AI-Powered Language Learning

Abstract

Artificial intelligence in language learning has greatly improved education by providing instant translation, individualized learning, and a better way to communicate with people from different cultures. However, the use of this technology comes with some serious ethical issues that need to be discussed. The following paper aims at exploring the ethical frameworks that control the use of AI in language learning, with focus on the Utilitarian approach which is based on the consequences of an action and the effects it has on the majority. It is evident that the AI tools like Google Translate and DeepL are biased in the gender, culture and language they use and can have some implications on the user’s privacy. Such biases not only lead to the wrong conveyance of the intended message but also hamper the process of learning about the real nuances of the language and culture. To overcome these challenges, the paper recommends the following solutions which are specific to various actors. First, AI developers should make sure that diverse data is used in training algorithms and explainable AI should be used to increase the understanding of the models. Based on this, educators are told to include AI critical literacy in their lessons so that students can use the tools critically and not rely on them to complement the vital human contact that is involved in learning. Furthermore, it is recommended that policymakers should establish policies that govern the use of ethical AI in education and should encourage the creation of open-source AI tools that can help in reducing the cognitive bias that comes with the commercial tools. These measures are important to guarantee that the language learning systems based on AI are fair, efficient, and ethical. Therefore, while the application of AI in language education can be viewed as revolutionary, for the benefits to be maximized, responsible innovation, data transparency, and cooperative regulatory mechanisms are necessary. Further research should also be conducted to examine the ethical issues associated with the use of AI in education and ways of addressing them, as well as to design new strategies to further integrate ethical considerations into AI design and implementation.