127 Who was Alan Turing? How does the Turing test work? It was the Logic Theorist, created by Allen Newell, J.C. Shaw, and Herbert Simon. to draw: attingere paper: articolo accademico trial-and-error: apprendimento per tentativi ed errori unlabelled: non etichettato ARTIFICIAL INTELLIGENCE Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity, and autonomy. The beginnings The history of AI as a scientific discipline began in 1950 thanks to the work of Alan Turing , who, in one of his papers, asked the question Can machines think? and launched a test (which later became known as the Turing test ) according to which a machine could be considered intelligent if its behaviour, when observed by a human, was indistinguishable from that of a person. In 1956, during a conference held at Dartmouth College in New Hampshire, the term artificial intelligence was coined and AI started receiving significant attention from the scientific community. A year later, the first computer program with a basic AI that learned through trial-and-error was built. Developments In the 1980s, the concept of machine learning developed. This idea involved creating models by training an algorithm to make predictions or decisions based on data using neural networks. Neural networks are algorithms modelled after the human brain s structure and function and consist of interconnected layers of nodes (analogous to neurons) that work together to process and analyse complex data. In the 2010s a new advancement was made: deep learning. This subcategory of machine learning started using multilayered neural networks that could automate the extraction of features from large, unlabelled and unstructured data sets, and make their 284 PeoPLe aND INStrUMeNtS own predictions about what the data represents without requiring human intervention. Generative AI exploded in the 2020s. This gen AI uses deep learning models that can create complex and original content such as long-form text, highquality images, realistic video or audio and more in response to a user s request. Basically, these models encode a simplified representation of their training data and then draw from that representation to create new work that is similar, but not identical, to the original data. Benefits and risks of AI AI offers numerous advantages to be exploited across various industries and applications. Some of them include: automation of repetitive tasks; increased productivity and efficiency; wider and faster insight from data; enhanced decision-making; fewer human errors and reduced physical risks; 24/7 availability and consistency. Using AI comes with challenges and risks, too, among which: data integrity; malicious use of its capabilities; operational risks; ethical and legal risks.