Design inference

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William Dembski

Design inference is the logical and/or mathematical result of an assessment of both small probabilities and specification(s) on any phenomenon or event, and the resulting elimination of chance occurrences as a viable explanation for the phenomenon or event.[1]

William Dembski published The Design Inference: Eliminating Chance through Small Probabilities as part of Cambridge Studies in Probability, Induction and Decision Theory in 1998 giving a rigorous mathematical basis for detecting design and eliminating chance as explanations.[2]

Chance occurrences can occur as a side effect of design (e.g. car accidents occur even when cars, controls, and roads are designed). Chance occurrences can also be a an unguided natural phenomenon (e.g. earthquake, landslide, etc).[3] In order to narrow down if something is designed or natural, specifications should be present.

Specifications "are patterns that identify events and that have short or simple descriptions. But descriptions can be represented in bits." Also, "Design inferences engage in a balancing act between the complexity of events and the simplicity of descriptions."[4]

The term "specified complexity" is term used and endorsed by eminent scientists such as Francis Crick, Paul Davies, Leslie Orgel, and even Richard Dawkins, sometimes using the very term and at other times using "complexity" and "specification" in the same breath. The actual term "specified complexity" goes back to biologist Leslie Orgel in 1973 in connection to origin of life research.[5]

Though detecting design is often intuitive, some examples of use of design inferences include archaeology, intellectual property protection, forensic science, identifying fraud, cryptography, SETI (search for extraterrestrial intelligence), directed panspermia.[6]

Many critics of the "design inference" mistakenly assume the mere improbabilities are what design inferences are. However, William Dembski has clarified "no ID researcher has ever suggested that "X is improbable; therefore X is designed" is a valid argument. Instead, since the publication of the first edition of this book in 1998, design researchers have repeatedly emphasized the indispensability of both small probability and specification in eliminating chance and inferring design."[7]

In biology

Example of a Gene Regulatory Network (GRN) in a single cell bacteria called S. cerevisiae where Transcription factors (large blue circles) and other genes (small green circles) have complex chemical interactions in the cell.[8]

Cells display a highly specific and complex set of chemical interactions. For example, gene regulatory networks highlight complex chemical interactions that occur per second in each cell. Resembling chemical manufacturing and synthesis of biological matter. Gene regulatory networks are segments within DNA that govern the rate and products of genes, controlling essential processes such as transcription and translation to prevent the production of harmful or ineffective gene products and also display how segments of cellular activity is automatically controlled by information embedded in DNA.[9]

Gene regulatory networks are visualizations of thousands of genes that are expressed and work in concert to ensure the cell's function, fitness, and survival whereby each gene is expressed at the proper time and in the proper amounts to ensure the appropriate function in each cell.[10]

Life requires multiple chemical processes to exist simultaneously in a microscopic space. According to leading chemist Felix Franks[11]

"To translate the dictionary definition into scientific terms, life processes, as we understand them, must encompass all of the following functions in sequence:

  • To control the synthesis of simple, chiral molecules and their reactions to form complex polymers, based mainly, but not exclusively, on carbon, hydrogen, oxygen, nitrogen, and phosphorus
  • To program and direct the assembly of such molecules into supramolecular structures, organelles, cells, organs, tissues, and organisms, that is, the achievement of differentiation in the right places and at the right time
  • To control cascades of chemical reactions (e.g., metabolism), resulting in growth to maturity, steady-state maintenance, defense against predators and chemical deterioration, energy- conversion processes, reproduction, followed by a more-or-less rapid senescence and expiry"

See also

References

  1. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. Page 70
  2. ↑ William Dembski. 1998. The Design Inference: Eliminating chance through small probabilities. Cambridge University Press. ISBN 0521623871.
  3. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. Page 75-85
  4. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. pages 132-133
  5. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. page 258-266
  6. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. Chapter 2. Sampler of Design Inferences
  7. ↑ William Dembski and Winston Ewert. 2023. The Design Inference: Eliminating Chance through Small Probabilities (2nd edition). Discovery Institute. ISBN 9781637120347. Page 70-80
  8. ↑ Ma S, Kemmeren P, Gresham D, Statnikov A (2014) De-Novo Learning of Genome-Scale Regulatory Networks in S. cerevisiae. PLOS ONE 9(9): e106479. https://doi.org/10.1371/journal.pone.0106479
  9. ↑ Gene Regulatory Networks Science Direct Journals "Gene regulatory networks are segments within DNA that govern the rate and products of genes, controlling essential processes such as transcription and translation to prevent the production of harmful or ineffective gene products."
  10. ↑ Macneil LT, Walhout AJ. Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression. Genome Res. 2011 May;21(5):645-57. doi: 10.1101/gr.097378.109."In any given cell, thousands of genes are expressed and work in concert to ensure the cell's function, fitness, and survival. Each gene, in turn, must be expressed at the proper time and in the proper amounts to ensure the appropriate functional outcome. The regulation and expression of some genes are highly robust; their expression is controlled by invariable expression programs. For instance, developmental gene expression is extremely similar in a given cell type from one individual to another. The expression of other genes is more variable: Their levels are noisy and are different from cell to cell and from individual to individual. This can be highly beneficial in physiological responses to outside cues and stresses. Recent advances have enabled the analysis of differential gene expression at a systems level. Gene regulatory networks (GRNs) involving interactions between large numbers of genes and their regulators have been mapped onto graphic diagrams that are used to visualize the regulatory relationships."
  11. ↑ Felix Franks. 2010. "2. Water and Life Friend or Foe?". In Harper, Charles (ed.). Water and Life: The Unique Properties of H2O. CRC Press. ISBN 9781439803561 page 13
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