AI continues to reshape the language industry landscape. With over a year in this most fast-paced round of the transformation, Nimdzi teams up with GLOBO in this Nimdzi Live episode to talk about AI and interpreting.
Dipak Patel, the CEO at GLOBO, has over 20 years of experience in health tech, consulting, and private equity. In the 2024 Nimdzi 100 report, GLOBO was ranked as the second fastest-growing language service provider and the sixth largest healthcare interpreting provider in the U.S. Its mission is to help organizations communicate across languages via its easy-to-use app, GLOBO Connect, and supplement them with trusted data insights through its reporting platform, GLOBO HQ.
Ewandro Magalhães is a global language specialist at Nimdzi. With over 30 years of experience, he has held various roles, including Chief Interpreter in the United Nations, a writer, and a TED speaker. He is also the co-founder and the Chief Language Officer of KUDO, a platform to add live interpretation to online and hybrid meetings.
In this episode, there was a huge emphasis put on the competencies of AI interpreters and what might be long-term consequences of relying on such technology in interpreting. Consensus? Human translators are not going to be substituted just yet; but AI is going to fill in the gaps where no interpreting was offered before, allowing speakers to return to their native tongues and helping people get access to data in a fast and cost-effective way. However, without a universally accepted quality standard for human interpretation, it is difficult to determine how AI interpretation truly compares to a human interpreter.
One of the questions investigated whether AI interpreters can effectively capture the nuances of language and the emotions the speakers want to convey. The experts agreed: the challenge lies in understanding when to express emotions and then how to express them across cultures, and AI still struggles with that. There are, however, some great improvements that AI can bring to the interpreting table. With its great capacity to analyze and compare lots of data in a short time, it already is a great aid to human interpreters.
Dipak and Ewandro have also raised the issue of the responsibility of humans in keeping up the quality of AI interpreting results and its training process. “The tool is just as good as the data it is fed” stays true in one more case. It is especially important in case of the possibility of perpetuating hateful or discriminating terms and language. But hopefully, there is much room for improvement: AI works great with safety measures, such as word-detecting systems or forbidden terms lists, outperforming its human counterparts in this area.
So, while it is not going to outperform human translators just now (or in the next 2 to 3 years), it is definitely going to be part of the landscape, serving human interpreters to provide yet better results. Our experts have meticulously broken down the expectations into real-life observations and offered the audience a chance to look at a change from a dual perspective – of a human and artificial interpreter.
Watch the full recording here to uncover all of the insights and enjoy the full perspective.
