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Author
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Topic: The Characterization of Intelligent Causation
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nosivad
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Member # 767
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posted 14. August 2007 08:42
Theories are not subject to "selection as the best." Sensu strictu a theory is a verified hypothesis so it is by definition valid. Has Einstein's Relativity Theory been accepted because it is the best one? Heaven's no! Darwin's so called Theory of Evolution is nothing of the kind. First of all, evolution is not a theoretical consideration as it is an established undeniable reality. Those who deny organic evolution cannot be considered to be scientists any more than can those who insist on an evolution produced by randomly produced and selected variation. Both perspectives are incompatible with tangible, experimentally verified reality. There was never a role for chance in either the origin or the subsequent evolution of life.
George Wald, a Nobel Laureate for his studies on vision, at least had the sense to call his "organic soup" an hypothesis, not a theory. The word "theory" has so many dictionary meanings that it has lost all usefulness. It has come to often mean nothing more than idea, notion or opinion.
We should remember this when we see folks like Life Engineer continue to throw "theory" around with such careless abandon. Words have meaning only if they are carefully chosen. Otherwise it is best not to use them at all!
"A past evolution is undeniable, a present evolution undemonstrable."
John A. Davison
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LifeEngineer
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Member # 3446
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posted 15. August 2007 08:23
PROCEDURES FOR SELECTING THE BEST THEORIES
As proposed elsewhere, ‘Selecting the Best Theories’ analysis is the technique used to demonstrate both the rarity of scientific competence and the academic distortions (delusions) produced by a failure to select out those lacking adequate scientific competence.
As should be obvious, the conventional academic model of ‘do experiment-publish results’ is really not an appropriate model for ‘select the best’ analysis. Useful productive discussion of this analysis requires an interactive model and medium. One reason for the use of an interactive medium is that the analysis is progressive. The theory or theories selected today by this analysis may well be superseded or replaced tomorrow.
A second important reason for the use of an interactive medium is the need to subdivide readers into two distinct classes- 1) readers who are non-participating spectators lacking demonstrated scientific competence and 2) readers who are active participants with the opportunity to demonstrate scientific competence relating to specific aspects of the analysis.
An interactive medium offers non-participating spectators the opportunity to ask questions and make suggestions. However, it is recognized that non-participating spectator are not interested in having their scientific competence tested or demonstrated. Their subjective opinions are therefore characterized as non-competent.
An interactive medium offers any reader the opportunity to become a participant and to demonstrate competence either with respect to the analysis as a whole or with respect to some specific sub-issue or specific set of sub-issues. The requirements for participation are that 1) a potential participant present and be prepared to defend a specific position within the context of the analysis being performed and 2) the participant be prepared to accept the conclusions produced by the analysis.
Past experience with this format shows that few if any Internet posters are either willing or able to participate in this type of formal analysis. If, as seems likely, no one comes forward to participate in defense of the academic position, I will present the academic position using a dummy identify called woodguy.
TO BE CONTINUED
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LifeEngineer
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posted 15. August 2007 09:42
SELECTING A TOPIC
The first step in this analysis is to pick a subject involving some type of intelligent causation. Keep in mind that in selecting a topic we are trying to determine if 1) the applicable academic science will successfully ‘select the best theory’ and if 2) the academics controlling the selection of theory process can demonstrate scientific competence in the scientific analysis of the subject being evaluated. Defenders of academic science might want to select a topic where they believe that there are valid theories recognized by academic science and where the theories recognized by academic science are superior to intelligence based teleological theories. Good luck in finding such a topic.
For someone simply interested in seeing a demonstration of select the best theory analysis, I suggest starting with some practical problem that either has been or needs to be solved by scientific analysis. As a starting point, it might be useful to look at a simple or even trivial problem.
I am open to suggestions for a topic to use to demonstrate select the best theories analysis.
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Arjun
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Member # 6108
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posted 15. August 2007 17:09
quote:
I am open to suggestions for a topic
What about whether climate change is a real phenomenon.
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LifeEngineer
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posted 15. August 2007 19:14
I am traveling for a few days, but global warming is a good a subject as any. So what in your view are the 'best' predictive theories on the subject?
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LifeEngineer
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posted 20. August 2007 07:28
Climate change has been proposed as a topic to illustrate ‘select the best theories’ analysis. It is useful to start this discussion by noting that global warning and climate control fit the classic model and definition of intelligent causation and design by intelligence. As with any issue of intelligent causation, climate control starts at some point with a goal and a problem that may reduce the likelihood of achieving the goal. In the example of global warming, the goal is survival and the problem is climate change (or potential climate change) that may endanger survival.
At some point in time, a goal and a problem exist but no solution. Intelligent causation MAY eventually produce a solution to the problem and the solution MAY increase the likelihood of survival. Global warming, like all problems addressed by intelligence may have a solution or solutions and intelligence may produce solutions, but intelligence may also fail to produce solutions or the solutions produced may not be adequate to achieve the goal. Global warming may result in the extinction of the human species.
While solutions to the problem of global warming may be new or novel, the model or framework or structure for finding an intelligent solution is not new. The intelligent or intelligent design solution to the problem of climate control, if it is found, will involve some combination of 1) methods of maintaining some equilibrium (preventing change) and 2) adjusting or adapting to climate change.
As is obvious to everyone except those blinded by academic dogma, humans are not the only biological life forms that use intelligence to intelligently design solutions to problems and that use intelligence to achieve goals. Life forms were dealing effectively with problems like climate change long before human intelligence evolved.
Again, global warming is a problem that fits the classic model of ‘to be solved by intelligent design or intelligent causation’. Although the situation currently being addressed may have some novel features, the basic structure or form of the problem is the same as the structure or form of climate change problems that life forms have been addressing for many millions of years.
When we turn our attention from a general discussion of intelligent design or intelligent causation to the more specific issue of human intelligent causation applied to the current issues of global warming and climate control, we need to look at two broad classes of human problem solving- 1) human problem solving using hard science analysis and 2) all other forms of human problem solving including academic soft science and religion. As is generally recognized, or if you prefer it is hypothesized, that hard science analysis is a materially or measurably more effective and efficient method of intelligent problem solving than other human problem solving methodologies.
Select the best theory analysis is based on the further premise that truly effective hard science analysis will consistently select the best available theory. If academic problem solving begins to select theories other than the best available, then the academic ‘science’ is departing from hard science analysis and the result is likely to be a material reduction in problem solving effectiveness.
Global warming is an interesting topic for select the best theory analysis because it both provides examples of both highly effective hard science analysis and highly ineffective and wasteful soft science analysis.
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LifeEngineer
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posted 20. August 2007 10:21
As stated, Global warming/climate change analysis provides examples of both effective hard science analysis where ‘the best available theories’ are routinely selected and ineffective analysis where the scientifically incompetence fail to select the best theories. It is probably best to start by looking at the use of effective hard science analysis in climate change analysis.
All applied science analysis, and arguably all hard science analysis begins by identifying and defining a goal or goal variable. In hard science analysis of climate change, the defined goal is human survival and more generally the survival of ecosystems where humans can thrive.
Given an identified goal, hard science analysis then identifies situations where the goal may not be achieved and then looks to identify changes that can be made to increase the likelihood of achieving the defined goal. Having identified a goal and framed a goal related problem in this manner, the hard science analyst can now formulate a predictive theory or more accurately a family of predictive teleological theories of the general form “Within defined constraints, F(G, S) =R”
The hard science analyst may initially know little more than that he has a goal he would like to see achieved. Even this limited knowledge can be fit to a member of the identified family of teleological theories. As the scientist gradually learns more about the behaviors or responses that can increase the likelihood of achieving the defined goal and the stimuli or input that can trigger these responses, the scientist gradually refines the teleological theory. The process of refining predictive teleological theories involves formal scientific testing.
If you perform select the best theory analysis at any stage of a successful hard science analysis, you will find the current best theory is always some member of the initially identified family of teleological theories. The specific theory selected will change as knowledge accumulates, but the ‘current best theory’ will always be a teleological theory. [Note that in analyzing complex phenomena, the scientist may break the single teleological theory into a large set of logically consistent theories. It is possible that included in the set will be physics type theories, stochastic theories, and trivial theories as well as teleological theories. For the time being, the discussion is focused simply on teleological theories.]
The current global warming or climate control analysis began with the observation that global climates might be warming and the observation that this climate change might have a negative impact on at least some humans. Given the goal of human survival, these initial observations translate into the standard teleological theory format. If it is assumed that climate change is potentially harmful, then the goal becomes to produce responses that will prevent climate change.
At an early stage in global warming analysis, possible correlations were observed 1)between human fossil fuel consumption and atmospheric CO2 levels and 2)between atmospheric CO2 levels and average global temperatures. These observations suggest that one part of climate control might involve something like a CO2 regulator where increases in atmospheric CO2 levels triggers actions that reduce CO2 levels. As should be reasonably obvious, there are all sorts of unresolved hard science issues surrounding this approach. However, recognizing the limitations of existing knowledge, CO2 regulator type theories provide the best fit to the available data.
If we look just at the CO2 part of the global warming issue, select the best theory analysis supports the assertion that a teleological CO2 regulator type theory provides the best fit to the available knowledge and data. If we list one by one the criteria that must be satisfied by a testable predictive hard science theory, we will find that the CO2 regulator type theories satisfy all the requirements. I am not aware of any alternative theory that can satisfy all the hard science requirements. If anyone is actually interested in seeing some of the hard science requirements and how CO 2 regulator theories can satisfy the requirements I will be glad to start going into the details. If anyone can propose an alternative theory to fit the data, I will be glad to start performing select the best theory on the proposed alternative.
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LifeEngineer
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posted 20. August 2007 13:30
A couple of general observations regarding ‘CO2 regulator type theories of climate change’. First, most people should be able to recognize that the concept of a CO2 regulator fits in with most of the hard science research being performed on the subject of CO2. Hard science analysis has been attempting to demonstrate that human activity may be responsible for observed increases in CO2 levels. Hard science analysis has been attempting to demonstrate that increases in CO2 levels are one factor associated with global warming. If both of these can be demonstrated, then it follows logically that some types of human activity could reduce CO2 levels which could in turn reverse the observed global warming.
Second, very few people understand or recognize or accept that this type of analysis translates directly into existing hard science theories. Lots of people accept the concept or principles that formal testing of predictive theories is the centerpiece of the scientific paradigm, but very few people have the scientific competence to understand how scientific theories are formulated or to recognize theories when they are formulated.
Third, select the best theory analysis simply involves looking at predictive theories that are presented and determining if the presented theories meet the formal requirements for predictive scientific theories. Surprisingly few academic scientists have the skills and talents to participate in such analysis.
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Arjun
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Member # 6108
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posted 20. August 2007 15:11
A statistical approach would surely be the best method. It works very well in actuarial calculations, after all.
[ 20. August 2007, 15:12: Message edited by: Arjun ]
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LifeEngineer
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posted 21. August 2007 08:17
UNDERSTANDING SCIENTIFIC INCOMPETENCE
If the analysis of intelligent causation required understanding advanced calculus or advanced statistical analysis, we would not be particularly surprised to find that only 5 in 100 or 1 in 1000 life scientists actually had a working knowledge of the required mathematics( the actual ratio will depend on the level of competence measured). Any one who sits in a math class with life scientists or anyone who has watched people with advanced mathematical training attempt to apply that math in a novel manner, has a realistic understanding of how few people ever attain a working knowledge of any complex form of mathematics.
Since life scientists generally don’t understand statistic or differential calculus, it should come as no real surprise that 95 out of a 100 or 999 out of a 1000 life scientists actually lack the scientific competence to understand defining and quantifying variables and fitting the resulting data to mathematical algorithms. Considering that there is no serious effort to teach the applicable skills and concepts to life scientists, the lack of scientific competence at basic theory formulation skills should not be surprising.
The actual rarity of scientific competence can be measured by asking individual scientists to actually produce and/or defend specific predictive theories. Global warming and the CO2 regulator concept provide a good basis for testing scientific competence. A large portion of both scientists and interested observers will claim to understand the CO2 regulator concept, (whether they agree or disagree with the concept), but very, very few of these individuals will actually be able to produce or understand or evaluate predictive theories based on the concept.
Confusion about the rarity of scientific competence arises because academic science permits and even encourages people to make false and misleading claims concerning scientific competence. By accepted academic standards, scientific competence is established by doing a Google search and shouting ‘I agree with this’. Obviously many more people can pass the academic test of competence than can actually formulate or evaluate predictive theories.
It should be noted that while real scientific competence is relatively rare, such competence clearly exists. It should also be noted that the problem solving productivity of the scientifically competent is very high (if their work is not hindered by the scientifically incompetent).
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Daniel Smith
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Member # 3004
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posted 21. August 2007 21:14
I see this thread has wandered off the original topic.
I came across this article on how scientists expect to be able to create artificial life in 3-10 years, and thought this would be a good time to make a prediction.
They'll be unsuccessful.
I especially like this part: quote:
once the container is made, if scientists add nucleotides in the right proportions, then Darwinian evolution could simply take over.
We'll see.
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LifeEngineer
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posted 22. August 2007 06:30
I suppose discussing an actual application of the scientific analysis of intelligent causation would be considered off topic by those who see the analysis of intelligent causation as a non-scientific endeavor.
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LifeEngineer
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posted 22. August 2007 10:24
The ‘problem’ with scientific incompetence is not simply the lack of scientific competence. In the absence of an effective methodology for removing scientific incompetents from the scientific analysis process, these individuals actively disrupt and corrupt the analysis process. Global warming/climate change analysis provides some excellent examples of disruption and corruption introduced by scientific incompetents.
In a relatively new area of research, scientific incompetents simply represent a drain on the limited resources available for research. Because incompetent individuals are far more numerous than competent scientists, a very large portion of research resources get diverted from productive research.
The drain on resources will worsen over time if the scientific incompetents gain control of the resource allocation process. In part, this occurs because incompetents limit resource allocation to members of their in-group. Initially they permit resources to be allocated to members who performing analysis not associated with testable predictive theories. Eventually, the incompetents will begin to restrict acceptable research so as to exclude or not permit research involving the testing of predictive theories. Because climate research is a multi-disciplinary topic that involves fields that are already corrupted by scientific incompetents, parts of climate research already shows signs of advanced corruption.
The following three topics illustrate disruption and corruption in the analysis of global warming issues by scientific incompetents:
1. Failure to recognize the capacity of living systems for intelligent adaptive change
2. Failure to recognize the possibility of existing intelligent climate control mechanisms.
3. Failure to properly recognize the role of intelligent adaptation of human decision making behavior.
In all three instances there is productive scientific analysis that could be performed based on ‘the best currently available predictive theories’. But in each instance, the groups controlling research in the area involved fail or refuse to recognize the best available theories and instead fund research based on flawed theories or on the absence of valid theories. For all three issues, select the best theories analysis can be used to demonstrate the disruptive role of scientific incompetence.
FAILURE TO RECOGNIZE INTELLIGENT ADAPTIVE CHANGE
Not surprisingly, our friends from biology are guilty of corrupting climate change analysis. PBS and the news media seem to have daily reports of the form “Global warming will cause the extinction of polar bears or some other species or group of species”. This type of Chicken Little ‘The sky is falling’ type of report may make for exciting newspaper articles, but it is incompetent and unproductive science.
I doubt if anyone seriously doubts that climate change has an impact on both individual species and on biomes. However, the usefulness of any research into the topic depends on how the issue is framed and this in turn depends on the types of predictive theories being tested and refined.
There are two (or at least two) general types of predictive theories that can be used in the scientific analysis of the capacity of living systems to adapt to climate change. The only type of theory recognized or accepted by academic biology is the Darwinian type theory that asserts that 1) each species evolves a near optimal form fitted to the environment in which it lives, and 2) a species will adapt to a new environment outside the range of its existing environment only via a process of random variation and natural selection.
This type of theory leads to general predictions of the type ‘if climate changes somewhat rapidly and produces an environment outside the existing range, then the species involved us likely to become extinct”. As should be apparent, this is the logic is the basis for lots of unproductive published Chicken Little research reports.
The second type of predictive theory dealing with adaptation to climate change is the intelligent design or intelligence based teleological type theory. Such theories make assertions or testable predictions of the general type “Within definable constraints, organisms and biomes can intelligently redesign themselves to adapt to changes in environmental conditions (organisms and biomes can efficiently redesign themselves in order to achieve the goal of survival)”.
As should be apparent, Darwinian theories lead to essentially useless and meaningless Chicken Little predictions. Teleological theories lead to efforts to understand the mechanisms involved in intelligent redesign and to better understand the limits or constraints applicable to intelligent redesign.
It seems likely that people lacking a proper level of scientific competence, will not be able to visualize or understand that select the best theory analysis will, for this type of analysis, consistently select the intelligence based teleological theories.
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LifeEngineer
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posted 23. August 2007 06:37
FAILURE TO RECOGNIZE EXISTING INTELLIGENT CONTROLS OF CLIMATE
Control of research funding and reporting by scientific incompetents produces stagnation in two ways. First, by focusing research efforts on non-predictive and non-testable theories, scientific incompetents make it impossible to resolve issues and make it impossible to reject flawed ideas. When scientific incompetents are in charge, endless research is performed without ever producing any scientific progress and without ever resolving controversies.
The second problem with ‘control by scientific incompetents’ is the limitations and restrictions on potentially productive research. Global warming and climate control provide a number of interesting illustrations of the phenomenon. If the scientific incompetents controlling research funding and reporting don’t recognize teleological climate control theories and they don’t recognize that the role of goal directed intelligence in biological systems, then it is not surprising that they will suppress research into the possibility that living systems may already be engaging in some forms of intelligent control of climate.
If the activity of humans is capable of producing undesirable impacts on climate, then it seems logical and likely that other types of organisms have also produced undesirable impacts. Since live on earth persists despite potentially harmful impacts of living systems, it seems almost inevitable that there are intelligently designed adaptations to offset or control the undesirable impacts on climate. It seems logical or likely that some of these intelligent adaptations involved some level of climate control.
If it were not for the refusal of academic incompetents to recognize the role of intelligent causation in living systems, we might see research into the question of existing mechanisms of intelligent biological control of climate. It seems likely that human efforts to understand climate control mechanisms could be greatly enhanced by looking for possible existing non-human intelligent climate control processes and mechanisms.
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IF
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posted 23. August 2007 17:47
LE.
Just for my own peace-of-mind, please answer the following:
1. What level of education did you reach?
2. In what country did the majority of your education take place?
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