stub Beyond AI Technophobia: Formation of Citizens and Global Education Uplifting - Unite.AI
Connect with us

Thought Leaders

Beyond AI Technophobia: Formation of Citizens and Global Education Uplifting




Currently, there is a public surge of interest on any Artificial Intelligence (AI) topics, especially those related to Large Language Models, like ChatGPT [1]. This is not a random development: AI is here to stay and will have huge social and economic implications. It is well known that AI can be a blessing but can also turn into a curse.  In view of its potential dangers, many AI scientists expressed their concern over AI developments in a way, which, in my view, borders technophobia. However, there are lines of defense. The first one is global AI regulation. However, the real defense and way forward is the formation of a new breed of well-educated and informed citizens. This article precisely addresses the relationship between AI and a necessary (in my opinion) revamping of the global educational system at all levels.

AI is humanity's response to the increasingly complexity of our globally interconnected society and our man-made and natural environment. The growth processes of physical and social complexity are deep and seemingly unstoppable.  Our current Information Society (where data increase exponentially but knowledge increases linearly over time) is rapidly transforming into a Knowledge Society (knowledge-dominated one, where knowledge is expected to increase exponentially). AI and the morphosis (formation) of knowledgeable citizens are our only hope for such a smooth transition. I deliberately use the Greek term “citizen morphosis” to emphasize the need to educate citizens equipped with critical thinking, precise multimodal communication skills, imagination, and emotional intelligence who will be able to understand, adapt, and ultimately harness the tremendous technological and economic possibilities and employment prospects that lie ahead of us. It is no coincidence that such a level of education is sought after today in many job positions internationally [2].

This need permeates all education levels of all social strata. A society divided into 1/3-2/3, where 1/3 of the population understands and benefits from scientific progress, while the remaining 2/3 lags, being impoverished and technophobic, is simply not sustainable, as it cannot guarantee the advance and take up of knowledge at global level. All people should reap the benefits of knowledge, including women, minorities and people of the Global South. Else, we may face a catastrophic social implosion, as happened, for other reasons, in the early Middle Ages.

Fortunately, the basic concepts necessary for understanding AI and Information Sciences (e.g., data similarity, clustering, classification) are simple and can be taught at all educational levels. If properly taught, they can easily be grasped even by uneducated people. This will greatly combat ignorance and AI technophobia.  Such an educational advance simply requires political will and educational readjustment to provide suitable teaching of these concepts, primarily through rearranging the Mathematics and Informatics curriculum at all education levels. Of course, we already observe a (partial) mathematization of all Sciences (including the Liberal ones), which seems inevitable. It is not certain that it is feasible, given the traditional separation of  Sciences/Engineering and Humanities in all education levels. However, it can be doable, as, besides Mathematics, Classical Studies are an ideal tool for developing critical thinking and precision of expression. Naturally, in such an environment, naïve knowledge memorization, or the educational offering of skills at the expense of a broader and deeper knowledge acquisition have no place.

In University education, the changes will be drastic and will come very soon (most of them). I present some proposals that I have detailed in my book ‘AI Science and Society' [2], which was published in October 2022, and I dare to say or hope that they were prophetic.

1. Creation of Schools of ‘Information Science and Engineering' with Departments of:

  • Informatics
  • Mathematics
  • Computer Engineering
  • Artificial Intelligence Science and Engineering
  • Internet/Web Science.

Such efforts are already being made internationally, as can be seen in Figure 1. Although driven by demand, the fundamental cause for such a development is the recognition of ‘information’ (and knowledge) as an independent scientific subject, on the same level as matter (Physics, Chemistry), environment (Engineering Sciences), and life (Health Sciences, Biology). It seems that Computer Science (called Informatics elsewhere) is already becoming the mother science of other disciplines, e.g., of Artificial Intelligence Science and Engineering. The same happened in the 19th century: at that time, Physics and Chemistry gave birth to all Engineering Sciences.

Figure 1: Number of undergraduate AI programs worldwide.

2. Creation of Departments for ‘Mind and Social Science and Engineering' in Schools of Arts and Humanities (perhaps a more suitable term can be used). I believe this is my most groundbreaking proposal. Currently, the Humanities face the greatest pressure from AI advances, which may not be immediately apparent. Indeed, the mathematization of classical subjects (e.g., Linguistics, Sociology) has advanced significantly. The creation of ‘Digital Humanities’ Departments would be another good choice. Otherwise, the only alternative I see is the creation of departments for ‘Philological/Linguistic Engineering' or ‘Social Engineering' in Natural Sciences or Engineering Schools. Being a fan of classical studies (though engineer by training), I would not like to witness such a demise of Humanities Schools.

3. Creation of departments for ‘Bio-Science and Engineering' in Schools of Health Sciences. Essentially, this would be a radical evolution of Biomedical Engineering Departments with the addition of new subjects, such as Genetic Engineering and Systems Biology.

4. Mandatory inclusion of Mathematics and Computer Science courses in the curricula of all disciplines without exception. Simply, one or two (poor) courses in Statistics or Programming do not meet the current needs.

Some of the above proposals (not all) have already been suggested or implemented at the international level. Given the inertia of the global educational system, I am not naïve enough to believe that such ideas can be implemented without reactions or overnight. However, these proposals (or even better ones) can be discussed at a political level and within the Universities themselves (at a scientific level), so that each country can enter the upcoming Knowledge Society era with the best possible prerequisites.


[1] Ioannis Pitas, “Artificial Intelligence Science and Society Part A: Introduction to AI Science and Information Technology“,

[2] Ioannis Pitas, “Artificial Intelligence Science and Society Part C: AI Science and Society“, Amazon/Createspace,

Further reading

[PIT2023a] Ioannis Pitas, CVML short course, “AI Science and Engineering and its Impact on the Society”,

[PIT2022] Ioannis Pitas, “AI Science and Engineering: A new scientific discipline?”,

[PIT2023b] Ioannis Pitas, “ChatGPT in education”,

[PIT2023c] I. Pitas, “Artificial intelligence is not the new Tower of Babel. We must beware of technophobia instead”, Euronews, 8/5/2023,

Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) is Professor at the Department of Informatics of AUTH and Director of the Artificial Intelligence and Information Analysis (AIIA) lab. He served as a Visiting Professor at several Universities. He has published over 920 papers, contributed to 45 books in his areas of interest and edited or (co-)authored another 11 books on Computer Vision and Machine Learning. He is chair of the International AI Doctoral Academy (AIDA).