectly- but trying each day to be 1% better will make a difference and push you to success. There is power in focusing on small gains for larger results. I would say if I could better myself 1% each day, it would create an impact on the team, and therefore improve results for the company, improving communications for the communities we serve, which is a win-win for all.

How can our readers further follow your work online?

Follow Blanca: https://www.linkedin.com/in/blanca-vidal-b455b414/

Follow team ULG at https://www.linkedin.com/company/united-language-group or https://www.unitedlanguagegroup.com/

This was very inspiring. Thank you so much for joining us!


About The Interviewer: David Leichner is a veteran of the Israeli high-tech industry with significant experience in the areas of cyber and security, enterprise software and communications. At Cybellum, a leading provider of Product Security Lifecycle Management, David is responsible for creating and executing the marketing strategy and managing the global marketing team that forms the foundation for Cybellum’s product and market penetration. Prior to Cybellum, David was CMO at SQream and VP Sales and Marketing at endpoint protection vendor, Cynet. David is a member of the Board of Trustees of the Jerusalem Technology College. He holds a BA in Information Systems Management and an MBA in International Business from the City University of New York.