They have existed for several thousand years, since the beginning of their appearance mathematicsbut its existence for the general public is linked to the technological explosion of recent years and especially to the leap in the development of artificial intelligence.
A recipe for pasticcio or moussaka is an algorithm. Directions from Tsimiski Street in Egnatia or Syntagma to a certain street in Chalandri are an algorithm. The term “algorithm” may sound like a puzzle meant to be solved by artificial intelligence scientists, but in reality it is simply a series of detailed instructions and logical commands to be executed by humans or machines. In fact, we learn many algorithms as early as elementary school: the instructions for how to add two numbers together are an algorithm.
“Algorithms are not a new invention. They have existed for thousands of years – since the beginning of mathematics – and were created to solve simple numerical problems. The oldest algorithm for dividing numbers is found on a Sumerian clay tablet from 2,500 BC. Algorithms developed significantly during the Hellenistic period, especially in arithmetic. The Sieve of Eratosthenes, dated around 200 BC, generates (through an algorithm) all small prime numbers (1,2,3,5,7,11,13, etc.). The Euclidean algorithm (300 BC) finds the Greatest Common Divisor. For ancient Greek mathematicians, arithmetic algorithms were a theoretical concern, something like the poor relation of mathematical theorems. They never imagined that their algorithms would be used as the theoretical basis of many modern cryptography and cybersecurity methods,” as AUTH’s Department of Informatics professor Ioannis Pitas, president of the International Academy for Doctoral Studies in Artificial Intelligence (AIDA), explains to APE-MPE. “
From simple addition and division to ideal drone flight
So why do we hear so much about algorithms today, when they have existed for millennia? “Algorithms have developed greatly with Information Technology, as they are converted into programs that are quickly executed on computers. For example, every mobile phone constantly executes many algorithms for its basic functions, for example, audio, image or video transmission. Furthermore, the study of the world and society, for example, the climate environment, brain neurons, robots and autonomous cars, is today largely done with a combination of mathematics and physics (and biology or chemistry, where appropriate, leading to mathematical models). The algorithmic study of these models helps to predict, for example, the economic size of a country or the ideal flight of a drone or the autonomous driving of a car. For the reasons explained, and because the “mathematization” of all sciences has advanced greatly, there is a huge need not only for IT specialists, but also for the acquisition of relevant training by almost all scientists”, he notes.
Thinking scientists, not professional robots
Algorithmic thinking, the professor notes, which today permeates to some extent almost all activities and sciences, is directly connected to mathematical thinking. “Both are part of critical and creative thinking, which must be promoted at all levels of education through the training of scientists and active democratic citizens. We need thinking scientists, with the capacity for abstract and creative thinking, imagination, emotional intelligence and correct expression, and not professional robots with a stylized way of thinking,” he stresses, adding that to date many governments around the world have chosen as a cheaper and faster solution (for example, with three-year undergraduate courses) the training of professionals, rather than the training of scientists and citizens. “Especially in Greece, the misunderstanding is deeply rooted, even among the majority of IT teachers in secondary education (sometimes also in HEIs), that IT is applications and programming. This misunderstanding is very problematic and leads to artisans instead of scientists, because it ignores the interconnection of Information Technology with Mathematics, which is essential, especially for NT”, he highlights.
He is pleased that algorithmic-mathematical thinking has recently been included in the Education Minister’s announcements, although the big question is – as he says – how the announcements will be translated into practice. “The proposed certificate in algorithmic thinking is very good, as long as it serves the general education of students and not just simple training. We need scientists with algorithmic-mathematical thinking who are also thinking citizens, otherwise we could end up with professionals with an overly stylized way of thinking, which the Germans call expert idiots (fach-idiot),” he notes.
According to Mr. – many fields of application. Furthermore, he continues, educational links with biology are necessary, but also with all other disciplines, especially linguistics and the humanities to a certain extent, because hardly anyone remains unscathed by Computer Science and IT. “Interdisciplinarity is a fundamental issue in algorithmic-mathematical thinking, especially in its philosophical, social, linguistic and psychological aspects, as long as it does not lead to a superficial view of science,” he stresses.
Omniscient superhumans?
Ultimately, however, are we asking for the creation of superhumans – supercitizens who will be omniscient? “No, this does not mean that all students will become excellent scientists, for example, computer scientists. I expect them to become excellent citizens, workers, professionals or scientists. The same scientific concepts can be taught at different levels and at all levels of education. To achieve these goals, of course, first of all teachers and teachers themselves must be trained, especially in computer science and partly in mathematics, because their old studies now have cognitive and value problems.
“There needs to be an effort from the Ministry of Education and proper planning to change the mindset of both IT teachers and students in secondary education, and to put IT and Mathematics teaching on their proper collaborative basis. The benefits will be enormous,” he argues, adding that if we want to optimize university studies in Computer Science, it is necessary to create a separate scientific area of Computer Science in national exams, which will feed the departments of Computer Science, Mathematics and Computer Engineering, and separate new departments of Artificial Intelligence.
Naftemporiki.gr with information from APE-MPE