Engineering perspectives on intelligence
From ResearchID.org
The Principle of Methodological Engineering
"The reason evolutionary biology has lost all sense of proportion about how much evolution is possible as a result of blind material mechanisms (like random variation and natural selection) is because it floats free of the science of engineering. At every crucial juncture where some major evolutionary transition needs to be accounted for, evolutionary biology invokes a designer-substitute (like natural selection, lateral gene transfer, or symbiogenesis) to do the necessary design work. Yet unlike the science of engineering, evolutionary biology does not actually perform the necessary design work or specify a detailed procedure by which it might be accomplished. Intelligent design, by contrast, takes what I call "methodological engineering" as a fundamental regulative principle for understanding biological systems. According to this principle, biological systems are to be understood as engineering systems. In consequence, their origin, construction, operation, break down, wearing out, repair, and above all history of modifications (both designed and accidental) are all to be understood in engineering terms.", by William Dembski
(From: Becoming a Disciplined Science: Prospects, Pitfalls, and a Reality Check for ID http://www.theapologiaproject.org/Reality%20Check%20for%20ID.pdf)
The Structure of a Scientific Concept
"The goal of science is to generate predictions about what the universe around us - what might be called "consensual reality" - will confront us with next. At some level, it is something we all do from an early age - that is how we build up our understanding of the universe. However, in recent years, the philosophy behind this process has become increasingly rigorous.
An unconfirmed statement about the objective universe that matches existing data is usually referred to as a conjecture."
From: FreeStyle:The_Structure_of_a_Scientific_Concept
What is Engineering?
"Engineers do much more than build things. They perceive a need. Then, they develop something that will fit that need. The answer must be aesthetic, practical, economical, and safe. That’s where design comes in.
How does one design something? How does one create the ideas to produce an effective result? From mousetraps to bridges and space stations to medical instruments, the way something is designed determines how useful it will be to the world."
From: http://www.jhu.edu/virtlab/finals/FINALS/2/2design.pdf
Are Intelligent Design formulations scientific?
FreeStyle:Are_Intelligent_Design_formulations_scientific?
Molecular Systems Biology and Control
From: http://www.math.rutgers.edu/~sontag/FTP_DIR/05cdc_ejc_oct05.pdf
Introduction
"Within the last few years, the field of “molecular systems biology” has taken shape, having as its goal the unraveling of the basic dynamic processes, feedback control loops, and signal processing mechanisms underlying life. Leading biologists have recognized that new systems-level knowledge is urgently required in order to conceptualize and organize the revolutionary developments taking place in the biological sciences, and new academic departments and educational programmes are being established at major universities, particularly in Europe and in the United States.
The studies of dynamics, feedback, and signal processing in engineering and in biology have long been intertwined, for example in the fields of biological and biomedical engineering. But our community has also actively participated in the study of biological control systems in their own right, independent of such application areas. Indeed, one of the founders of our field, Norbert Wiener, developed many of the ideas of feedback and filtering in the early 1940s in collaboration with the Harvard physiologist Arturo Rosenblueth, who was, in turn, heavily influenced by the work of his colleague Walter Cannon, who coined the term homeostasis in 1932 to refer to feedback mechanisms for set-point regulation in living organisms. Wiener viewed his study of cybernetics as a unifying theme in engineering and biology. Rudolf Kalman often used biological analogies in his discussion of control systems theory, and so did many other early researchers. Balthazar van der Pol, the Dutch electrical engineer whose oscillator models of vacuum tubes are a routine example in the theory of limit cycles, was motivated by models of the human heart and an interest in arrhythmias. In parallel, and for at least as long, mathematical biologists have been developing quantitative theories of physiological regulation, metabolic pathways, insulin control, heart electrical patterns, neural and circadian oscillations, and so forth.
So, one may ask, why the sudden resurgence of interest? The answer surely involves a combination of many factors. Bioinformatics has been tremendously successful in facilitating the sequencing of human, animal, plant, bacterial, and other genomes, as well as in protein structure prediction. Nontrivial ideas and algorithms from discrete mathematics, probability and statistics, theoretical computer science, and even partially observed stochastic systems (Hidden Markov Models), embedded in user-friendly software, are now indispensable tools of the working biologist and pharmaceutical researcher. Thus, many biologists have come to accept and value the use of mathematical tools. On the other hand, new data collection and measurement approaches, themselves based upon sophisticated engineering, make possible the simultaneous monitoring of the activity of thousands of genes and the concentrations of proteins and metabolites, thus allowing for the study of microscopic dynamic interactions among cellular components, and making a systems-level view of cells particularly natural. The huge amounts of data being generated by genomics and proteomics require new theoretical approaches to interpretation and organization. Medical advances also drive this new emphasis. Many in the pharmaceutical industry have come to the realization that only by understanding cells as a whole can one identify novel targets for new drugs, and understand their systemic effects; gene therapies will depend on a more global understanding of dynamic interactions among genes and their cellular environment. Finally, and at a somewhat more philosophical level, there also is the fact that current experimental methods permit making falsifiable predictions, bringing modern biology closer to physics and chemistry as a science.
While classical theoretical biology dealt largely with ecology, or with whole organisms, biologists can now test hypotheses in a precisely targeted fashion. For example, if a mathematical model predicts that a certain mutation will make fruit flies grow a leg instead of antennae on their heads, the mutation can be carried out and the results observed."
Accuracy and Precision
The functional accuracy and precision found in an object is a direct reflection of the specificity and attention to detail of goal directed behavior required to produce the object. All of our design engineering science makes this clear. This is why a fine precision crafted mechanical wrist watch cannot be made with big clumsy tools like mallets and jack hammers. Similarly, big clumsy random mutation and natural selection (RM&NS) could not perform the extremely delicate assembly of amino acid chains that form functional proteins and DNA to form Gene-expression life from scratch.
