Limits to Human Knowledge and Problem-Solving

6/29/2025

1.     Introduction. Consider the question. Are there limits to human knowledge, and by association the art of problem-solving? Specifically, are there fundamental aspects of the universe that are truly unknowable, as in the impossibility of problems to be solved? Age old problems such as, “What is truth?” and “What is the origin of the universe?” are still mysteries. Will they be solved? Can they be solved? Do humans have what it takes to solve them? That is the situation at hand. As is the problem with these impossible-type problems, we are prone to offer half answers and partially solve perceptually incompletely understood problems. An important take-away is that knowledge and problem-solving are very dynamic in breadth and technique, respectively. Naturally, it is necessary to include some discussion about Artificial Intelligence, and whether it’s ready to take over.

2.     Resistance. We may refer to the fortress of human knowledge. It allows the expansion of what knowledge exists but resists innovation and other novelties. The progression of knowledge is often envisioned as a relentless march forward, perpetually embracing novel ideas that refine or revolutionize our understanding. Yet, the reality is frequently characterized by a palpable resistance to new theories. This phenomenon is not necessarily an indictment of close-mindedness but rather a complex interplay of epistemological rigor, deep-seated psychological tendencies, and the inherent sociological structures of scientific communities. Understanding this resistance is crucial to appreciating the arduous journey from speculative idea to accepted truth[1].

Foremost among the reasons for academic skepticism is the demanding standard of evidence required to dislodge established theories. Existing scientific paradigms are not mere conjectures; they represent the culmination of decades, sometimes centuries, of meticulous observation, rigorous experimentation, and consistent replication across diverse contexts. These theories have withstood countless challenges and have proven remarkably effective at explaining observed phenomena and making accurate predictions. To propose a new theory, therefore, is to challenge a formidable edifice of accumulated knowledge. It necessitates not just offering an alternative explanation, but presenting an extraordinary volume of compelling, independently verified evidence that not only accounts for existing data but also successfully explains anomalies and offers novel, testable predictions that surpass the predictive power of the incumbent theory. Any perceived flaws in methodology, statistical analysis, or interpretation of a new theory’s supporting data will be subjected to intense scrutiny during the peer review process, serving as a critical barrier to immediate acceptance.

3.     Technique. Beyond the stringent evidential demands, human cognitive and psychological factors significantly contribute to resistance. All of us, despite their training in objectivity, are not immune to biases. Confirmation bias, the tendency to seek, interpret, and favor information that confirms one's existing beliefs, is prevalent. When a researcher has spent years, even decades, investing their intellectual capital, reputation, and career progression into a particular theoretical framework, challenging that framework can feel like an assault on their very identity. The sheer cognitive load of unlearning deeply ingrained concepts and integrating a radically different theoretical perspective is also a formidable psychological barrier. As Max Planck famously observed, "A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it." This sobering insight underscores the human element of resistance, where established thinkers may hold onto their views until individuals unburdened by prior commitments emerge. Concomitant with Confirmation bias is Technique bias, tendency to over-rely on familiar methods, tools, or approaches. even when they may not be the most effective for the problem at hand. It’s a type of cognitive bias that limits creativity, flexibility, and innovation. For example, a leader insists on brainstorming sessions, ignoring that root-cause analysis might be more effective. Techniques bias creates several problems including leading to misdiagnosis of the problem, stifling innovation by limiting perspective, wasting time and resources using a method that doesn’t align with the problem’s nature, and  creating blind spots as in alternative methods or creative insights may be ignored. In familiar terms, people become attached or bonded to the tools they know best. Note the familiar, “The hammer sees only nails,”

The significance of resistance factors is that they increase in proportion to the volume of knowledge. It is a certainty that with highly advanced knowledge, it will take longer and longer to become an expert and therefore more and more difficult to adopt new theories or problem-solving techniques. As well, experts become less and less capable with problems even in areas nearby.

4.     Impossibility. The question of whether the limits of human knowledge are defined solely by mental and technological constraints or whether there exist aspects of the universe that are fundamentally unknowable is a profound one. It touches on the nature of human cognition, the universe itself, and our tools for understanding it. Human knowledge is expanding at an unprecedented rate, driven by advances in technology, scientific methodologies, and collective intellectual effort. Yet, this rapid growth prompts us to consider whether there are boundaries to what we can know. These boundaries are imposed not just by the tools we wield but by the inherent nature of the universe or the limitations of the human mind itself.

5.     Perspective. One perspective on this question hinges on the sheer volume of information in the universe. The human brain, for all its complexity, has a finite capacity for processing and retaining knowledge. Similarly, humanity as a collective entity faces practical limits in time, resources, and cognitive bandwidth. Given the vastness of the universe, galaxies, particles, interactions and the lot, it seems plausible that the sheer quantity of information might outstrip our ability to grasp it all. However, this view assumes that knowledge is merely a matter of accumulating facts, rather than understanding underlying principles. Could it be that there are aspects of the universe so alien to our cognitive framework that they will remain beyond our grasp, regardless of technological progress?

6.     A Thought Experiment. To explore this perspective, consider a thought experiment: Can you teach an ant to read? The answer is certainly no. An ant’s brain, wired for an olfactory world of chemical signals, lacks the capacity to conceive of something as abstract as reading. Its cognitive architecture is fundamentally limited, not by a lack of tools but by its intrinsic design. This analogy raises a humbling possibility: just as an ant cannot comprehend reading, there might be concepts or phenomena in the universe that are similarly inaccessible to the human mind? If so, these limits would not stem from technology but from the fundamental structure of human cognition. Companion to the above thought experiment is one about us: Is the mind of humans still evolving? On this there may be some negative news through the agency of cognitive offloading. Precisely, the brain tasks of memory, calculation, and navigation have been outsourced to digital tools, changing how we use our minds. As well, these days literature has gone wild with reports about how Artificial Intelligence (AI) may be dumbing down the brain, at least those of students. One aspect of AI, quite different from libraries, Wiki, and the other online sources, is that AI can give a complete essay on a topic answering precisely your given question. Remember, however, AI only knows what’s known, including unknown knowns, those pesky bits of incorrect information it has learned. If AI was available three centuries ago, for example, it might still be recommending bloodletting as a treatment for many illnesses. Every single revolution in science has contravened the whole of accepted literature.

7.     Modeling. Yet, there is a counterpoint to this notion of inherent unknowability, particularly when it comes to the physical universe. Human ingenuity has consistently overcome apparent cognitive and technological barriers through the development of models and theories. Scientists across disciplines are tirelessly constructing frameworks, including mathematical, computational, and conceptual, that describe the universe’s behavior with increasing precision. From Newton’s laws to quantum mechanics, these models allow us to predict outcomes, even if probabilistically, and to answer questions we once thought unanswerable. Models are the “organizers” of human knowledge.

If humanity can develop models comprehensive enough to address every factual question we can pose about the physical universe, we might claim to “know” it in a functional sense, even if we haven’t cataloged every detail. In this view, technology is not merely a tool but a bridge to overcoming the limitations of our biological minds, enabling us to simulate, predict, and understand the universe’s mechanics. The stark exception to this possibility is that humanity constructs models that answer everything we ask, but are wrong. Perhaps we have answered only the questions we can conceptualize, perhaps missing completely the “real” questions. The notion of model strips bare the human brain, and its depth of thought.

With regard to AI, many think it will replace humans at every level. For example, can generative AI innovate models for physical processes?  Right now, it’s good at medical diagnostics. Additionally, even though AI doesn't "understand" physical laws the way humans do, generative AI can learn patterns, propose new formulations, and even discover approximations or structures that humans haven't noticed. However, while AI doesn’t lie, it requires you to ask the right questions. Thus, technology cannot generate miracles, much less new knowledge, without a human brain in the mix. 

8.     Exceptions. Optimistic views falter when we consider non-physical aspects of existence, such as emotions or abstract concepts like truth, love, or consciousness. These phenomena may resist reduction to empirical models. For instance, while we can study the neurochemical basis of love, capturing its subjective essence may lie beyond the reach of science. Here, the limits of knowledge may not be technological but philosophical or experiential, rooted in human consciousness itself. Unlike physical facts, which can be modeled and tested, these aspects of existence might remain elusive, suggesting that some parts of reality are indeed unknowable in a foundational sense.

9.     A Timely Paradox. We come to an intriguing paradox. If we imagine a future where humanity’s models of the physical universe are so complete that they answer every question we can formulate, we might declare that we “know” everything worth knowing, much like ants in their colony, content with their limited but sufficient understanding of their world. Ants, after all, have no questions left unanswered within the scope of their existence. They eat, live, and die in a universe they fully comprehend for their purposes. Similarly, humans might reach a point where our models satisfy our curiosity, even if they don’t capture every nuance of reality. But what if the human brain evolves, or if we augment our cognition through artificial intelligence or other means? A more advanced mind, or just by a twitch of evolution for us, might ask new questions, revealing gaps in our current understanding and restart the cycle of inquiry. The limits of knowledge, in this sense, are not fixed but dynamic, shifting with our capacity to question, all the while believing we have it all.

10.  Conclusions. The limits of human knowledge are shaped by both technological and fundamental human constraints. Technology expands our reach, enabling us to model and predict the physical universe with ever-greater accuracy, potentially allowing us to answer all factual questions we can conceive. However, aspects of reality tied to subjective experience or abstract concepts may remain unknowable, not for lack of tools but because they transcend the framework of human cognition. Like ants in their mound, we may one day believe we have grasped the universe fully, only for an evolved perspective to reveal new mysteries. The question, then, is not just whether the universe holds unknowable truths but whether we will ever recognize the boundaries of our own curiosity.

In brief, the fact is that even if humanity may be capable of understanding everything in its current evolutionary state, the amount of knowledge required to understand or solve some problems may be too vast for any one person or collective to do so. This is a impenetrable barrier to total knowledge.

My opinion? We have argued that yes, understanding everything is possible, aided by technology perhaps, but it is unlikely that we will do so without further human evolution. Yet, while technology can certainly help, human evolution can possibly be regressive because of it.

                                                                                            

©2025 G Donald Allen

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[1] The notion of accepted truth is as near to what truth may actually be. This implies the candidate for truth is generally accepted by a large majority of the relevant players. This acceptance normally follows its predictability. It works. Its main flaw is that it may be dead wrong, as exemplified by the many theories of disease over many centuries. So yes, truth changes all the time. It is similar to pragmatic truth, originally offered by William James.