Machine translation and interpretation make sciences take a leap.
Machine translation and interpretation make sciences take a leap
Ever heard of the Life Sciences industry? It’s the science concerned with the study of living organisms, including biology, botany, zoology, microbiology, physiology, biochemistry, and related subjects.
And over the years, it has incorporated Machine Translation (MT).
It makes sense. As humans, we tend to collaborate. We survived because we grouped. We conquered because we divided life into roles and labor and eventually, developed intelligence deeper than we could imagine. But by that time, many of us spoke words mute to the ears of others. Novelties had to travel, communicate and translate. And as years piled up, in a more and more specific manner.
But two heads are better than one. And thousands can do wonders. Participatory research allows for actual users to be in contact with the case study in previous stages. Instead of being informed after the study is finished. A factor that induced science to disconnect with the healthcare needs of society at large. From developing the research questions to interpreting the implications, translation experts from all over the world unite.
So, to have an artificial aid to get at least part of the job done is a blessing. Still, quality requirements lag in technical adoptions, privacy, and security are some of the reasons we don’t make the most out of it. But these reasons steadily lose weight. When should we use MT and when should we go full human?
Types of MT
Translation technology in healthcare is a popular subject. The medical industry is way over the national line and is bringing medical innovations to all kinds of markets. But “the medical industry” or “life sciences” and even “healthcare” are very broad terms. And so, there isn’t only one kind of Machine Translation and language technology. To mention a few:
– AI-enabled linguist selection: used for job interviewing processes. It can establish a profile of a specific language expert’s strengths and weaknesses. It matches this linguist to their particular and proven areas of expertise.
– Terminology management: It’s the ability to map specific terms to their foreign language counterparts to ensure consistency in translating medical documentation. The goal is to eradicate variations across documents.
– Translation memories: It’s all about keeping key terms and phrases in nearby storage. As the consistency of terms is found, it is also accumulated.
And these are only some of the advances we’ve had.
Paperwork MT: Human versus the Machine
One of the first items to be tackled was lengthy paperwork. The process of one person translating from one language into another, especially when it involves corporate and legal documents, can be very slow. If it’s a multilingual investigation, that means thousands of pages.
On the other hand, the speed and accuracy of AI are exponentially growing. Machine Translation technology can be used to remove unrelated or unnecessary documents from an investigation. And reduce human translation hours.
Still, most MT methods require many specs that we don’t always count with. While we humans are friends with chaos, handwriting, typos, and more. And healthcare is much too big a deal to blindly trust MT. It has yet a long winding road to the precision or nuance a team of human language experts can achieve.
Therefore mixing and matching and playing with this combination of strengths, is making us more efficient and fast paced.
Our daily bread
However, healthcare is not all jotted down notes and complex articles. It has a lot of office visits, scheduling, check-ins, and follow-up tasks. Some face-to-face meetings are sensitive and should be granted to a language expert. But some other interactions are very ordinary. MT saves money on low-risk encounters.
For now, research mostly considers MT inadequate for medically focused content. But for non-healthcare-focused communication, provides heaps of value.
In 2020, the demand for translation within healthcare increased by 49% due to the need to dispense and relay COVID-19 healthcare information. Top that with the fact that we humans are clumsy and tourists will be back to traveling. This means the rate of tourist injuries is likely to rise back to the 4.4 million the Post Office Travel Insurance noted in its study.
AI translation technology grants access to past medical records more quickly. And during emergencies, when there is literally no time to waste, they represent life-saving time. Therefore hospitals are being encouraged to introduce AI translation to treat patients faster.
The increasing volume of consumer data now available and need is undeniable. Data used to influence drug discovery, disease identification, global clinical research, and global disease outbreak monitoring.
All these seem like advocates for the greater good. However, there’s a concern about the risks involved. And the actual control we have over certain liabilities. For example data security aspects. Once something is translated using Google Translate, it is potentially available in the public domain. There are safer methods. Nonetheless, can we hands down vouch for them?
It’s a bridge we said we’d cross when we get there. And here we are. Making the most out of combining human mind power, automated translation, and advanced technology. With the sure belief, we’ll sort out every obstacle in the way in order to make safe progress.
If your company, medical institution, or healthcare enterprise needs some of this human mind power, our language experts at Stillman can help out.