How Artificial Intelligence Learns: Legal Aspects of Using Data in Machine Learning

An essential pillar of artificial intelligence systems, particularly machine learning systems, is data, which serves as the foundation for training, testing, and validating these systems. Data is not merely a technical construct; it is a multifaceted concept that encompasses significant legal implications. These implications arise not only from the processing of personal data but also from a broader range of legal concerns linked to automated data processing. This paper explores the legal dimensions of data quality, data justice, and the protection of intellectual property in the context of data deployment by machine learning algorithms.