And what does this mean for businesses? That they have an easy, cost-effective opportunity to expand their reach, for one. But there’s more to it—machine translation can now be at the front line of market research, helping companies feel out their target audience in different languages at minimal cost, before they invest more resources into full expansion.
The possibilities of machine translation in marketing are now greater than ever, and businesses need to learn how to best harness it for quick growth.
Often, when we think of machines and AI, we tend to think of them as emotionless, logically-driven systems that are more objective than humans. This is one of its strengths compared to more subjective, more irrational human processes, but it can also be a weakness.
But it’s become increasingly clear that AI is not, in fact, as objective south africa mobile database as we think, and they are increasingly shown to reflect biases in their operations that are all too human.
In this article, we will talk about the paradox that is machine translation bias and why it’s a problem that MT developers and stakeholders need to address.
What is “bias” in the context of machine translation?
In common usage, bias is defined as the tendency to make prejudiced assumptions or have prejudiced inclinations toward someone or something. There is a negative connotation to the term, in that biases are often unfair and discriminatory.