About us
Artificial Intelligence
History of AI
The field of AI is very broad and multidisciplinary, we can currently find research on AI in several domains, i.e. medicine, genetics, robotics, and education. However, AI ideas in computer science date back 1950’s. The recent boom is particularly related to the availability of huge amounts of data and powerful computers to compute all this data (Russell and Norvig, 2010). Definitions of AI are still evolving but for the purpose of this programme, we can say that AI systems consist of pieces of software developed and coded by humans based on mathematics and statistics that use data to generate outputs (answers, predictions, recommendations…) or perform tasks (EU, 2022).
Machine Learning for Educators
“Machine learning can also be defined as the process of solving a practical problem by gathering a dataset, and algorithmically building a statistical model based on that dataset. That statistical model is assumed to be used somehow
to solve the practical problem” – Burkov, 2018
There are different types of Machine Learning (supervised, unsupervised, reinforcement) and techniques (i.e. deep learning, neural networks…) however those algorithms use data to “learn” from them and to give answers on data never seen before. Those algorithms use mathematics and statistics to do so. For example, if we want to have a model to classify cats from dogs, we should train the model with lots of cat pictures and dog pictures. A typical machine learning workflow consists of data preparation, training, test.
Image from Seeger et al.
AI big ideas
Research suggests that since an expert’s knowledge is built around core concepts and big ideas, then the curriculum should be organized in the same way (Bransford, Brown, and Cocking, 2019). The big ideas of AI for K-12 students are framed around five main concepts as illustrated below (Touretzky et al., 2019). Perception, Representation and reasoning, Learning, Natural interaction, and Societal impact. In other words, how a computer or a robot (also called an “agent”) uses sensors to gather information on the environment, how AI systems analyse data, find patterns and make predictions, how this software relates to humans, and what is the impact on our lives.
Image from https://ai4k12.org/
