Introduction.
In this article, I will briefly touch on what separates natural and artificial intelligence, exploring how these two forms of “smartness” learn, adapt, and interact.
Intelligence – it is something we attribute to both humans and machines in these days. Do not be surprised, it is already existing. I am not here to explore some “likely story” or immerse into science fiction. Instead, l will stick to the facts as they happening in the real world today and around us.
In other words, machines are intelligent and smart right now, “almost “just like we, humans! It is named artificial Intelligence (AI) as probably everyone already knows.
On the one hand, we have got something special named – natural intelligence (NI), which has evolved over millions of years, and on the other, artificial intelligence (AI), a creation of human creativity and imagination that has been around for just more than a few decades.
As technology penetrates every aspect of our lives, understanding the distinction between the two is not just an interesting intellectual exercise – it is also crucial. We are living in times where AI is not just changing our lives, it is reconfiguring what we even consider as intelligence.
It is also co-creating the future! With us and our involvement if we are in, or without us.
Whether “human-in-the-loop” or “no-human-in-the-loop” the digital world is evolving and changing.
We still have our voice and the ability to choose what we like, dislike, or want to do, but we must remain aware, sharp, well-educated, and active to reap the rewards of such liberty and freedom.
However, we should recognise that the window of our liberties may shrink and narrow over time.
I am going to highlight their unique mechanisms, limitations, and where this evolving relationship might or might not lead us.
Defining Intelligence.
What exactly defines intelligence generally speaking?
Intelligence is the ability to learn from experience, solve problems, adapt to new situations, and apply acquired knowledge in meaningful ways.
For us humans, intelligence is not just about facts and numbers, tokens, or vectors – it is creativity, empathy, intuition, gut feelings – all those qualities that make us human.
Natural Intelligence (NI)
When we talk about natural intelligence, we are referring to the sum of human cognitive abilities – learning, reasoning, and understanding.
Human intelligence has been shaped not just by our biology but also by cultural evolution, occasionally interrupted by powerful revolutions. You may think of it as an ongoing collaboration between our genes and our environment, which shapes and models how we perceive, think, and make decisions.
Our intelligence may be considered a bit messy and emotional. Same time beautifully adaptive-driven by millions of years of natural selection, polished through collective experience and refined by our differences in cultures and societies.
In contrast, machine thinking is based on probabilistic techniques, while we humans use logic.
Sadly, the use of logic is a skill that is gradually disappearing and becoming forgotten by constantly busy-to-death and mobile-addicted humans. However, I strongly recommend revitalising and re-applying these old fashion techniques!
Remember – the magic word is Logic!
If people do not follow logic, they gradually become zombies or organic sort of machines.
Artificial Intelligence (AI).
AI is a tech-driven attempt to replicate or even surpass human-like intelligence.
Born out of mid-20th-century computer science, AI is modelled on the way we think humans process information.
But AI is fundamentally different – it processes in a linear, structured manner, theoretically free from emotions (by the time of writing), or biases (ideally).
By the way, I was “discussing” with a couple of LLM models the existence of vector emotions and probabilistic feelings. You may be surprised to see what the output was! But the content of such discussion is far beyond the topic of that article.
We may talk about various types of AI.
Narrow AI, which performs well in specific tasks, like recommending something, proposing, or predicting.
We are also witnessing the birth of general AI (AGI), the goal of machine learning. This idea of a machine that is as flexible and smart as a human, adapting to new scenarios without being explicitly programmed.
AGI is triggering sometimes a hot debate whether true general AI is feasible or maybe even dangerous. But if you afraid of AGI what about Super AGI?
My daughter whose name is Agnieszka, used the nickname AGI a long time ago. So, it is reminiscing happily in my case, and I am not so scared of AGI.
Nevertheless, as always there are a few possible scenarios and possible positive and negative outcomes.
In my private opinion fully loaded general AI is inevitable and elements of it probably already exist.
To support my statement, try to use a simple human logic and apply it to what you see is happening right now. If you are accustomed to use a logical thinking – the answer should become clear.
Will the super-intelligent general AI one day outsmart humanity itself?
Yep, that is a very important question, and I think it may do, in many cases.
May it be dangerous to humanity?
Yep again, it may be – why not.
There is always a probability of good and bad AI and good and bad actors/players behind it.
If a bad one dominates or escapes out of control and starts evolving itself without-human-in-the-loop – “we may have a problem, Huston”.
But it is just theoretically bad scenario, based on Murphy’s Law.
I still love AI and hope AI love me too.
Agentic AI and the existence of AI-agents.
Instead of just coding and instructing computers on what to do, we’re now teaching them how to think and act.
AI agents are a current way of building intelligent systems.
They leverage LLMs and blend automation and cognition into tools that do not only follow commands – but they also reason, make decisions, act, and learn over time from it.
Machines “learning on the fly”, how awesome it can be?
On top of that, there is no one type of agent, there are hips of them with different levels of functionality and operability.
About half a year ago I started to write the paper titled “The Anatomy of AI and AI Agents”. Need to finish it before it becomes too obvious.
Comparing Mechanisms.
How do NI and AI learn?
Human intelligence is rooted in the brain’s neural pathways. We grow and change as we learn, forming new connections that reshape how we think and react. It is all about the intricate web of neurons and synapses that adapt over time.
Meanwhile, AI learns through neural networks, which were inspired by the human brain but are not biological at all. These networks process data and find patterns, getting better with experience (a process we call “training”).
Then there is decision-making.
Humans often rely on a blend of intuition and logical reasoning, weighing factors subconsciously, influenced by experience, emotions, and sometimes, premonitions, plus so-called gut feelings.
AI, as it is per now is all about algorithms – devouring numbers to arrive at a decision, following its training and rules, and without human uncertainty and subjectivity.
If I have gone too far, feel free to ignore it – but, please do not stop reading!
Probabilistic thinking vs Human logic.
AI probabilistic thinking and human logic differ significantly across reasoning, data handling, certainty, learning, and ethics.
Humans use deductive, inductive, and abductive reasoning influenced by emotions, culture, and biases, often leading to intuitive but sometimes flawed judgments.
AI relies on probabilities and data patterns, making decisions purely algorithmic but reflecting training data biases.
Humans shine in making decisions with minimal data and leveraging intuition, while AI usually blossom on large datasets, identifying subtle patterns but struggling with insufficient data, especially when data are poor quality.
Data Handling.
Humans can often make decisions with very little data or even extrapolate from a single instance due to cognitive abilities like analogy or metaphor.
However, this can also lead to errors, biases, or even catastrophic consequences.
AI requires large datasets to make accurate predictions. Its effectiveness usually (but not always) increases with more data, and it can handle complex patterns in data that might be too subtle for humans to notice. However, without sufficient data, AI might struggle or make less accurate predictions.
More Data Handling.
Not every human can see, chase, and follow patterns, or lack of patterns. I do.
It happened to me after I graduated from the University in Krakow. I like it, get used to it, and apparently, I am good at it!
I think almost everyone, may learn and practice it too.
Warning: it can lead to sort of paranoid thinking if not handle properly, so always use this technic carefully and in moderation.
Occasionally, we humans hallucinate too.
Data processing.
Humans operate effectively amid ambiguity, often relying on intuition, whereas AI quantifies uncertainty through probabilities but lacks adaptive flexibility in novel contexts.
We humans continuously learn and adapt intuitively, considering ethics and morality influenced by societal norms.
AI, however, requires design-specific algorithms for adaptation and lacks intrinsic ethical understanding, operating within programmed boundaries.
A hybrid approach combining AI’s data-driven precision with human intuition and ethical insight may offer very interesting outcomes IMO.
Certainty and Uncertainty.
Humans often seek certainty or at least a level of confidence in their decisions, but they can also operate effectively in ambiguity, using intuition or hunch.
AI deals with uncertainty through probabilities. It can provide confidence levels in its predictions but doesn’t “feel” uncertain or confident – it simply outputs probabilities.
AI can handle and quantify uncertainty better than humans in many scenarios, but it might not adapt as flexibly to completely novel situations outside its training data.
In the real world with a novel scenario – humans surprisingly do.
Ethics and Morality.
Human decision-making often involves ethical considerations, moral judgements, and societal norms, which are deeply ingrained and culturally dependent.
AI by the time of writing, lacks intrinsic ethics or morality. It can be programmed to follow ethical guidelines or predict ethical outcomes based on data, but it doesn’t inherently understand or feel these concepts, yet.
If you happen to read it a couple of years from the day I am writing it, it may be untrue – completely different. It would only confirm my predictions and highlight the beauty and power of learning.
Applications and Implications.
In society, we have witnessed AI complement human intelligence in various fields. It is very slowly changing healthcare delivery, enhancing diagnostic accuracy, and even recommending personalised treatments.
In education, AI-driven tools are personalising learning experiences and automating scoring in ways we could not have imagined a decade ago.
Mentioning AI as a general generative tool is far beyond the capacity of that article.
You can generate almost everything, just choose a decent model and use proper priming and promoting. You will witness the rest of that miracle.
I am not going to write about AI-powered weapons and AI-supported War Strategies.
So, let’s not ignore the flip side and potential consequences.
AI can also compete with human intelligence. It is doing things humans used to do and very often doing them better – whether it is predicting market trends or optimising supply chains.
This raises ethical questions too. Should we keep pushing the boundaries of AI development if it means replacing human jobs or risking unintended, or even unpredicted consequences?
Some argue that natural selection may start to favour AI capabilities over human ones, as we increasingly depend on them.
To answer this question, try to use a logic combined with predictive and statistical thinking. And stick to the first thought which enters your mind!
Limitations and Boundaries.
Human intelligence has its limits, like cognitive biases, memory lapses, and our relatively slow processing speed. We might rely on intuition a little too much or misjudge things based on emotional responses.
But it is a beauty of humanity & a luxury of being human IMO.
AI, on the other hand, still lacks true emotional understanding or human-like creativity. It can write a good article or generate art based on patterns, but does it truly understand it in as we human do?
But, at the end of the day, who declares that AI understanding and AI inelegance must be an exact copy cut of ours?
I mentioned at one of the local Machine Learning meetings that the form of non-human intelligence may differ from humans, so may differ the metrics defining and evaluating them.
In general, AI is a master of pattern recognition and vector thinking, but it does not “feel” or “understand” the deeper meanings behind its calculations or outcomes. Feel like in human terms, I mean.
But how about a “vector-feeling”, and “emotional logic” would it evolve or already exist?
As I am futuristically orientated type of scientist, I do not have any problem with that. I even ask that questions to a couple of a models and they confirm the relevance of such a thinking.
Anyway, I do not like to either glorify or jinx it. We will witness the further evolution of AI soon.
The Interplay Between NI and AI.
Real wonders happen when NI and AI collaborate. Think of cognitive augmentation like brain-computer interfaces for example, or AI tools that help process massive datasets in ways that would take humans lifetimes to process. Similar with coding.
It is an interplay of human creativity and machine efficiency, pushing boundaries in art, science, medicine, finance, and far beyond.
Future Prospects.
Looking ahead, the future of AI is an open question.
Will we achieve AGI, or even something more??
Could AI surpass human intelligence, and what would that mean for us?
I remember about three years ago during the research conference; I mentioned the singularity and asked a couple of questions to the machine learning panellists. I assume it was a bit too early for an answer, or perhaps I was considered too futuristic for such an event.
Certainly not anymore, as by the time of writing this.
Picture a world where human intelligence and AI converge – our cognitive abilities enhanced by tech, breaking down what we even consider as “natural” or “artificial.”
Also, “no-human-in-the-loop” digital type of interactions. And tools. Just AI to AI. No humans allowed!
Scary, interesting, or both?
Conclusion.
In comparing natural and artificial intelligence, we see two distinct yet increasingly interconnected forces.
Human intelligence, shaped by biology and culture, is adaptive, emotional, and intuitive.
AI, built on algorithms, is logical, efficient, and incredibly quickly evolving.
The interplay between these two might just define the next chapter of human evolution. Singularity? Who knows!
Where does that leave us? We are at a crossroads, and it is up to us to navigate the merging paths of NI and AI.
It is not about choosing one over the other but understanding how both can impact us and modelling the future.
Without constant learning about AI, then actively participating (whatever as a creator, or simply as a user) we are forming a group of unaware opposition – based on ignorance.
From this point, we can only criticise and complain post-factum.
Remember: Those who are absent are not in the right!
Maintain a constant state of digital awareness and help to pave the way for responsible emerging technologies leadership.
Cheers, The Author.
Oryginally published at: