Data literacy and artificial intelligence – biases and limitations

As AI systems collect, analyse, and interpret large amounts of educational data, every step in the process must be grounded in accountability, transparency, and respect for the privacy of students and teachers.

Adherence to the Principle of Transparency
All participants in the educational process should be clearly informed about how AI systems use their data. For example, students should know why data about their progress is collected, how it is processed, and how the system generates personalised recommendations or feedback. Transparency is essential for building trust and acceptance of AI technologies in education.

Obtaining Informed Consent
Data collection and processing are permitted only with the free and informed consent of the data subjects, in accordance with ethical and legal standards such as the General Data Protection Regulation (GDPR). Students should have the right to know what information is collected, how long it is retained, and for what purposes – especially when the data is used to train or adapt AI systems.

Ensuring Privacy and Data Security
When AI analyses educational data, it is essential to ensure that all data is adequately protected from unauthorised access, loss, or misuse. Security is achieved through technical and organisational measures such as encryption, anonymisation, and the use of trusted storage and processing systems. For example, when analysing student engagement in digital systems, students’ identities should remain hidden to preserve their privacy.

Promoting Fairness and Accountability in AI Systems
AI systems in education must be designed and implemented to prevent discrimination and bias. Regular testing and evaluation of models are necessary to verify that AI decisions are fair and aligned with pedagogical goals. For example, if the system recommends additional educational content, it is necessary to ensure that the recommendations are equally accessible to all students, regardless of their previous results, sociodemographic characteristics, or language abilities.

The Role of Teachers and Students in the Ethical Use of Artificial Intelligence
Teachers and students share the responsibility for the ethical handling of data and AI technologies. Teachers should ensure a safe digital environment, encourage open discussion about ethical challenges, and critically examine the results generated by AI systems. Students need to develop awareness of the importance of protecting personal data and understand how their interaction with AI tools can affect their learning experience.

Data literacy in the context of artificial intelligence involves not only understanding the technical processes of data collection and processing, but also recognising the biases, ethical challenges, and limitations that these systems carry. Only with a thoughtful, responsible, and transparent approach can it be ensured that artificial intelligence in education contributes to the creation of a fair, safe, and supportive learning environment.