What is Artificial Intelligence.docx

What is Artificial Intelligence? Throughout Europe, learners and educators increasingly use Artificial Intelligence (AI) systems, sometimes without realising it. Search engines, smart assistants, chatbots, language translation, navigation apps, online videogames and many other applications use Arti...

What is Artificial Intelligence? Throughout Europe, learners and educators increasingly use Artificial Intelligence (AI) systems, sometimes without realising it. Search engines, smart assistants, chatbots, language translation, navigation apps, online videogames and many other applications use Artificial Intelligence in our everyday lives. AI systems rely on data, which is collected in different modalities (e.g. sound, images, text, posts, clicks) and all together form our digital traces. AI has great potential to enhance education and training for learners, educators and school leaders. AI systems are currently helping some educators to identify specific learning needs, providing learners with personalised learning experiences, and helping some schools to make better decisions, so that they can more effectively use the teaching resources available to them. As AI systems continue to evolve and data usage increases, it is of utmost importance to develop a better understanding of their impact on the world around us, particularly in education and training. Educators and school leaders need to have at least a basic knowledge of AI and data usage in order to be able to engage positively, critically, and ethically with this technology and to properly use it to exploit its full potential. The definition of an Artificial Intelligence system (AI system) proposed in the draft AI Act is "software that is developed with one or more of the techniques and approaches (listed below) and can, for a given set of human-defined objectives, generate outputs such as content, predictions, recommendations, or decisions influencing the environments it interacts with". The listed AI techniques and approaches are: a\) Machine learning approaches, including supervised, unsupervised and reinforcement learning, using a wide variety of methods including deep learning; b\) Logic and knowledge-based approaches, including knowledge representation, inductive (logic) programming, knowledge bases, inference and deductive engines, (symbolic) reasoning and expert systems; c\) Statistical approaches, Bayesian estimation, search and optimisation methods.