AI Implications in Satisfying Digital Skills Training Needs Through OER

Open education is a catalyst for meeting the global demands for education. One of the current problems that affects a large part of the population and market is their shortage of digital skills. Among the main challenges that Open Education aims to is facilitating the discovery of relevant educational resources, attending to the needs of those affected. For this, the quality of the repositories of OER (Open Educational Resources) and the interoperability between them must be ensured. The main solutions provided by AI in this context have as main obstacles the poor quality of the data, and how to deal with the ethical implications. Data quality is crucial in AI because it directly affects the performance, accuracy, and reliability of your models. In our context, high-quality OER metadata allows the models to make better predictions and produce more reliable results, fostering trust among users. This paper explore quality and ethical implications in a case of application of AI techniques to improve the accuracy of searches requested by educators and students.