Paradigm Change Ahead
It is both a blessing and a curse to live in interesting times. Today, we are not just in interesting times; we are in a time of paradigm change. Much like the eras of Copernicus, Tesla, or the advent of the internet, those who fail to adapt risk extinction — not as a species, but as individuals.
This series of columns is intended for individuals. You, yes you, have found this and are reading it, seeking some personal value. Whether you aim to be amused, engaged, or motivated, this series explores the fantastic new phenomenon of Generative AI and its role in reshaping how people learn and gather personal knowledge in any area of interest.
I deeply believe that Generative AI, even today, will make a huge difference, potentially changing the paradigm of knowledge acquisition. This change is not about content availability or intensity, as the internet/Google era has already addressed those. The shift lies in consumption.
I see Generative AI as the last missing piece, with its ability to adapt to each individual’s capabilities and learning style. It will serve as a true personal (not institutional) teaching assistant — always available and free!
However, we need to master its use, and that is what all future columns will focus on.
Innovative Education
Innovation in education is a constant buzzword. Innovative teachers and innovative methods are often touted, but innovation is not about technology or Generative AI. It never was!
Innovation is also not about originality, new ideas, or new methods. It is not even about new products or services. It is about value — whether it brings value (or not) to users (pupils, students, teachers, professionals, and everyone). This is one of the greatest misconceptions, and I want to clarify this from the very start.
I was fortunate to be influenced and educated by several extraordinary math teachers in primary (Stjepan Vuk), secondary (Branimir Jelić), and university (Vladimir Kirin, my Logic teacher and mentor). They did an excellent job teaching the required curriculum. But, only now, from this perspective, I do understand how innovative they were! Each, in his unique way, taught me to love, learn, and live mathematics. This is the essence of their job, not written in any official learning outcomes. As Antoine de Saint-Exupéry said, “If you want to build a ship, don’t drum up people to gather wood, divide the work, and give orders. Instead, teach them to yearn for the vast and endless sea.”
Of course, they knew nothing about Generative AI, yet I credit them gratefully and proudly.
Personalized Knowledge
It has always been the case that what I know (think I know, believe, stand for) is my personal knowledge. And that is all that truly matters!
There is general (not ultimate) knowledge, agreed upon by society, but it is not ultimate and changes as society evolves. This primary applies to humanistic and social, but natural, and technical knowledge as well. This is why I mentioned Copernicus.
To gain knowledge, we all attend school, then university, studying an approved corpus of knowledge divided into various disciplines, taught by educators trained to transfer this knowledge to us. Each individual, with its own background, interests, and abilities, receives the same education. Which is good, of course, one of most important society achievements. But not at its own pace and depth. And, at the end of the educational cycle, the only measurable difference is a grade, which confirms our competence.
But the real aim is a personalized way to navigate the entire educational period (8–20 years!). It is too much time we have to adopt to the system, now we finally have a tool to ease, until free us, for our own, individual benefit!
When I insist that knowledge is personal, I mean that while grades, certifications, and diplomas are personalized in a uniform way, true knowledge is measured differently. It is assessed by your ability to demonstrate it, defend your stance in a debate, or influence others.
It is not about how you acquired it, but how you defend it!
Stand by Your Knowledge
This first column serves as a prologue, setting the scene and understanding the basic context we will further develop on.
Disclaimer!
I am not speaking on behalf of any institution or pleading for any change (though it will come, the sooner the better). I am simply expressing my thoughts, based on my knowledge and experience, regardless of when and how I acquired it. Some thoughts are backed by scientific literature, some by popular articles, and most are simply mine. I am rarely sure how or when I developed them, but I stand by them with my reputation.
This principle also addresses the dilemma of using knowledge generated by Generative AI. You simply sign it with your name and stand behind it, for better or worse, without needing any disclaimers.
Simple, isn’t it?
Knowing More
· Paradigm Change: A paradigm change refers to a fundamental shift in the approach or underlying assumptions of a particular field. This concept was extensively explored by Thomas Kuhn in his seminal book The Structure of Scientific Revolutions (1962). Kuhn argued that scientific progress occurs through a series of revolutionary changes rather than a gradual evolution. He introduced the idea of “paradigm shifts,” where an existing framework is replaced by a new one that better explains the observed phenomena. As Kuhn stated, “The transition from a paradigm in crisis to a new one from which a new tradition of normal science can emerge is far from a cumulative process. It is rather a reconstruction of the field from new fundamentals.”
· Why Engineers Should Study Philosophy: In a rather unexpected, yet valuable insight, Harvard Business Review author Marco Argenti explains that an engineering career benefits from studying philosophy, as it enhances the ability to create clear mental models and deeply understand problems, which is crucial in the age of AI. Although AI excels at coding, the quality of its output relies heavily on well-crafted prompts, making prompt engineering an essential skill. As AI democratizes access to knowledge, the importance of reasoning, logic, and critical thinking increases, ensuring users can guide AI effectively and discern accurate information from plausible but incorrect outputs.
· Antoine de Saint-Exupéry: Antoine de Saint-Exupéry was a French writer best known for his book The Little Prince. His famous quote, “If you want to build a ship, don’t drum up people to gather wood, divide the work, and give orders. Instead, teach them to yearn for the vast and endless sea,” emphasizes the importance of inspiration over mere instruction.
· Generative AI: Generative AI refers to a type of artificial intelligence that can generate new content based on the data it has been trained on, such as text, images, or music. This capability enables it to adapt to individual learning styles and provide personalized assistance, transforming how knowledge is consumed, understood, adopted and applied.
Where are the references, resources, links …?
This blog is written under No easy answers policy!
If you really want to know more, I believe this Generative AI summaries (under my revision) have enough reference points to google original source or someone you believe/trust and do minimum effort to do small private research. It is good practice as well 😊
But if you do have questions, I am more than glad to answer in comments or private message.
