Archive for January, 2011

January 31, 2011

Purpose (5) – nature and purpose

by Neil Rickert

It seems obvious enough that purpose, as I have been describing it in this series of posts, is entirely natural.  However, some ID (intelligent design) proponents probably disagree.  In this post, I shall explain why I believe it to be natural.  I have already provided much of the basis for seeing that purpose is natural, in that I have connected it with measurement.  However, the examples that I have used, such as the thermostat, are man made.  In particular, the measurement aspect of the thermostat is the result of human design.  Thus we might expect some ID proponents to claim that they show the need for an intelligent designer.

In order to complete the picture, I need to provide examples of natural measurement.  For that, I want to turn attention to homeostatic processes.  To say that a process is homeostatic is to say that keeps itself in some sort of equilibrium.  Such homeostasis works on the basis of feedback, where the process is reacting to its own current state and modifying its behavior in ways that tend to keep it in a reasonably stable range.  That feedback is a form of self-measurement.  Thus a naturally occurring homeostatic process already exhibits natural measurement.

January 25, 2011

Politics simplified

by Neil Rickert

Pragmatist:  If it ain’t broke, don’t fix it.

Conservative: It ain’t broke.

Religious conservative:  It wasn’t broke 2,000 years ago.

Progressive: Newer is better.

January 24, 2011

Purpose (4) – chaos

by Neil Rickert

In earlier posts in this series, I have pointed out places where there is apparently chaotic behavior.  In this post I shall further comment on chaos.

I’ll start by indicating why I have been mentioning it.  Many people seem to take the view that we could manage with only using mechanistic explanations, and that the vocabulary of intentions is unnecessary, though perhaps convenient.  For example, that appears to be the view of that Dennett is suggesting in his The Intentional Stance.  I mentioned examples of chaotic behavior because they are cases where mechanistic explanation breaks down, and thus fails to be adequate.  Thus they show that mechanistic explanation is not adequate, and that there are cases where we need teleological explanations.

Now it may be that the world is still entirely mechanistic, and that mechanistic explanation fails for chaotic behavior because as finite beings we are limited in the amount of information we can have, and we cannot have enough for a full mechanistic explanation.  Or it could be that the world is not entirely mechanistic, and a mechanical explanation could not be completed even in principle.  You, the reader, will have to decide which of those positions you want to take.  I will present my current tentative view at the end of this post.

January 17, 2011

Purpose (3) – measurement and purpose

by Neil Rickert

In this post, I plan to connect the notion of purpose to that of measurement.  Here, I am using “measurement” to refer to the process of measuring, rather than to an individual item of data.  I could not find much in the way of a philosophical account as to what measurement is, though a google search for “philosophy of measurement” (with the quotes) turned up some references to metrology and some discussion of the problems of measurement in psychology.

Measurement and chaotic behavior

I will be interpreting “measurement” quite broadly, so that much of what we consider to be ordinary observation can be considered to be measurement.  Our ordinary experience in measuring things is generally a good guide to what counts as measurement.  In particular, when we are measuring something, we normally expect that the result of that measurement will be a decimal number.  While scientists mathematically model measurements as being real numbers from a continuum, actual practical measurement gives discrete values of limited precision.  So a measuring process is a discretizing process, or something similar to a digitizing process.  Because of this discretizing and because of limits of measuring equipment, measuring typically gives approximate but inexact results.

The process of measuring is a purposeful one.  Or at least that is how I see it.  However, it seems to be a common view that perception is passive (see the Wikipedia entry), so those who see perception as passive might also consider observation to be passive.  And that could lead to disagreement over whether measurement is a purposeful activity.  My main aim, that of connecting measurement with purpose, does not depend on assuming that measurement is a purposeful activity.

When measurement is carried out by people, such as when using a ruler to measure the width of a window, it isn’t clear that it makes sense to talk about that measuring being a chaotic process.  We would, instead, tend to think of it as inherently ambiguous.  For example, if that window is just between 31.6 inches and 31.7 inches, then we might be unsure which of those two measurements to choose.  When we automate measurement, as with a digital thermometer or a digital voltmeter, that same problem does show up as a chaotic process.  A tiny change in the input causes the digital measurement reading to jump from one value to the next.  When we idealize measurement mathematically, the ideal measurement value is a discontinuous function (a step function), and it is that kind of discontinuity in the idealized measurement that leads to chaotic behavior in an automated measuring system.

The same problem of ambiguity or chaos shows up for simple observations.  A cat enters the room, walks over to the mat in front of the fireplace, and settles there.  At the end of this, “the cat is on the mat” will be true, but when the cat just entered the room it would have been false.  There will be a stage where it is ambiguous as to whether we should say that “the cat is on the mat” is true or false.  If we were to setup an automated “cat on the mat” detector”, then it would behave chaotically at the stage where it is making the transition from false to true.

Purpose and measurement

Here is how you can construct an automated system or robotic system with apparently purposeful behavior.  First identify what you consider the purpose, and then devise a way of measuring the extent to which that purpose has been achieved.  We then program the automated system so that it periodically measures its degree of purpose achievement, and then takes action intended to move it closer to that goal.

The programming could amount to using an algorithm that moves the system closer to its goal.  Or it could even be a trial and error procedure, that tries something and if that doesn’t work, tries something else.  The use of randomness could be part of that trial and error procedure.  As it finds something that seems to work (as determined by the periodic measurements, the trial and error program can attempt modifying what works to find an even better way of solving the problem.

The house thermostat is an example of just this.  The thermostat measures whether the room is warm enough (i.e. meets the intended purpose of the thermostat), and if not it turns on the heating system so as to heat up the house.  As another example, consider the heat seeming anti-aircraft missiles.  Once the missile has been targeted on a heat source (typically the jet engine of an enemy aircraft), it attempts to reduce its distance from that heat source to zero by modifying its own motion.  We can see that as having a purpose of colliding with the enemy aircraft (the heat source).

A theory of purpose

As a tentative theory of purpose I want to suggest that, at least within scientific discussions, we should take “purpose” to mean just such a measurement controlled program as just considered.  In ordinary non-scientific conversation, “purpose” is sometimes used in other ways.  However, we should be more careful about usage when using “purpose” scientifically.  Specifically, we should use the terminology of purpose, only when we have reason to believe that there is some kind of measurement going on, with a program of behavior that is controlled by the measurement in a way that is likely to achieve the indicated purpose.

To illustrate this, I would like to analyze some examples, including those mention by Eric Thomson in a comment to my previous post in this series.  One of the examples he mentioned was “a (naturally formed) system of gulleys in a mountain side that tended to somehow sort small and large stones into two piles.”  In that case, I see no measurement going on, so I see no basis for considering that to be the following of a purpose, except in a metaphorical sense.  Contrast that, however, with the apple orchardist who has a system of moving belts and diverters to sort the apples by size.  In that case, the orchardist would be checking on the sorted apples, and adjusting his apparatus so that it sorts them as wanted.  That checking is a kind of measurement of whether the purpose is being achieved, so it would be appropriate to describe apple sorting as the purpose of the apparatus.

For another example, consider the heart (also mentioned by Eric Thomson).  It is often described as having a purpose of pumping blood through the body, though that is not how Eric describes it.  However, I cannot see anything measuring whether that purpose is achieved.  However, there are biological feedback system that are, in effect, measuring whether the heart is rhythmically pushing blood out into the arteries, so we can reasonably describe that as a purpose.  And note that what Eric says is the purpose fits that well enough.

January 10, 2011

Purpose (2) – Teleological explanation

by Neil Rickert

Briefly, a teleological explanation is an explanation based on a purpose.  The thermostat, for example, has the purpose of maintaining a suitable temperature, and we often explain its operation in terms of how it meets that purpose.  Biologists sometimes talk of teleonomic explanations.  An explanation is said to be teleonomic if it is based on apparently purposeful behavior, and teleological if it is based on a purpose arising from a conscious agent.  Since I am not particularly concerned with the role of consciousness here, I shall not make that distinction and will use “teleology” to describe both cases.

Mechanistic explanation

Teleological explanation can be contrasted with mechanical explanation.  A mechanical explanation is one based on the idea of physical matter in motion, as described by laws of physics.  When we describe the behavior of objects using Newton’s laws of motion and Newton’s law of gravity, we are providing a mechanistic explanation.  No purpose is assumed by such an explanation, so the mechanistic explanation is entirely non-teleological.  Scientists usually prefer mechanistic explanations, where they are available.

Chaotic behavior

Mechanistic explanation can break down, when there is chaotic behavior.  Chaos, as I am using the term, is well described by:

Mathematically, chaos refers to a very specific kind of unpredictability: deterministic behaviour that is very sensitive to its initial conditions. In other words, infinitesimal variations in initial conditions for a chaotic dynamic system lead to large variations in behaviour.

When a mechanistic explanation deals with chaotic behavior, the explanation is of limited use.  In particular, it is unable to make reliable predictions.

Example – the thermostat

We can think of the thermostat typically used as part of a heating system for a house.  The thermostatically controlled system keeps the house at a near uniform temperature.  The thermostat, as a simple device, is part of the controlling functionality.  If we ignore the electrical aspects, then a thermostat has a simple mechanistic description.  In the traditional version, a bimetallic strip bends as it is heated, due to the differential expansion of the two metals.  And this bending brings two surfaces (usually part of a switch) into contact.  Once we include the electrical characteristics, things become a bit more complicated.  The switch does not instantly go from open to closed.  Rather, the resistance of the circuit goes from very high (open circuit) to very low (closed circuit).  The transition in resistance is chaotic, and that limits the accuracy of a mechanistic account of what happens.  However, the fact that the electrical transition is chaotic does not interfere with the intended purpose of the thermostat.  So we can give a good teleological account without getting into the details of the chaotic behavior.

Pseudo-mechanistic explanation

Typically, the full thermostatically controlled system is explained by describing the thermostat as switching from open to closed (or from off to on) when it reaches the set temperature.  But when we describe it that way, we are not giving a mechanistic account of the thermostat, for we are not talking about parts in motion.  We have, in effect, replaced the thermostat in our description with an abstract ideal machine that just switches.  The full explanation of the thermostatically controlled system, when given that way, has the general form of a mechanistic explanation, except for our substitution of the ideal abstract machine for the actual mechanism of the thermostat.  I shall use the term “pseudo-mechanistic” for an account that has the general form of a mechanistic explanation, but is based on the “mechanism” of an abstract ideal machine.  Such an explanation is implicitly teleological, for we have constructed that abstract ideal machine based on the intended purpose of the actual thermostat.

When it comes to pseudo-mechanistic explanation, the big example is the digital computer.  We typically explain its operation in terms of logic gates, flip-flops, latches, etc.  The flip-flop is used as a one-bit memory device.  Electrically, it is a transistor like component, but with the transistors operating in a non-linear region.  We normally describe it as having two stable electrical states, and being switchable between the two.  The states might be indicated by a voltage or a current flow, depending on chip design.  The transition from one electrical state to the other is chaotic.  We often describe this as a memory cell which can have the value 0 or 1, and in using that description we do not mention the electrical values.  Likewise, a logic gate is usually described as having an output value of 0 or 1, depending on the inputs.  Again, the actual physical device has output voltages or currents (depending on chip design), and the transition between the output levels that we label “0” and “1” is chaotic.  In typical computer explanations, we describe the logic gate as an idealized abstract machine that can have an output of 0 or 1.  Our explanation of computer operations is in the form of a mechanistic explanation, except that it is based on these abstract ideal machines such as logic gates.  And our use of abstract ideal machines is based on the intended purpose of the actual electrical circuits, so is implicitly teleological.  There’s a bit of an irony here, for AI (artificial intelligence) proponents are often outspoken in their favoring a mechanistic view of everything, yet they rely on a teleological account of their computers.

Purpose in biology

When the inputs to a neuron reach a sufficient level, the neuron “fires” and transmits a signal.  This is usually described as a threshold event, with the neuron activating (or firing) when the input reaches a threshold.  With threshold events, there is a large output change from a small input change (that last little bit of input that pushed to the threshold).  And because of that, we should consider the operation of the neuron to be chaotic.  This is an example of an apparently purposeful action of a biological cell, though it is hard to be precise about what we should consider the purpose, since the operations of the brain are not yet fully understood.

When we talk of a struggle for survival, we are using teleological language, and assuming some sort of intrinsic survival purpose in the biological organism.  If we say that the purpose of flowers is to decorate our living rooms or our gardens, then we are imposing our own purposes on the plants.  If, however, we say that the flowers have the purpose of increasing the likelihood of successful pollination, then we are ascribing a purpose which is a better fit to what the plant appears to be doing.  It is difficult to discuss biology without the use of teleological language, because the appearance of purposeful action is so common.

Summary

I have illustrated how widespread is our use of teleological language.  At the same time, I have suggested we often run into situations where a purely mechanistic explanation is unsatisfactory, often because there are chaotic aspects to the behavior we are describing.

January 8, 2011

On induction

by Neil Rickert

Induction, its use and its problems, is a thread that runs through philosophy (epistemology and, particularly, scientific epistemology).  I am an induction skeptic.  John Wilkins has a recent blog post on the topic: Phylogeny, induction, and the straight rule of homology.  I’ll comment on that post as a way of indicating where and why I disagree.

Phylogenetic classification is a form of induction. It enables us to infer the properties of an as-yet unobserved member of a clade with a very high degree of likelihood, as was pointed out by Gary Nelson in the 1970s.

I disagree already.  But let’s continue reading and looking for other examples of the problem.  A little further down, while discussing the “grue” problem, Wilkins says:

It must be noted that this is not a claim that emeralds will change color. It is about what we can infer of unseen members of a class.

This is implicitly creationist.  It presupposes that God created the classes, and it is up to us to discover what we can about the members of those classes.  The alternative is that classes are human constructs, and are part of our pragmatic enterprise to organize the world for our own use.  In the latter case, the projectible predicates are precisely those that we use to define our organization into classes (our classification scheme).

You might ask “Why should it matter whether the classes are created by God or defined by humans?  Don’t we still have the same problem of identifying projectible predicates for those classes?”

At first glance that might seem to be a reasonable question.  But it does not stand up to analysis.  If the classes are created by God, then they are immutable.  There is nothing that we can do about the classes, except discover projectible predicates for them.  If, however, the classes are pragmatic human constructs, then the classes are not immutable.  We can modify our classification scheme whenever new empirical evidence shows that it would be to our advantage to do so.  Induction, as usually described, is a truth seeking system for immutable classes.  If science is a pragmatic enterprise, then it can change its classification as needed, and that does not require induction.

And yet, biology is not deeply troubled by grue problems, even though it is precisely the science that should be. While the colour of the swan’s plumage turned out not to be projectible, the new black swan was not placed in a new order or class. It was recognised to be a swan nevertheless, and placed into the existing genus, hitherto a monotypic genus. Although philosophers, who anyway tended then as now to rely upon folk taxonomic categories for their examples, were shocked in the manner of Captain Renault, biologists simply shrugged, reported the new species, and added it to the existing taxonomy. The reason is quite obvious by now: the swan was not defined, but classified upon the overall affinities it exhibited, and the fact that one homolog differed in character state from the rest was not crucial, any more than if it had a different shaped beak from the rest of the genus.

And that should be the evidence that science (in this case, biology), does not actually depend on induction.  We see in what Wilkins said there, that biologists are not working with an immutable set of classes.  Rather, they are working with an extensible and refinable classification system, and they adjust that system as needed to accommodate new evidence.

If the universe were such that properties correlated by chance, it would not work, but in the cases of the special/paletiological sciences, properties correlate due to a shared productive cause.  If the universe lacked appreciable structure of this kind, then no search method would deliver knowledge (consider Wolpert’s and Macready’s “No Free Lunch” theorem).

And there we see the implicit creationism again.  There’s an assumption there about an immutable structuring of the universe.  But if the structuring comes from the way that we humans organize the universe, and if we organize it on a pragmatic basis that assures that it will work for us, the problem of “it would not work” simply does not arise.

It should not be thought we are supposing that natural classifications are in any way certain, or that any given homolog will exemplify the same states in each taxon or object classified.

To be clear, I am not objecting at all to the expression “natural classification.”  I am merely saying that we should take that expression as referring to a human designed classification system based on what is observed in nature, rather than as an immutable classification system handed to us by nature.

January 7, 2011

Illinois politics

by Neil Rickert

The local news is abuzz with reports of a deal in Springfield to increase state taxes.  Apparently, the state income tax would go from its current 3% to 5.75%.  Then, after 4 years, it would revert to 3.75%.  See here and here.

Nobody likes tax increases.  However, I applaud this change.  Part of the tax would be used to reduce property taxes and to fund schools.  And part of it will be to catch up with the deficit that has been building over the last several years.  I’m not sure who gets the credit (or blame) for this deal.  And, of course, it has not yet been enacted into law.  But it is good to see some fiscal sanity returning to Springfield.

January 5, 2011

The Model T and the Cadillac

by Neil Rickert

Whenever farmer Brown drove his old model T into town, the manager of the general store would make fun of it, pointing out its deficiencies.  It was noisy; the exhaust was smoky; the seats were uncomfortable; the ride was harsh; its fuel efficiency was poor.  But farmer Brown always shrugged it off.  After all, he needed that model T to get into town.  One day, when farmer Brown arrived in town, the store manager offered him a Cadillac as a replacement for the old model T.  Farmer Brown was not too sure about that.  The Cadillac handled differently, so he would have to learn how to drive all over again.  And it was a lot more complicated, so it would be harder to keep the Cadillac in good mechanical condition.  But, after experimenting with it for a while, farmer Brown recognized that the Cadillac offered him a number of advantages over his model T.  So he set nostalgia aside, and went with the newer car.

In a recent post at the Uncommon Descent blog, Barry Arrington comments that Newton’s theory of gravity has been replaced by Einstein’s general relativity, while Darwin’s theory of evolution continues to be accepted.  I’m not at all sure that’s a correct conclusion, for the modern theory of evolution is significantly different from what Darwin originally proposed.  However, even ignoring that, there’s another important point that is being missed.  Einstein gave us his general relativity as the Cadillac to replace the older Newtonian model T.  By contrast, the critics of evolution are just criticizing Darwin’s model T, but they have failed to provide a Cadillac that could replace it.

January 4, 2011

Community

by Neil Rickert

I’ve been reading “Rich Man, Poor Man” over at the BQO site.  David Sloan Wilson wonders whether communities of the rich are poor in other ways, such as a lack of social cooperation within the community.

I worry that the affluence of modern society is eroding our capacity to cooperate at any scale, small or large. Those of us who can pay with our credit cards don’t need to cooperate, and so we forget how.

It’s an interesting report, and worth reading.  However, I wonder whether Wilson has noticed that our idea of “community” has changed.  For many, the neighborhood is no longer the community.  As a mathematician and computer scientist, I feel more at home in a community of fellow mathematicians and fellow scientists than I do in my neighborhood.  But it’s not just academic communities.  There are sports communities, musical playing communities, and many other communities defined by interests.

I became involved in a music community when my daughter decided she wanted to play the violin, and that was before the time of the Internet.  I suspect that the telephone and the automobile had a lot to do with the forming of these alternative communities.  No doubt the Internet has expanded the possibilities of engagement in alternative communities.  I’m inclined to suspect that there is still plenty of social cooperation within these alternative communities, even if there is less of that cooperative behavior in the neighborhood community.  That might make for an interesting sociological research topic.

January 3, 2011

Purpose (1) – Introduction

by Neil Rickert

In a recent blog post at BioLogos, Dave Ussery wrote:

I do believe that life’s history is infused with purpose and that this process is God’s process.

I agree with the first part of that.  The second part is why scientists often try to avoid talk about “purpose.”  The problem that science sees in the second part, is that it is an attempt to explain purpose that is not evidence based.  And yet people find “purpose” and other intentional words a very useful part of their vocabulary.

This post is intended to be the first of a series where I discuss “purpose” and similar intentional words, and where I attempt to provide a basis for intentional language that is entirely natural and is consistent with the scientist’s requirement of evidence.  If there are aspects of our use of purpose that are inherently mystical or religious, I won’t be attempting to deal with those.

Science usually attempts to give what we might consider to be mechanistic descriptions of what it is studying.  However, in our non-scientific lives, many of our descriptions are based on purpose, rather than on mechanism.  Take this blog, for example.  A mechanical description would be about the physical events that take place to cause a pattern of illuminated pixels on your screen.  That’s fine if we are interested in the physics of digital displays, but it is not satisfying if we are interested in what the blog is about, in what meaning it is attempting to convey.  To convey those meanings and interests, we need an account that uses our intentional vocabulary, our words that talk of purpose, goal, aim, intention, meaning, etc.

The attitude of many scientists with regard to purpose is well illustrated in a recent post to an internet forum:

Purpose is a human construct implying intent, which is another human construct. Science has nothing to say about purpose and intent. Once you’ve started talking about purpose you’ve left the realm of science.

I am sure that expresses a rather common view.  However, if to talk about purpose is to leave the realm of science, then study areas such as Psychology and Cognitive Science will have to be abandoned or at best to be recognized as being outside the realm of science.  I do no see any reason to exclude those fields from science.

There is an alternative to excluding purpose from science.  And that alternative is to find a natural basis for purpose such as will make purpose itself potentially something that science can study.  And that is the direction that I will be taking in this series of posts.

Terminology

We use “purpose” and other intentional words in a number of different ways.  A brief discussion is appropriate.

I might say that the purpose of my automobile is to get me to work and then home again.  However, when I use “purpose” in that way, I am not really talking about the automobile having a purpose.  Rather, I am talking about me having a purpose, and using that automobile as part of how I fulfill that purpose.  So when I use “purpose” in that way, it really means the same as “use”, as in “I have a particular use for my automobile.”  We can discount that particular way of using “purpose” as not being about what we ordinarily understand as purpose.

The other extreme would be to limit the word “purpose” to the case where a person has a conscious purpose.  I want to avoid that particular usage, because it is rather difficult to characterize what we mean by “conscious.”  In between, there are many systems that exhibit what we might describe as “apparently purposeful behavior.”  And that is where I wish to target this series of posts.  That kind of behavior can be seen in many biological organisms, including those such as plants that we would never consider to be conscious.  But it is not restricted to biology.  We can describe a thermostatically controlled system as having apparently purposeful behavior.  Because of its relative simplicity, the thermostat is reasonably well understood, so I shall occasionally use it as an example in the series.  Here, and throughout this series, I shall sometimes use “thermostat” as shorthand for “thermostatically controlled system.”