The Mystery of Life's Creation: A Generational Question

The Mystery of Life's Creation: A Generational Question *Note: This article is from the book Smart Design: Philosophy and History of Theory. After seven years of research, chemist Charles Thaxton and Nobel laureate Walter Bradley, who specializes in the mechanical properties of polymeric compounds, and geochemist Roger Oslin introduced the concept of "intelligent causation" as an explanation of the origin of biological information in their book The Mystery of Life's Origin, published in 1984 by The Philosophical Library, and reprinted by another prestigious publication. These scientists defied the mainstream interpretation of evolutionary chemistry, in addition to the old scientific paradigm, and Thaxton traveled to California to meet with one of the world’s best evolutionary chemists, Dean Kenyon, a professor of biophysics who knew how serious the opposition would be to the publication of their book, and who co-authored the groundbreaking study on the topic of biochemical determinism. Thaxton wanted Kenyon to discuss the fairness and accuracy of the critique of his book The Mystery of Life's Origin, but Thaxton had another motivator: his desire to write Kenyon an introduction to his book, even though his book contains criticism of Kenyon's life-creation thesis, which made him famous in the field. One can imagine how this meeting might be due to the disagreement between the two men over their theses; but none of this happened, the meeting went well, and before Thaxton offered Kenyon his wish, Kenyon volunteered to write the introduction; he told him that he had been reviewing his ideas for some time, and that he was beginning to tend to see Thaxton. Kenyon's book Biochemical Imperative made the best sales on the subject, illustrating what at the time could be considered the best possible evolutionary model of how the first living cell formed in primordial soup, and Kenyon had begun revising his hypotheses in the 1970s. Some experiments, some conducted by Kenyon himself, have consistently shown that simple chemicals – amino acids and nitrogenous bases – cannot organize themselves into molecules capable of storing information, such as our father’s proteins, without prior guidance from human observers. Thaxton, Bradley, and Olsen took this fact into account when they worked on their argument, and Kenyon found their argument strong and well-researched, noting in his preface that "The Mystery of Life's Origin: A New Extraordinary Analysis of an Old Question." It has become a bestseller among books with advanced university scientific content, specializing in the subject of evolutionary chemistry, and has been praised by leading and brilliant scientists such as: "Kinyon", "Robert Shapiro", and "Robert Jastro", in addition to good reviews in prestigious scientific journals[1] such as "Yale University Journal of Biology and Medicine", and some have rejected the book as a claim. What sparked interest in the scientific community in the book "The Mystery of the Origin of Life" is his critique of all explanations based on the purely materialistic view of the origin of life, noting that the Yuri-Miller experiment did not realistically simulate the primitive conditions that preceded the formation of any kind of life on Earth. The existence of "prebiotic" soup is a myth; the chemical shifts that are crucial to the evolutionary story of life on Earth have been subject to destructive interference called destructive overlapping interactions,[2] and neither chance nor the amount of energy flowing can explain the information stored in biological polymers, such as our father's protein. The three scientists presented a new hypothesis that looks at this issue in a radically different way; they proposed that the properties that allow the storage of information in DNA may indicate an intelligent reason, and they based their argument on the theories of "Paulani" and others, arguing that the scientists of physics and chemistry alone can not produce or generate information, and they compared this to the inability of ink and paper to produce or explain the information contained in a book, and put forward their argument that our experience is steady. The book succeeded in sparking interest in intelligent design theory, and inspired a new generation of young scientists (such as Denton, Kenyon, Behe, Mills, Dembski, Morris, Lunich, Schedler, Nelson, Morris, Meyer, and Bradley), to continue to investigate the issue of whether the manifestation of living creatures is a function of design, or whether it is as the neo-Darwinian forms of design and theorists claim. By the time the book appeared, I was working in the field of earth physics at the Atlantic Richfield Company in Dallas, where Charles Thaxton lived, and I later met him and became fascinated by the radically different idea he had developed of DNA. I started going to his office after the work was done to discuss his arguments in his book. I was not entirely convinced by his idea. Then, a year later, I left my work in geophysics and began my PhD at Cambridge University in the field of the history and philosophy of science. During my research, I investigated several issues that arose from my discussions with Thaxton. After I completed my PhD, I began to try to answer the question: Can DNA’s signification of a designer be formulated rigorously and accurately? Between contemporary evidence and etiology In my doctoral research at the University of Cambridge, I have found that sciences that rely on historical evidence, such as earth science, paleontology, and archaeology, use distinctive methodologies to investigate their problems, while all fields of science involve the attempt to uncover universal laws. Steven Gould says historical science tries to “interpret the past through its findings and effects,” visiting for example the Royal Tyrell Museum in Alberta, Canada, where scientists have imagined the ocean floor of the Cambrian and the animal groups that lived there, and then spectacularly represent, reconstruct and synthesize it. You can also read the fourth chapter of Simon Conway Morris's book on the Burgess Shell fossils[4] and you will see a vivid tour of this ancient place, but what Morris and the scientists working at the museum have done is to reconstruct the ancient sites of these Cambrian creatures based on their fossils of the present day, in other words, the paleontologists have deduced or painted a picture of the situation that existed in the past from what they have in the present. To understand this particular method of reasoning, we should refer to one of Darwin’s contemporary scholars, William Whewel, who is known to have authored two books on the nature of science: The History of Inductive Science in 1837, and The Philosophy of Inductive Science in 1840. Hill's distinction between two types of inductive science, such as mechanics or physics, and what he called palaetology, a branch of science concerned with the study of past events through present scientific causes, is characterized by three characteristics: 1) It has a particular purpose, which is to determine or examine the conditions under which the old things were applied – or the causes that caused the facts in question in the past. 2) Explaining and interpreting current events or facts through causes that have occurred in the past, rather than explaining and interpreting them through general laws, (although these laws sometimes play auxiliary roles). 3) It has a special pattern of reasoning based on interpreting the terms of the past through its "clear effects" using generalizations that link the evidence between our hands to its past causes. Inference with the best possible explanation This type of inference is based on the use of deductive and logical methods of inferring certain inferring current arguments, facts or facts to explain invisible events that occurred in the past, and can be called "probability inference", and the first to describe this pattern of inference is the American philosopher and logician "Charles Pierce C. S. Peirce"; he observed the difference that follows this pattern of inference from the application of the same type of inference is repeated; The problem of probabilistic inference can be understood from what Pearce presented, represented by the following measurement: If it rains, the streets will get wet. The streets are wet. This means that it has rained. The above analogy shows us the conclusion of a situation that has existed in the past – the streets are wet – through data in the present, but this conclusion falls into a logical fallacy, which is known as recourse to results; the fact that the streets are wet without taking into account other evidence that helps in the decision on this issue, one can only conclude that it is raining is only a possible conclusion; it says: it is possible that it may be raining. It can be caused by rain, but it can also cause the washing machine to get wet, or the opening of the fire hydrant, for example, so the possibility of inferring the facts of the present and its data on the past is characterized by some difficulty because of the many possibilities that may cause the situation to get the same. Pierce's main question was about our repeated use of this type of inference, though fraught with the fallacy of invoking the results; he cited the fact that Napoleon was incontestable, yet we use probabilistic inference to infer his existence, and thus we must infer the fact of his existence in the past through his present effects. Although we use probabilistic reasoning and its lack of reliability, there is no sane person who doubts its existence, and Pierce explained this by saying: "Although we cannot see Napoleon, we cannot explain what we have seen without assuming its existence." Pierce's argument explains that a given probability hypothesis is stronger if it can explain the result in a way that no other historical hypothesis has. In practice, this is reasoned and believable if the hypothesis is interpreted as something else. In other words, its "increase in logical acceptability" of the probability hypothesis can be improved if it can be presented in a way that makes it the best and most appropriate explanation of the effects present. What scientists are doing here is putting the evidence in the balance and comparing it carefully to determine the best explanation, and contemporary philosophers of science call this method "finding the best possible explanation," so when trying to explain the origin of an incident or system that existed in the past, historical scientists compare different hypotheses to look for the best possible explanation if this hypothesis is true. They therefore tentatively assert that this hypothesis is the best possible explanation of the available and most likely data. Current operating causes But what constitutes the best possible explanation for historical science? My research has shown that the prevailing view among historical scientists is that “the best” does not mean “ideologically satisfactory explanation” that is, one that agrees with the researcher’s ideology or “common explanation”; it is, first and foremost, “reasonable explanation,” so historical scientists try to identify the causes that produce the desired effect they are researching. Accordingly, scientists here assess hypotheses by their prior knowledge of the effect and its cause; the triggers that produce the desired effect are better explanatory than others; for example, a volcanic eruption can be considered a better explanation for the volcanic ash layers in the Earth's layers of earthquakes, because we already know that a volcanic eruption produces gray layers, while earthquakes do not. Charles Lyell, a geologist who had a major impact on 19th-century historical science and Darwin in particular, read Charles's greatest book, Principles of Earth Sciences, on his famous Beagle voyage, and then adopted the principle of regularity,[5] arguing that the processes of change we observe, which occur through small evolution, can explain new forms of life. The “principles” in the title of Charles sums up this geologist’s main methodological idea: “try to explain past changes in the Earth’s surface, by reference to the reasons or causes for which he is now working,” and Lyell argues that in seeking to explain past events, historical scientists should not follow strange and anomalous reasons, and the implications of what we do not know, but instead should cite the known and learned reasons for them. The term he used to express the "current effectual cause" was vera causa, which means real and actual cause, and accordingly, Darwin tried to prove that the process of inheritance with the presence of genetic modifications in subsequent generations was the real cause of many different patterns, and was definitely observed among living creatures. Darwin noted that there are traits common to different organisms. He called this “symmetries,”[6] and noted that we know from our experience that, although descendants differ from their ancestors, they are similar in many respects, and usually this similarity is most evident in the descendants closest in time to their ancestors. Accordingly, Darwin argued that our steady experience proves that the process of inheriting characteristics acquired from a common ancestor is characterized by "explanatory efficiency" and has the ability to generate these identical and similar traits among living creatures. Then there was one thing. Contemporary philosophers of science agree that interpretative efficiency is the best way to separate competing hypotheses, but note that this methodology leads to a reliable and valid conclusion in only one case, namely, if the conclusion can be presented as the only known reasoning for the reasoning. This leads to the fact that the process of determining the best explanation involves the generation of a set of hypotheses and then comparing them, so that when historical scientists deduce the most unique and reasonable reasons among their hypotheses, they avoid the fallacy of invoking the results, and the error of ignoring other possible causes, which may lead to the same effect. This means that the process of determining the best explanation involves making a list of possible hypotheses, and then comparing the strength of their known or theoretically proposed causes based on data relevant to the subject of research and evaluation, and this follows a gradual deletion of possible and probable hypotheses, but less efficient until we reach the most reliable reason which is considered to be the best explanation. Scriven adds that probabilistic inference, or as he calls it, "the process of analysis and re-selection of the most probable causes," if done in this way will avoid the limitations or logical limits of probabilistic reasoning. As Peres has observed, the fallacy of recourse to results can be formulated in the manner of formal logic in the form of two introductions and a result: * If "x", lead to "y". "Y" is signed. * Therefore, "x" is true. Michael Scriven, Eliot Super, William W. P. Alston, and Walter Price W. B. Gallie have observed that this type of inference can be recast in such a way as to make it more logically acceptable, making "y" the only known cause of "x", or making "x" a necessary condition for "y" to occur, as follows: "X" is a prerequisite for the existence of "Y". "R" is found. “C” must also exist. The above formulation of this type of inference - probabilistic inference - has logical validity in philosophers, and acceptability in historians and forensic scientists. Scriven particularly emphasized this point: if scientists can discover a trace that has only a possible single cause, they can confidently infer the inevitability or efficacy of its existence in the past; for example, archaeologists know that the human ability to write is the only known cause of linguistic inscriptions, and must therefore infer the existence of writing activity when they discover plates containing ancient writings. There is no doubt that many cases require the researcher to strive very carefully to find the cause or the only possible reason, for example: The refraction of the wind or the so-called wind shear or the damage of the codes of the aircraft may explain the crash, but investigators will search for whichever is the actual reason, or the real reason is hidden elsewhere. In the ideal situation, the investigator will discover one detailed evidence or a set of appropriate evidence that allows him to distinguish between them. In my study of historical scientists I found that they are similar to investigators and forensic scientists, they follow to arrive at the best explanation.[7] In fact, Darwin himself employed this methodology in his book The Origin of Species, arguing for his theory of a common ancestor not because it can predict outcomes. In my study of methods in historical science, I found that historians are like investigators and criminals, using the same methodology of reasoning for probability and exclusion in their attempts to solve the case and arrive at a better explanation. Darwin employed this method in his well-known work On the Origin of Species, and he used it to defend his well-known theory of the common ancestor; not for its ability to predict future events or outcomes tested under exact conditions, but for its ability to explain known facts better than other competing hypotheses; Darwin writes in his letter to Asa Gray: "We have tested my hypothesis of the common ancestor of biology against the best of what I have found." DNA Design: Developing the Argument Through Information What does this historical research have to do with methods of scientific reasoning, intelligent design, biological information, and the mystery of the origin of life? For me, it is very important to determine whether the design hypothesis can be formulated in a precise scientific manner rather than just as an interesting hunch, as I know from my study of life genesis research that the first central question scientists try to explain the first form of life is a central question scientists face in explaining the first life genesis: how was the specific sequence or sequence of digital information stored in both DNA and RNA necessary to build the first cell? My studies of the curricula of historical scientists have led me to the question: What is the real and actual cause of the origin of digital information in DNA and RNA? Or what is the "current effective cause" that can have such an impact? Based on my steady experience and knowledge of different attempts to solve this problem by conducting unguided biosimulation experiments or using computer simulations, I have concluded that there is only one sufficient and effective reason at present for such specialized intelligence. In other words, through our empirical understanding of the structure of cause and effect – or cause and effect – in this world, I have come to the conclusion that intelligent design is the best explanation for the information necessary to build the first cell. Ironically, my discovery is that applying Lyell’s principle of modularity – which is flawed and refuted by creationists who argue that the Earth is short-lived – to the question of the origin of biological information, the evidence from molecular biology supports and sustains the theory of the new scientific argument. [1] In addition to receiving an award from the Journal of College Science Teaching, Klaus Dose wrote a major review in the journal Interdisciplinary Science Reviews titled, "The Origin of Life: More Questions than Answers." They prevent the completeness of the chain of organic reactions necessary for the formation of life's basic biomolecules, i.e., the process of polymerization and molecular chain lengthening. [3] The term “historical sciences” can be used in this paper. [4] Fossils bearing deposits and traces of decaying Cambrian creatures found in Canada and Britain. [5] It is a principle that aims to perpetuate the causal system and the natural laws of the universe. [6] Meaning is the apparent similarity and congruence between living creatures. [7] Gian Capretti developed Persen’s probabilistic inference, and Gian et al. offered this type of reasoning through Sir Arthur Conan Doyle’s series of stories about Detective Sherlock Holmes. Capretti attributed the success of Holmes’ probabilistic inference to the mastery of the method of phasing out possible hypotheses that are less capable and more explanatory than others. - Dr. Steven Meyer. — Source: Brahin Center website - Published on 2018-05-20 (archived at the Internet Archive) https://braheen.com/articles/evolution-design/لغز-نشأة-الحياة-سؤال-عابر-للأجيال