Writer: Menelaos Gkikas
Happy New Year creatives, marketers and science people! Today’s scientists as well as creative digital marketers are quested not to invent the wheel and furthermore, learn the lessons of digital transformation in the 21st century, align with hybrid visual development solutions in AI and focus on better productive models. Let me just state my inspiration of how the entire today’s discussion started!
AI cannibalizes its own foundations as well. From the very moment we came up with Gemini and ChatGPT, the era of developers stochastically theorizing for weeks to produce one simple piece of code started to erode. Why should we need over 1 week to stochastically theorize for commands over one piece of code, when we can put the task into ChatGPT, produce the program, fix the code on our own and come up with a solution in less than 1 hour? This disruptive change in traditional programming and industry shifts is boosted by software platforms that function as hybrid visual development asking for tinier code samples together with object-oriented tasks, as well as the need of outsourcing digital marketing to independent martech as long as we conceptualize effectively our bottom need which is data, meaning, data production displayed with a data production line.
No matter the industry, for a computer to produce effective data, means that all its components function harmonically and effectively together that is the same logic with a production line inside a food industry. You can’t override the daily tasks of the factory and if they’re not daily, weekly or bi-weekly…
For digital marketers, we need content production. This means scripts, photos, music, videos. This production line has to be followed and applied regularly inside our mediums and from the very moment of regular flow, digital tools like Google Analytics are immediately activated and authorized to display qualitative and quantitative data.
The above truly mean you have activated machine learning, data analytics and AI qualitative and quantitative data further deployed with extra martech and SEO and digital PR tools.
Data flow on the other hand, a time-dependent dynamical system, reminds us something from differential equations possibly redirecting our thoughts to the Schrodinger equation in quantum physics. Here we have elements of the connections of advanced math to how data scientists think with data and numbers evolved… Different notions in data shift to different notions in equations. If you wake up one day and you’re in the mood of thinking whether you shall make articles about Cirque du Soleil or K-Means Clustering AI, means that your perception on what to talk about shapes outcomes…! If you could model that, perception shaping outcomes means pure quantum physics.
But what about the real logic and the rationale of bridging creative digital marketing with STEAM education initiatives? Pay attention to the following bullets:
1.) Martech
Complex digital marketing happens with tailor made complex technologies. To scale-up digital marketing projects means to carefully outsource expertise to low cost or free outside products in terms of SEO and outreach campaigns, digital PR, analytics as well as manual programming.
2.) Hybrid Visual Development
Coding is no longer king. The era of conceptualizing for weeks and thinking you’re Schrodinger only to write essential code is now gone. This does not mean we don’t need programming. It means programming should be combined with complex visual development products.
3.) Traditional Programming Starts Becoming Obsolete
The evolutions in AI in the last 10 years start threatening traditional programmers. Tools like ChatGPT, Gemini and automated production of code start to emerge, that make the demand for programming less and shifted to more valuable options. Which brings us to the next bullet argument.
4.) AI cannibalizes its own roots
The previous do not mean we don’t need math and programming. If we live in the 4th industrial revolution of AI, then coding and math are part of that AI as well. It just means that not ‘you’, but ‘other’ coding and science examples will survive.
5.) Data Vs Mathematics
It’s important to think like a data scientist. Different notions in data are equivalent with different parts in mathematic equations. For example, we know even before we enter the university that f is defined as the derivative of F and we learn statistics in university that say that this f is the probability density function of the cumulative distribution function F, the major definition of all statistics and since we know differential and integral calculus, F can be expressed as the integral of f. Here, we have founded math for data analysis. Using the same logic we should seek equivalences of data flow with a differential equation and possibly seek the differential equation of Schrodinger in Quantum Physics. Less exercises and problem solving as a university student and more like applying elemental basic principles.
6.) STEAM Education As Content
Science and especially STEM are being defined quantitatively. Nevertheless, equations in books and courses are classified as general statistics that may not comply with the unique example of us, furthermore, they do not comply when we make our own single measurements. Unique measurements may be something else completely. So, it’s important to embrace science as content and see what we can learn as digital marketers by other products that incorporate metrics, not inventing the wheel on our own.
7.) Redefining Science & Coding
In the 21st century of the 4th industrial revolution we’ll be needing less coders and more scientists. It’s important to bridge the gaps and apply inclusion successfully but it’s also important to focus on the science and codes that matter, not on our personal story…
8.) Paradigm Shifts
All the previous mean that as we live in the age of computers, there will be other paradigms that will lead the reigns of evolution and these paradigms will not be the same with the previous generations or the scientists and coders that have been left behind.
9.) Why Digital Marketing
Projects need ROI and Lead Generation. The same counts for the entire company as well. A big company that cannot sell anymore, faces the risk of closing down operations. My personal evaluations on the other hand say that heads of marketing and heads of companies will not allow complete and hostile take overs by AI… Electronic commerce will not beat physical commerce and physical presences completely in all industries. It’s just that there are paradigm shifts, new equilibrium points defined and we have to comply with disruptive change modelling and digital transformations. All the previous bring at the frontiers of the revolution marketing and digital marketing.
10.) Acceptance Vs Reinvention
It’s not what you say it’s how you say it and more specifically the delicate way you will serve it to others. Discovering the how and the mediums to apply STEM are more important than saying your lesson as a university parrot. Meaning, to discover what’s truly important in science and how it’s applied rather than merely applying your classroom contents by-heart.
11.) Nature’s Smarter Than People Think…
We cannot defeat science and science will defeat us more if we override it. Whatever you abandon, it abandons you. Future generations will be heavily science oriented, so it’s important to realize not only the mediums we use but the fact that today’s scientists are a ship that finds no harbor for we are making wrong usage of our tools. We have to thoroughly investigate our previous and current tools before we venture with new ones and more importantly, science is not for the faint at heart. Science is for the brave ones, so make brave choices and let the future evolve at its own…!
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