To prove his point, Nursi states three possibilities to explain the existence of things in the universe:

1. Everything is created by causes

2. Everything is created on its own

3. Everything is an outcome of natural laws.

The common theme of these three possibilities is that creation is dependent on some natural rules and causes. Bediuzzaman refutes these possibilities by arguing that these rules and causes are not conscious; thus, they are not aware of other causes or the ultimate purpose. From this, Nursi concludes that natural causes are not true creators but veils—screens behind which the act of creation takes place, while we perceive only laws and outcomes on the surface. This article explores this argument by relating it to contemporary scientific and technological examples.

Mechanisms do not explain agency

One point of discussion in this debate is whether elements in nature operate randomly or follow a certain manual, so to speak. Modern molecular biology give us numerous examples to ponder over this point. For instance, T-cells, a type of immune cells, are able to distinguish whether a cell belongs to the host or not via their highly precise receptors [2]. Such a precise receptor cannot be adequately explained by randomness alone, without a system of built-in rules that guide and stabilize its formation. Similarly, B-cells, which are another type of immune cells, can produce highly accurate antibodies against pathogens in the body. To be able to produce these antibodies, they have gone through a process called hypermutation and selection in which many versions of antibodies with small changes are made and only the most effective ones are retained [3]. Such a process is not random; on the contrary it follows specific selection criteria. Neither B-cells, nor other components involved in B-cell mutation have intelligence or training to conduct these processes on their own. They appear to be following an instruction manual, which has been provided by an authority who knows every detail of these processes.

Some people have the tendency to underestimate such complexity as soon as the mechanism of these systems are demystified through scientific discoveries. Discovering the underlying mechanism of a complex biological process helps us understand the system but does not indicate that the mechanism has the power to conduct the action. In this article, I further discuss this perspective by leveraging the recent advances in Artificial Intelligence (AI) as analogies to clarify the distinction between mechanism and agency.

Why technology makes this easier to see

I use examples from AI and modern computing because they can turn abstract ideas into concrete pictures, even for children, who often find abstraction difficult. For instance, the idea of recording all of our deeds by a Creator is easier to grasp in a world where phones, sensors, and street cameras quietly record what happens around us. Being in multiple places at the same time is also easier to understand via technologies such as virtual reality.

Several examples from computer science and modern technology help us better understand the relationship between mechanisms, rules, and agency in creation—the difference between what executes and what intends. To develop software, we need a programmer—someone with intelligence, power, and intention to write and direct the code. A book cannot exist without a writer, and software cannot exist without a programmer. Similarly, in biology we observe many “books” of information, and information, by its very nature, points beyond itself to an author.

Generative AI makes this contrast especially vivid. With generative AI technologies and methods such as vibe coding, one can now produce working software code using a simple prompt. This shows that parts of writing code can be automated once the underlying structure and rules are already in place. In other words, machines can learn the mechanism of coding, which implies that producing complex software happens automatically. Yet the “autonomy” is borrowed: the AI system is executing mechanisms that someone else designed, trained, and powered. It depends entirely on human-designed architectures, pre-existing data, external energy, and meaningful prompts to function. AI can generate text or code, but it cannot decide why it should do so, nor can it sustain or direct its own existence. We can therefore compare generative AI to a keyboard or a pen—a powerful tool, but still a tool—which requires a “writer” to operate it. Today, the writer (i.e., the user) no longer needs to specify every detail; a short prompt can be sufficient.

Likewise, biological processes—despite their sophistication and apparent autonomy—do not possess agency. They operate according to rules but rules themselves do not create; they are enacted. Therefore, just as intelligent machines require a human creator, life itself points to a Creator beyond the mechanisms that sustain it. As the Qur’an states: “His command is only when He intends a thing that He says to it, ‘Be,’ and it is” (Surah Ya-Sin 36:82).

Randomness, direction, and purpose

Another common argument suggests that random changes, given enough time, can account for the complexity we observe in life. Time certainly amplifies processes—but time alone does not define direction or meaning. Random variation can generate differences, but without a standard for evaluation, there is no sense of progress.

An everyday analogy makes this clear: Randomly rearranging letters indefinitely will not produce a meaningful book unless there is already an understanding of language and meaning. In the same way, biological changes require more than chance—it requires a framework that distinguishes what works from what does not.

This can be illustrated through computer algorithms, too. An algorithm that undergoes random modifications cannot “improve” unless improvement is defined. In AI, this role is played by an optimization or reward function, which could be described as a built-in goal. Even self-learning systems such as AlphaGo require pre-defined goals and evaluation rules. Without knowing what to optimize for, learning would be impossible.

Likewise, natural processes that seem to develop or improve over time presuppose a standard by which “improvement” is measured. Yet these processes do not define their own goals or evaluation criteria. Order, harmony, beauty, and directed complexity therefore point not merely to rules, but to a conscious source that established those rules with intention.

Autonomy still requires sustenance

A further question naturally follows: even if creation has an origin, does it then run on its own? This is the classical debate between a continuously active Creator and a non-intervening God.

The clock analogy is often used to argue for non-intervention: once a clock is wound, it runs independently. Yet this analogy fails upon closer inspection. Even a clock requires continuous energy; without it, the system stops. The universe likewise depends on energy at every moment. Moreover, unlike a clock, natural systems are not fully deterministic. Flexibility, contingency, and openness to change are intrinsic features of reality.

From a technological perspective, even the most autonomous AI systems remain continuously dependent on external inputs. Agentic AI requires power to operate, retraining when conditions change, and intervention when goals or constraints are altered. Apparent autonomy does not remove dependence—it conceals it.

Similarly, natural laws are not independent actors but frameworks through which ongoing sustenance is expressed. Knowing how a system operates does not eliminate the need for the One who sustains its operation. Rather, the consistency of rules can be understood as a veil through which continuous divine power and will are manifested.

Rules as a veil, not a replacement

Seen in this light, natural laws can be understood not as rivals to divine action, but as expressions of consistency in how that action unfolds. Nature, then, is not the author of existence but the script through which existence is written. Rules describe patterns; they do not generate meaning. Mechanisms enable processes; they do not explain purpose.

By reflecting on both nature and technology, we are reminded of a simple but profound insight: understanding the workings of the universe does not diminish the question of its Creator. It deepens it.

References

1. Nursi, Said. Nature: Cause or Effect. NJ: Tughra Books. 2012.

2. Johannes Pettmann, Anna Huhn, Enas Abu Shah, Mikhail A Kutuzov, Daniel B Wilson, Michael L Dustin, Simon J Davis, P Anton van der Merwe, Omer Dushek (2021) The discriminatory power of the T cell receptor eLife 10:e67092.

3. Syeda, M.Z., Hong, T., Huang, C. et al. B cell memory: from generation to reactivation: a multipronged defense wall against pathogens. Cell Death Discov. 10, 117 (2024).

Books, bodies, and beautiful paintings – these are all emergent systems. As our understanding of these systems grows, so, too, do the questions about how we study them.

Scientific revolutions require the shift of paradigms [1]. According to Thomas Kuhn, a paradigm is more than a current theory and its implications. It’s also combined with a worldview where the theory exists. As an example, classical mechanics does not only consist of Newtonian laws, but also has a deterministic worldview. Kuhn states that when the anomalies and limitations of the current paradigm are encountered in the scientific community, new ideas pour in and thereby a new paradigm is formed. The development of quantum mechanics against classical mechanics is an example of such a paradigm shift. Along with this shift, not only new formulas and theories were developed, but a new worldview – one that was not deterministic – emerged.

In the last century, we witnessed many scientific breakthroughs in the areas of chemistry, computer science, medicine, molecular biology, and physics. Along with the experience and knowledge we gained from them, we still try to understand the secrets of the universe we live in from “very small” to “very big.” However, certain systems, so-called complex systems, push the limits of our scientific theories and the tools used to analyze them. In this article, we will describe such systems, viewing them as candidates for a new paradigm, with their characteristics and their implications to our worldview and science.  

In the existing literature, complex systems are defined as those formed by many elements that correlate and interact with each other somehow. As a result of these correlations and interactions, these systems reveal behaviors and properties that are not obvious in their individual parts. There are numerous examples of complex systems, including biological systems, climate systems, and economic systems.  

The most important feature of complex systems is emergence, which can be deciphered from the below example. When someone moves into a new apartment, the first issue they face is how to decorate their place. Depending on what they have, they put pieces of furniture in certain places within the room and organize them according to their taste. For example, if they decorate a living room, they might put two couches against the walls in such a way that they sit perpendicular to each other. A rug might be laid out before them and a coffee table might be placed on it. Moreover, another table with a lampshade on it might be put in an empty place where the two couches connect. They might put a television stand so that it faces the couches and the café table. In addition, a dining table with a nice tablecloth on its top and six chairs around it might stay in the far corner. A vase with flowers might be put on the middle of the table. In this example, they picture a pattern that emerges in decorating the living room according to one person’s taste. Clearly, someone else could have organized the room differently with the same furniture and thereby another pattern might have emerged.

Let us consider a bit what the aforementioned example tells us. First, the character and the impression we get from the room depends intimately on how it is decorated. Changing the arrangement of furniture leads to the emergence of new patterns which might seem lovely to some people, boring to others. Although the impression might vary from person to person, everybody might agree on a professional’s take of the decoration. Second, the emergence of patterns in the organization of parts is not limited only to the decoration of rooms. It is obvious in many, many systems. For instance, Monet, Picasso, and Renoir made their masterpieces using different colors of oil paint and a canvas. With the same pieces, one can however paint figures with no clear meaning. By the same token, using letters in one language, Shakespeare, Goethe, and Dostoyevsky wrote their masterpieces. However, with the same letters, it is possible to write essays that do not say anything at all. In these examples, we see different patterns emerge by arranging the pieces in different plans.

Now let us ponder on the following question: What is the relationship among individual parts and the pattern that emerges when we arrange these parts in specific ways? In all the examples mentioned above, none of them seem to have a direct relationship with the emergent pattern. In the case of room decoration, just a couch or just a café table does not tell us what kind of living room there will be. In other cases, the lack of relationship is even more obvious. Twenty something letters do not possess any insight into Shakespeare’s Hamlet or Goethe’s Faust. Nor do oil paints have any hidden picture in them related to Monet’s Argeteuil or Renoir’s La Grenouillere. Then, it is clear that patterns emerge according to the knowledge, talent, vision, and plan of whomever is organizing them.

The above examples were chosen from daily life for the sake of simplicity. At this point, let us turn our focus to the scientific aspects of pattern emergent systems due to the interaction of parts. This emergence phenomenon is universal and one of the characteristics of the complex systems that are formed by many parts with different features and characters. Therein, new features that are not obvious in individual parts arise as a result of their interaction. There are numerous examples of such systems such as the internet, stock market, economic systems, and biological systems [2]. As you might see, they interact extensively with our daily lives; therefore, understanding them offers unlimited benefits to us. Furthermore, they challenge us in both scientific and philosophical manners. Let us see how so in the below paragraphs.

The first way we’re challenged are the scientific aspects. Let us see emergence in the following example. Quarks are the most fundamental particles that are experimentally verified in the universe. That is, they cannot break into parts. Their typical features are mass and electric charge. When they come together in certain combinations, they form protons and neutrons that form the nucleus of an atom. Atoms also have electrons around the nucleus; these electrons have different energy levels.

Up to this level, we do not see much difference in behavior emerging from the arrangements of parts aside from some physical details. When atoms come together, they connect by chemical bonds and thereby form molecules and matter. At this level, the chemical bond is a new feature. If we had a single atom, we would not know chemical bonds were possible. Then, a single atom does not have this feature: a chemical bond.

As an example, two hydrogen atoms and one-oxygen atom bonded together form the water molecule. By itself, this molecule does not display very peculiar phenomena. However, when many of them come together, they can be ice, liquid, or vapor depending on the environment’s conditions, e.g. temperature and pressure. Again, these behaviors are completely new and do not appear in a single water molecule.

Another aspect is this. Up to a few molecule levels, quantum mechanics describes what’s going on. However, when the system size reaches a certain level, usually a few centimeters to meters, we use Newton’s laws to describe the system. According to a Noble laureate in Physics, Robert L. Laughlin [3], Newton’s Laws are emergent properties that arise in a sufficiently large scale as a result of the interaction of smaller entities described in the Quantum regime. This point of view differs from the classical reductionist approach in which a complex system might be understood by studying the simpler parts that constitute the system. This is quite opposite to what is described above. Laughlin, as many others, sees the reductionist approach limiting our understanding of complex systems [3].

We would also like to look at examples from biological systems. In contrast to the above example, in this case, there are numerous types of molecules. Additionally, most of them function in the water; thus water is part of the system. Biological molecules are organic and made of a few types of atoms – nitrogen, oxygen, hydrogen, and carbon. In addition, a few ions, such as zinc, sodium, and so on, play crucial roles.

Simple biological molecules are DNA, RNA, and proteins. Even they are made of thousands of atoms. At this point, it is clear that a special arrangement of this many atoms yield very complex molecules. If we go one level up and investigate a system of DNAs, RNAs, and proteins, we will reach the basic unit of living organisms: cells. In a simple bacterial cell, there exist a few million proteins that float in the water. In more complex organisms, this number significantly increases and the cell becomes more complex. However, what emerges keeps us in awe: life. A single DNA or single protein does not have this feature. However, when they are together, they act in harmony, produce, grow, exhume energy, and die. These are very distinct features that do not exist at the level of a single molecule. Biology does not have quantitative theories, such as physics or chemistry. The approach to study such systems is usually to modify a certain gene and to check its effect on the phenotype. Then, this approach can be considered reductionist.

In the above examples, we saw how emergence occurred. Now, let us see how science studies complex systems. There are two approaches to study such systems. One is top-down, or the reductionist approach; the other is a bottom-up, or holistic approach. So far, the former has reigned over science. This is due to various reasons. The most important is that breaking the system into subsystems reduces the complexity. However, this approach is valid only if the system is the sum of its parts. In contrast, in emergent systems, as Aristotle said, “the whole is more than the sum of its parts” [4]. Then, you might expect that the holistic approach might be more useful than reductionism.

However, there are other factors challenging this approach. One is the lack of tools or insufficient availability to study the systems. For example, with the advances in today’s technology, we can simulate and do the necessary calculations to dock a small molecule to a protein structure in a few days using the methods of Molecular Dynamics. In this simulation, there are a few thousand atoms. However, in a cell, there are roughly 10¹⁴ atoms and the simulation of such an environment would take forever.

The philosophical aspects of complex systems are not limited to how we study such systems or the emergence of physical laws. One important question is this: how do parts with no relationship to the emergent pattern know which pattern they will give rise to? In the science community, this question causes a big debate due to its outcomes. As we see in the decoration example, or the painting and literature examples, emergent patterns do depend on how they are arranged and thereby who arranges them. Can we say that many letters come together randomly to form words and later sentences? Are those sentences arranged randomly to give birth to Hamlet? If you adopt these questions to the cellular, then you must ask how life emerges by the arrangement of zillions of atoms. At this point, we are forced to agree with both Aristotle that, “the whole is more than the sum of its parts” [4] and Paul W. Anderson, Noble Laureate in physics: “More is different” [5].

Murat Erdin is a freelance writer living in Massachusetts.

References

1. Kuhn, Thomas. 1962. The Structure of Scientific Revolutions, The University of Chicago Press.
2. Waldrop, M. Mitchell. 1992. Complexity: The Emerging Science at the Edge of Order and Chaos, Simon & Schuster.
3. Laughlin, Robert. 2006. A Different Universe: Reinventing Physics from the Bottom Down, Basic Books.
4. Metaphysics, Aristotle.
5. Anderson, P.W. 1972. “More is different,” Science Vol. 177, No. 4047, 393-96.