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Topic: The Characterization of Intelligent Causation
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aiguy
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posted 28. March 2007 13:30
I'm interested in reviewing Intelligent Design Theory from the perspective of our current understanding of intelligence. If intelligent causation is to be offered as a meaningful explanation of anything - whether it be the behavior of human beings or the origin of biological complexity - we must be able to positively* characterize this type of causation in way that is distinguished from other types.
We pursue our understanding of intelligence at multiple levels of abstraction simultaneously. At the most abstract, psychology defines intelligence simply as an opaque theoretical construct deduced from the covariance of performance we see on tests of specific mental abilities. Most concretely, the neurosciences attempt to tie these abilities to neural mechanisms. In between, cognitive scientists attempt to build models of our mental skills that are consistent with findings at either end of this explanatory spectrum.
If the assumptions of neuroscience are correct, and mental functions critically rely on particular types of neural mechanisms, then the explanatory domain of "intelligent causation" becomes highly constrained, applying only to biological systems that possess these or similar mechanisms. Design theorists generally discount these assumptions, for obviously if intelligence requires a complex biological mechanism, then explaining the origin of complex biological mechanisms by means of intelligence is problematic. But if the specific tests employed by psychologists to operationalize the meaning of intelligence cannot be applied in the context of ID, and the neurological basis for cognition is rejected a priori, the question becomes what, if anything, of our scientific understanding of mental phenomena can be employed by ID theory to give meaning to its sole explanatory construct, intelligent causation?
The design inference asserts an identity relation: "Whatever cause enables human beings to design artifacts is the same thing as the cause of biological complexity". If true, this is certainly a meaningful unification, like our unification of explanations of terrestrial and celestial motion, or of electrical and magnetic phenomena. But these unifications relied on detailed characterizations of the underlying causes, without which we would be unable to demonstrate that the same cause was in fact operative in these disparate phenomena. It was not possible, for example, to conclude that apples fell from trees for the same reason that the planets orbited the sun until Newton provided sufficient detail about his hypothetical force of gravity. A description of gravity as merely "a fundamental force which causes otherwise unexplained motion" would have been too abstract.
The question I wish to raise, then, is what unitary description of intelligent causation, at what level of abstraction, can serve to support the hypothesis that, for example, whatever enables humans to design a watch is the same thing as that which enabled some unknown entity or process to design the flagellum.
ID literature is currently unclear on this question, with few if any references to cognitive research. One prominent exception is the work of Jeffrey Schwartz at UCLA ( http://www.iscid.org/jeffrey-schwartz.php ), who interprets his work with OCD patients as evidence for mind/body dualism. Is Schwartz's conception of mental force sufficiently detailed to enable us to even begin to evaluate the unification of human intelligence and the design of biological structures? Are there other theories, such as those of Henry Stapp ( http://www-physics.lbl.gov/~stapp/PTRS.pdf ) or Penrose and Hammeroff ( http://www.quantumconsciousness.org ) that might be useful in this context? What are the prospects for empirically supporting ID's proposed unification of causes without some commitment to one or another of these theories?
* Note: By positively I mean "not negatively" rather than "with absolute certainty". In other words, we need to say what intelligent causation is rather than merely saying it is not any combination of fixed law and chance.
[ 20. April 2007, 18:53: Message edited by: aiguy ]
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LifeEngineer
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posted 29. March 2007 08:24
Quote: The question I wish to raise, then, is what unitary description of intelligent causation, at what level of abstraction, can serve to support the hypothesis that, for example, whatever enables humans to design a watch is the same thing as that which enabled some unknown entity or process to design the flagellum.
There are two critical elements in developing a definiition of intelligent causation that can be used for both human behavior and biological evolution. The first issue is 'who proposes and who approves definitions'. The second issue is 'what scientific criteria must be satisfied'
To somewhat simplify there are two types of answers to the 'who' question. The first type of answer suggests that a definition of intelligent causation must be established by, agreed upon, and acceptable to some group or groups of recognized experts. The type of answer to the who question is 'scientific definitions are developed by and agreed upon by the scientists formulating and testing relevant predictive theories'.
Most people, including aiguy I believe, are advocates of the 'academic consensus' type answer to who defines intelligence. The basic problem with such an approach is that it can not ever produce a workable definition and it can never resolve conflicts.
Although it is clearly the minority view, 'defined by scientists in association with predictive theories' approach is, IMO, the only workable approach to defining intelligent causation. My comments will be restricted to this type of answer to the who question.
If we assume that a definition of intelligent causation is developed by scientists formulating and testing predictive theories, then the first two requirements to be satisfied are that 1) the definition must be associated with predictive theories involving intelligent causation and 2)the definition must permit clear communications among the scientists formulating and testing these predictive theories.
A third, useful but not essential, requirement is that at least initially the definition of intelligent causation be associated with relatively simple or elementary forms of intelligent behavior. It is recognized that while the reductionist approach (isolating elmentary forms of the phenomenon being studied) is widely accepted in sceintific analysis, it does not appear to be a widely used approach used by those studying either evolution or human intelligence.
While I am fully aware that the approach or framework outlined here is not particularly popular with either ID proponents or ID opponents, it is a conventional hard science framework for defining intelligent causation. It is also, I suggest, a general approach or framework used by a lot of scientists who model and simulate intelligent behavior.
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aiguy
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posted 29. March 2007 14:16
The issues I've raised have nothing to do with "approval of definitions"; I've asked what sorts of characterizations of intelligence can be useful in establishing an identity relation (or even a meaningful "similarity relation") between human mentality and the cause of biological complexity. I am not interested in debating the authority of anyone to impose definitions, and you are mistaken to assume I advocate that current "academic consensus" should determine the matter. To consider the "who question" - as you put it - at all is strictly irrelevant.
You point out that a theory of intelligence must be predictive and clear; I don't see those as particularly controversial claims. But you have not addressed the issue, which is how ID can characterize intelligent causation. A "general approach or framework used by a lot of scientists who model and simulate intelligent behavior" is not a sufficiently clear answer. There is a multitude of specific approaches utilized in AI of course, but none are recognized as a canonical model of intelligence in general, much less one that can be applied in the context of establishing that the same model can be demonstrated to explain human cognition and the origin of biological complexity.
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LifeEngineer
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posted 29. March 2007 15:09
The question of 'who' is, of course, only relevant if the concern is with resolving or reaching concensus on a definition. Any individual or group can express subjective opinions on the subject, but if the goal is to reach scientific agreement then the 'who' is not only relevant but critical. If the concern is with achieving scientific agreement or consensus then, I suggest, the who must be limited to those actually formulating and testing predictive theories, and thus implicitly with those with the technical skills to formulate and test theories.
I might add that I am only describing the standards and criteria applicable to my comments. I obviously don't suggest those standards and criteria need apply to your comments.
My original comments only provided what I view as a useful framework for discussing definitions. I note that your comments also only addressed framework and not definitions. Some people might find it useful to hear your proposals for defining intelligent causation.
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aiguy
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posted 29. March 2007 16:56
Once again: Arguments from authority are completely irrelevant to the topic of this thread.
quote:
My original comments only provided what I view as a useful framework for discussing definitions. I note that your comments also only addressed framework and not definitions. Some people might find it useful to hear your proposals for defining intelligent causation.
I mentioned a variety of approaches to characterizing intelligence, at various levels of abstraction. To reiterate:
1) The approach of psychology, which is to consider intelligence simply as that which causes the covariance of scores on intelligent tests. This approach is unsatisfactory, since it lacks any model of the cause, and is inapplicable when the subject is not available for testing - as in the case of ID.
2) The approach of the neurosciences, which is to identify neural mechanisms that account for mental abilities. This is a tremendously active area of research, but it is also inapplicable in the context of ID, since we cannot study the neural mechanisms responsible for the creation of living things.
3) The approaches of Schwartz and Stapp, or Penrose and Hameroff, which seek to tie our understanding of mental abilities to various quantum phenomena. I don't believe any of these theories have found experimental support, nor is it clear to me how we could evince that the same quantum effects were at work in human cognition and in the origin of life. I bring these up to see if anybody else here has any ideas about these sorts of theories.
As for approaches in AI, there is no single theory that is a candidate for a general explanation of mental abilities. Each area of AI - speech, vision, language understanding, planning, diagnosis, and so on - have used models of information processing that are specific to each task, rather than a unitary, coallesced model of intelligence in general.
The twin goals of AI are to 1) achieve human competence in these different abilities, and 2) create a model that is consistent with neurological evidence and experiments in cognitive psychology. These goals are independent of one another; that is, we might succeed at (1) and fail at (2), or even the converse.
This is perfectly clear from the example of chess-playing: While AI has achieved the goal of human-level competence in playing chess, nobody believes that the methods employed are similar in any important respect to the methods that human beings use, and a series of cognitive experiments on chess players has confirmed this repeatedly (for example, experiments that measure the ability of human chess masters to remember board positions reveal that humans parse the board in ways fundamentally different from the way AI programs currently do).
And so I pose the question again: How can intelligence be characterized such that we can demonstrate that, for example, that which caused the existence of the flagellum is the same thing as that which enables a human to design a watch? I know of no way at all, which is why I have posed the question on this board.
[ 29. March 2007, 16:59: Message edited by: aiguy ]
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LifeEngineer
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posted 30. March 2007 07:26
Quote: Once again: Arguments from authority are completely irrelevant to the topic of this thread.
You are, of course, entitled to your opinion. To clarify, my comments did not advocate arguments from authority. In fact, I am suggest that it is unproductive to consider arguments from authority, particularly second and third hand authority, unless those ‘authorities’ can demonstrate a capacity to formulate and test predictive theories. In other words, it is my opinion that it is more productive to focus discussion on scientific definitions of intelligent causation that have been shown to be useful in formulating and testing predictive theories.
I am not aware that any of the three types of approaches you described have been used to produce predictive theories, and it seem unlikely that any of the three approaches has led to predictive theories in both the area of human behavior and evolutionary change. If you know of any successful applications of these approaches in formulating predictive theories I would be interesting in hearing of the applications. (I am aware that the psychological approach has had some demonstrated success in predicting school performance).
Your list does not appear to include the general approach most commonly used in simulating human intelligent behavior and the method that is most directly applicable to the scientific analysis of biological evolutionary change. For the lack of a better name, we might call this the computer simulation approach. Alternatively we might call it the intelligent, goal-directed, dynamic or programmable, information processing approach. By what ever name which wish to call it, this approach can produce definitions of intelligent causation that can be used in formulating and testing predictive theories.
The first step in discussing what I am calling the computer simulation approach to intelligent causation is identifying or isolating a relatively simple element or unit of intelligent behavior or intelligent causation. Probably the most common and easiest way to explain or describe this relatively simple unit of intelligent behavior is with a mathematical model or mathematical paradigm. The mathematical model or paradigm that is used to characterize a simple unit of intelligent causation can be described as the dynamic or programmable goal-directed logic machine or computer.
Essentially everyone who has worked with computer simulations will have had some exposure to this type of model or paradigm, although not necessarily using the same terminology I use. The following rough outline of the programmable goal directed logic machine should be recognizable to most people. The purpose of this outline is simply to identify the major components.
A MATHEMATICAL MODEL OF AN ELEMENTARY UNIT OF INTELLIGENT CAUSATION
The starting point for this model is the standard model for an input-output or information processing logic machine. It will be recognized that this type of logic machine can be defined in terms of:
1. Input variables (denoted by S)
2. rules for quantifying input variables
3. output variables (denoted as R)
4. rules for quantifying output variables
5. processing algorithms or functions( denoted by F or F(S)=R)
6. applicable environmental conditions
In order to address intelligent causation, there are a number of additional features imposed on this simple logic machine or input-output model. The two most obvious are that 1) the processing algorithm F is dynamic or changeable or programmable, and 2) the output, under appropriate conditions, is a member of the goal compatible subset of the set of possible outputs.
Readers with a working knowledge of mathematical modeling will probably recognize this as a fairly standard type of mathematical model. Readers without a working knowledge of mathematical knowledge are likely to have difficulty in following the discussion.
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aiguy
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posted 30. March 2007 11:04
quote:
I am not aware that any of the three types of approaches you described have been used to produce predictive theories, and it seem unlikely that any of the three approaches has led to predictive theories in both the area of human behavior and evolutionary change. If you know of any successful applications of these approaches in formulating predictive theories I would be interesting in hearing of the applications.
Of course these approaches lead to predictions in human studies. Psychologists can predict test scores. Neuroscientists can predict behavior changes based on various brain changes (induced by drugs, surgery, injury, disease, etc), and they can predict brain changes based on behavior changes (specific cognitive defects).
quote:
Your list does not appear to include the general approach most commonly used in simulating human intelligent behavior and the method that is most directly applicable to the scientific analysis of biological evolutionary change. For the lack of a better name, we might call this the computer simulation approach.
My last post discussed AI (Artificial Intelligence), which is what this is generally called. There is a huge literature associated with AI in dozens of journals; see for example:
http://www-lsi.upc.es/~miquel/aijournals.html
Once again, the point of the thread is how some particular characterization of intelligence can be used to evaluate the identity relation that ID claims exists between the causes of human behavior and biological complexity. All AI programs could be said to conform to your general description, but obviously not all AI programs can be shown to be plausible models of human cognition, as the chess example illustrates.
Evaluating the identity relation proposed by ID requires that one identify at what level of abstraction this relation is presumed to hold. If a human being and a computer can both play chess by virtue of processing information, does this mean that the same thing, "intelligence", is responsible for both behaviors, even if it can be demonstrated (e.g. by the cognitive experiments I've mentioned) that the type of processing is fundamentally different? If so, then that would be the answer to my question, and the characterization of intelligence implicated would simply be "information processing". If not, then at some more concrete level, the algorithms employed need to be shown to match the evidence from neuroscientific and cognitive psychological studies.
[ 30. March 2007, 12:44: Message edited by: aiguy ]
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2ndclass
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posted 30. March 2007 12:50
Since nobody's responding to the OP, I'll throw in some random, disjointed thoughts from a layman.
I think that framing the problem in terms of unification is the right approach. If there is a property that is shared by certain human artifacts and certain biological structures, and by nothing else in the observed universe, then it's worth our time to pursue a unified explanation.
I think most of us have a sense that there is, in fact, such a property, although we may have a hard time pinning it down. Maybe it can be described in terms of edge-of-chaos complexity. Strangely enough, I've never seen ID theorists address that area of research, preferring instead to use their own custom definitions of complexity, eg Dembski.
With regards to defining intelligence or design, theorists like Dembski claim that the first step is to infer design, and the next step is to find out who or what that entails. That's tantamount to saying that we should apply the label first and decide later what the label means.
And the ID movement has firmly resisted taking that second step. Some seem to hold that intelligence is outside of nature and exempt from definition. Salvador calls it an "undefined primitive".
If the commonality between biology and human artifacts is indeed describable in terms of edge-of-chaos complexity, then the question is whether there is a set of necessary conditions for such complexity to emerge. If so, then we could call that set of conditions intelligence.
Mitchell Waldorp's Complexity talks about the work that has been done to determine those conditions. Whatever they are, we know that the human brain meets them. The IDers' task would be to show that our pre-biosphere did not meet them, and therefore could not be labeled intelligent.
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Daniel Smith
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posted 30. March 2007 13:23
It would seem to me that 'Intelligence' could be defined as 'the ability to solve problems'.
Of course this is a very rudimentary definition, but I think it applies both to human designs and to biological complexity.
What we see in both are novel methods of problem solving which can be measured as to efficiency, simplicity and ingenuity. The latter being one of the key 'ingredients' of intelligence.
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aiguy
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posted 30. March 2007 14:03
2ndclass,
quote:
I think that framing the problem in terms of unification is the right approach. If there is a property that is shared by certain human artifacts and certain biological structures, and by nothing else in the observed universe, then it's worth our time to pursue a unified explanation.
It may be worth our time, but we cannot assume in advance that the same cause is responsible. Even if this property can be pinned down (and it's not clear that it can), our sample size of types of known things that can create it is 1, so it's hard to draw conclusions about the properties of other things that can create it.
quote:
With regards to defining intelligence or design, theorists like Dembski claim that the first step is to infer design, and the next step is to find out who or what that entails. That's tantamount to saying that we should apply the label first and decide later what the label means. And the ID movement has firmly resisted taking that second step. Some seem to hold that intelligence is outside of nature and exempt from definition. Salvador calls it an "undefined primitive".
Exactly so. Calling intelligence an "undefined primitive" is equivalent to Newton describing gravity as "a fundamental force which causes otherwise unexplained motion". As I pointed out in the OP, this would not have been sufficient to establish the identity of causes between terrestrial and celestial motion.
quote:
If the commonality between biology and human artifacts is indeed describable in terms of edge-of-chaos complexity, then the question is whether there is a set of necessary conditions for such complexity to emerge. If so, then we could call that set of conditions intelligence. Mitchell Waldorp's Complexity talks about the work that has been done to determine those conditions. Whatever they are, we know that the human brain meets them. The IDers' task would be to show that our pre-biosphere did not meet them, and therefore could not be labeled intelligent.
I haven't read Waldorp's book, but I think these ideas (mostly coming from the Sante Fe institute) are interesting. Like Kauffman's work, though, they are a long way from saying anything very concrete about either human intelligence or the origin of biological complexity.
However, I think you are spot-on about the general level of description that might allow us to draw parallels or establish what the connection is - or isn't - between human thought and the origin of complexity in the universe.
Daniel,
quote:
It would seem to me that 'Intelligence' could be defined as 'the ability to solve problems'. Of course this is a very rudimentary definition, but I think it applies both to human designs and to biological complexity. What we see in both are novel methods of problem solving which can be measured as to efficiency, simplicity and ingenuity. The latter being one of the key 'ingredients' of intelligence.
I think this idea is far too general to be useful here. There are endless examples of systems that "solve problems" in nature, but we don't tend to think of these as examples of intelligence. A river solves the problem of finding a path to the sea. Is its solution simple and efficient? I'd say so. How about "ingenious"? I think that's not something that we know how to measure.
The way clouds solve the problem of discharging their electrical charge to Earth is pretty ingenious; so much so that until a few hundred years ago, the cloud's uncanny ability to direct its lightning bolts to the highest point in the vicinity was taken as a certain indication that intelligence was involved. How else could the cloud look around and find the church spire and decide that is what it was aiming for?
[ 30. March 2007, 18:18: Message edited by: aiguy ]
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2ndclass
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posted 30. March 2007 15:19
I would also note that human design is usually detected on the basis of artificiality rather than ingenuity. It wouldn't make sense to say that intelligence is a prerequisite for something like Stonehenge, because if erosion were known to produce such formations, we probably wouldn't ascribe intelligence to erosion. So if we're going to associate intelligence with human artifacts, a lot of artifacts should be excluded in order to retain the intuitive sense of the word.
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aiguy
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posted 30. March 2007 17:00
Newton determined a specific model comprised of a property (mass) and a well-characterized relation (gravitational force). He showed that the very same relation (instantaneous, always attractive, inversely proportional to the square of the distance, proportional to the product of the masses and the universal gravitational constant) held true for both terrestrial and celestial motion.
So far, it appears, there is no candidate for a model of intelligence that can be shown to hold in both human cognition and the origin of biological complexity. If the model of intelligence is simply "an undefined fundamental force that causes complex specific information", then it is too general to be useful, just as it would be too general to describe gravity in terms of "an undefined fundamental force that causes motion".
Even if there was a property (like CSI) specific only to the artifacts of human activity and the structures in organisms (and that is itself subject to doubt), we still would have to apply a model of intelligence to both contexts in order to demonstrate the cause was the same. Otherwise, these objects may be caused by something unrelated. For example, the property of "being on fire" was once thought to be exclusively caused by chemical combustion (oxidation), and both a burning campfire and the burning sun were explained by this same cause. But we now know that the sun's fire is caused by a different cause, nuclear reaction.
Given this, I'd like to ask how ID proposes to support this claimed identity relation. Any ideas?
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LifeEngineer
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posted 31. March 2007 08:19
Quote: Once again, the point of the thread is how some particular characterization of intelligence can be used to evaluate the identity relation that ID claims exists between the causes of human behavior and biological complexity.
This is a good point but stated in a somewhat ambiguous manner. Scientific ID does start with the general observation that the intelligent design processes used by humans to design airplanes does appear intuitively to be analogous to the intelligent design processes involved in the design of birds. But what exactly is the meaning of this logical similarity or more specifically what is the significance of this analogy to scientific analysis of human behavior and evolution.
Various ID proponents have proposed all sorts of unproductive explanations for the logical similarity, many of them focused on the possibility of conscious intelligent agents or intelligent forces being involved in both types of behaviors. Although lots of people are and have pursued such approaches, I am not aware of any evidence that any of them have led to non-trivial predictive theories.
This brings us back to the basic computer or information processing model or paradigm that I discussed in my last post. As anyone familiar with abstract modeling and computer simulations should be able to recognize, the computer model outlined can be and is used to model and simulate both human behavior and evolutionary change. In addition, the basic information processing model or paradigm can be used to model and simulate computer behavior, developmental processes, and the behavior of hurricanes. As far as is known or as far as anyone has been able to demonstrate, the basic information processing model can be used to model and simulate any behaviors associated directly or indirectly with life forms. Does anyone disagree? There is evidence of phenomenon that can not be modeled perfectly by the basic information processing model, but for behavior of interest to science, the information model appears to produce useful approximations. Correct?
Back to aiguy’s question- One answer or one approach is to define intelligent causation in terms of the basic information processing model. The definition developed in terms of this model would then be applicable to the modeling and analysis of both human intelligent behavior and biological evolution. Such a definition of intelligent causation would also be applicable to a wide range of other goal directed behaviors.
There really is no reason for anyone to question the existence of the information processing model or paradigm nor is there any real reason to question that the paradigm is used in essentially all analysis involving computer modeling and simulation. Correct?
The ‘controversy’ surrounding the use of the information processing model or paradigm to define intelligent causation involves the question of the completeness or adequacy of the model, paradigm or approach. Does or does not the information processing paradigm leave out some component or phenomenon essential to the formal scientific analysis of intelligent causation?
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Daniel Smith
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posted 31. March 2007 13:37
aiguy:
quote:
I think this idea is far too general to be useful here. There are endless examples of systems that "solve problems" in nature, but we don't tend to think of these as examples of intelligence. A river solves the problem of finding a path to the sea. Is its solution simple and efficient? I'd say so. How about "ingenious"? I think that's not something that we know how to measure.
The way clouds solve the problem of discharging their electrical charge to Earth is pretty ingenious; so much so that until a few hundred years ago, the cloud's uncanny ability to direct its lightning bolts to the highest point in the vicinity was taken as a certain indication that intelligence was involved. How else could the cloud look around and find the church spire and decide that is what it was aiming for?
The question then, is:
Do the earth's hydraulic, gravitational and weather systems show evidence of intelligent design?
Attributing "intelligence" to the water and clouds is just as irrelevant as attributing "intelligence" to DNA, any other biological system or any human invention for that matter. We are talking about whether or not these systems have intelligence as their first cause, not whether they are intelligent in themselves.
[ 31. March 2007, 13:39: Message edited by: Daniel Smith ]
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aiguy
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posted 31. March 2007 17:45
LE,
quote:
This is a good point but stated in a somewhat ambiguous manner. Scientific ID does start with the general observation that the intelligent design processes used by humans to design airplanes does appear intuitively to be analogous to the intelligent design processes involved in the design of birds. But what exactly is the meaning of this logical similarity or more specifically what is the significance of this analogy to scientific analysis of human behavior and evolution.
Right. The ambiguity is built into ID as it's explained in books and papers by prominent ID theorists, since they explicitly refuse to speculate on the nature of the intelligent causation they offer as their explanation.
quote:
Various ID proponents have proposed all sorts of unproductive explanations for the logical similarity, many of them focused on the possibility of conscious intelligent agents or intelligent forces being involved in both types of behaviors. Although lots of people are and have pursued such approaches, I am not aware of any evidence that any of them have led to non-trivial predictive theories.
Agreed.
quote:
This brings us back to the basic computer or information processing model or paradigm that I discussed in my last post. As anyone familiar with abstract modeling and computer simulations should be able to recognize, the computer model outlined can be and is used to model and simulate both human behavior and evolutionary change. In addition, the basic information processing model or paradigm can be used to model and simulate computer behavior, developmental processes, and the behavior of hurricanes.... Back to aiguy’s question- One answer or one approach is to define intelligent causation in terms of the basic information processing model.
As you've described it here, this "basic information processing model" appears pretty much tantamount to "Turing computable". The claim that all processes are Turing computable may or may not be true, but even if it is, it isn't much of an explanation of anything. It certainly doesn't help us make a meaningful statement about an identity relation between two processes.
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