The Limits of AI in Interpreting Spoken Language: Why Human Interpreters Are Still Necessary

Artificial intelligence (AI) has made significant advances in the field of language translation in recent years, with machine learning algorithms able to accurately translate large volumes of text from one language to another. However, while AI may be able to perform some tasks traditionally carried out by translators, it is unlikely to fully replace the role of human interpreters in the near future.

One of the main reasons for this is the complexity of interpreting spoken language, which requires more than just a thorough understanding of grammar and vocabulary. Interpreters must also be able to listen to and understand spoken language in real-time, accurately conveying the meaning and intent of the original message. This requires a range of skills that are difficult for AI to replicate, including the ability to understand and interpret local dialects, idioms, and cultural norms.

For example, when working with international organizations such as the United Nations (UN) in the Middle East, interpreters may be called upon to work with local dialects such as Iraqi Arabic, Egyptian Arabic, or Syrian Arabic. These dialects can vary significantly from standard Arabic and may include unique idioms and expressions that are specific to the region. An interpreter who is familiar with these dialects and their cultural context will be better able to accurately convey the meaning and intent of the original message to the target audience.

In addition to understanding local dialects and idioms, interpreters in the Middle East may also need to be familiar with the socio-economic status of the people they are working with. For example, in some areas, there may be significant disparities in wealth and access to education, which can impact the way people speak and the words they use. An interpreter who is aware of these differences will be better able to accurately convey the message to the target audience.

Overall, while AI may be able to perform some tasks traditionally carried out by translators, the complex nature of interpreting spoken language means that it is unlikely to fully replace the role of human interpreters in the near future. In order to accurately convey the meaning and intent of spoken language, interpreters must be able to understand and interpret local dialects, idioms, and cultural norms, something that is difficult for AI to do.