Archive for September, 2010

September 28, 2010

The Folly of Ignorant Thinking

by Neil Rickert

Over at the Big Questions Online site, there is a post that is titled “The Power of Realistic Thinking” with a subtitle “How can we avoid the pitfalls of too much optimism and too much pessimism?”  That post strikes me as highly unrealistic (and hence ignorant).

The central idea of the post is to warn against what it calls utopian visions of the future, and against what it calls dystopian visions of the future.  Here is an example of what it considers a utopian vision:

The future in most popular scenarios  is progressive: we move forward, solve problems and make things better. In these utopian scenarios, humanity is increasingly perfected through technology, freed from the ordinary burdens of life, and able to focus on things wholly outside ourselves. Reason and the rule of law will ultimately prevail, because the fruits of rationality and order — including science and technology — are key to overcoming obstacles that stand between humankind and a more peaceful, prosperous, and free future.

And here is how it illustrates the idea of a dystopian vision:

In the dystopian vision of the future, various apocalypses threaten to destroy humanity. The future is a dark and threatening place in which the progress humankind made in more enlightened eras has led, tragically, to its potential destruction. The solutions to problems of an earlier time often turn out to create even worse difficulties.

Well, that sounds reasonable enough.  So let’s be realistic and avoid the extremes of optimism and the extremes of pessimism.

The problem is with what the author says next.  She writes:

Environmental dystopians, for example, believe the petroleum that created the modern world, and that dramatically improved the lives of billions, is leading to a planet-wide climatic disaster.

No, dummy, those are the realists.  They are not warning of a disastrous future.  They are advising about the kinds of steps that can be taken now so as to avoid a future disaster.

For a real example of dystopian thinking, look to the Armageddon nonsense being predicted by the religious crazies.  And what makes the Armageddon scenarios even worse is that the religious crazies actually believe that to be utopian, and some of the crazies might actually be in a position to try to carry it out with the misuse of nukes.

September 26, 2010

Facts, Truth, Correspondence

by Neil Rickert

In an earlier post, “What’s a fact, anyway?” I wrote about the dependence of facts on conventions.  Today’s post is intended as a followup, and perhaps it will clarify some of the issues.

In what follows, I shall use the acronym WAFA to refer to the earlier post.

A commenter to WAFA suggested as a corollary, that “the whole idea of ‘facts’ can be tossed out as well, since it is dependent on the conventions people set up.”  In this post, I want to explain why that problem does not actually arise.  And that, inevitably, gets us to questions such as “What is truth?”

Facts and brute facts

In his 1995 book The Construction of Social Reality, John Searle distinguishes between what he calls “brute facts” and what he calls “institutional facts.”  Searle mentions the height of a mountain as an example of a brute fact, and facts about money as examples of institutional facts.  That’s a good distinction, and not anything that I am attempting to undermine.

September 21, 2010

ID and Fibonacci

by Neil Rickert

Over at the Uncommon Descent blog, there is a post expressing awe at how the Fibonacci sequence crops up in nature.  And it is not just the post itself that is expressing awe.  We see the same theme echoed in the comments on that post.

The Fibonacci numbers are a sequence where each number is the sum of the two that precede it.  The Wikipedia entry probably has more than most people would ever want to know about them.  They are said to show up in such things as the growth of sunflowers.  The UD blog post suggests that they also crop up in the shape of spiral galaxies.

It is true that they show up in sunflower growth.  But what shows up is only an approximation.  The actual flowers are a bit irregular, so not exactly in conformance with the Fibonacci sequence.  But this is not particularly surprising.  The Fibonacci sequence of numbers is formed by a rather simple rule.  It would not be at all surprising for natural growth processes to grow at a rate dependent on what is already there, and a Fibonacci pattern is a rather simple possibility for this.  It is not even surprising if the sequence shows up in the natural growth of galaxies by gravitational attraction.

The poster and commenters at UD seem to be awestruck by all of this, and they see it as the mark of an intelligent designer.  However, as I just commented above, it is surely only the mark of natural processes.  If they are so easily awestruck, how can they expect to be taken seriously in their claims that there is a scientific basis for their intelligent design thesis?

Footnote: What’s up with the UD site?  On a couple of occasions, I have considered posting a comment.  When I click on the “login” link, a WordPress OpenID login form comes up.  But it looks as if the password would be sent unencrypted to uncommondescent, whereas it should be sent encrypted to wordpress.  Either I am doing it wrong, or they are doing it wrong.  I chose not to continue with the login.  That might be just as well, for it sure looks as if they really only want comments that agree with them.

September 16, 2010

How science works

by Neil Rickert

John Wilkins has asked about how scientists think.  This is intended, in part, as a response, though it also fits into my series on epistemology.

The received view of science is that it is based on analysis of facts.  But that is too simple.  We express our facts in terms of concepts.  An understanding of science has to begin by looking at concepts.  The history of the scientific investigation of electricity and magnetism illustrates this particularly well.  Today we may heavy use of electricity and electronics.  Many of the facts that we use are expressed in terms of voltage (or electromotive force), current, resistance, inductance, capacitance.  None of those concepts were in use at the time intensive investigation of electricity and magnetism began in the 18th century.  The electrical facts that we commonly use today were inexpressible at the start of that historic research program.  Coming up with a suitable conceptualization was an important part of that research.

The received view is that science is mainly concerned with discovering regularities in its data, and that scientific laws are presentations of those discovered regularities.  But that is not at all what I see.  Rather, I see a primary concern as one of finding ways to actually have facts (or symbolic representations).  Many of the scientific laws are abstracted from measuring conventions.  In some sense, the scientists are really solving the intentionality problem, the problem of having representations that are actually about something in the real world.  What is usually considered to be the intentionality problem is sometimes called “The Symbol Grounding Problem”, an expression used by Stevan Harnad in a 1990 paper.  Scientists, being the pragmatists that they are, go about this the other way.  They might be said to be solving the “symbolizing the ground” problem.  Instead of starting with symbols and asking how they can be about something, the scientists start with the something and come up with a systematic way of expressing factual information about that something.

The newly formed concepts that emerge from scientific research allow us to represent facts that could not previously have been expressed.  That is, the new concepts are the basis for a representation system, which we can think of as something like a coordinate system.  As mathematicians are well aware, when you are constructing a coordinate system there is some flexibility in how you do that.  Where possible, scientists use that flexibility to create a coordinate system that is mathematically nice, and this is part of why mathematics is so useful in the sciences.  Physics produces more sui generis concepts than do other sciences, so physics has more flexibility than other sciences in constructing their coordinate systems in a way that allow the use of mathematics.  In the other sciences, many of their new concepts are in some way derived from the more basic concepts of physics, so that those sciences have less flexibility to mathematically structure their systems of concepts.

In the universities, it is traditional that science majors are expected to take laboratory classes.  It is in these lab classes, that they master the intentionality of the scientific concepts.  That is to say, it is in these classes that they learn to connect their technical concepts to reality.

And that’s my heretical view on part of how science works.

September 12, 2010

AI and Intelligent Design

by Neil Rickert

I’m a bit late adding my two cents to the blog debate between PZ Myers and Ray Kurzweil.  If you want to review the debate, then a good place to start would be with PZ’s August 21 post on “Kurzweil still doesn’t understand the brain“, and follow some of the links from that report.

I was reminded of the debate by a recent John Wilkins post.  And when I reread Kurzweil’s response to the first PZ post, I noticed how well that raises some of the design versus evolution themes that I have been raising in this blog.  This post will comment on some of what Kurzweil has posted.

For starters, I said that we would be able to reverse-engineer the brain sufficiently to understand its basic principles of operation within two decades, not one decade, as Myers reports.

I’ll go on record as doubting that the brain will be reverse engineered within 100 years.

I presented a number of arguments as to why the design of the brain is not as complex as some theorists have advocated.

There we see a key point.  Kurzweil is talking about the design of the brain.  He is looking at the brain as a designed thing rather than as an evolved thing.  We generally see “reverse engineering” as a way of retrieving the underlying design from an designed thing.  However, the brain is not a designed thing, it is an evolved thing.  And evolved things are very different from designed things.  If the brain is not a designed thing, then there is no underlying design to retrieve, and thus the planned reverse engineering is bound to fail.  Or, to put it differently, the brain was not engineered in the first place, so there is no engineering step that could be reversed.

A little later, Kurzweil says:

To summarize, my discussion of the genome was one of several arguments for the information content of the brain prior to learning and adaptation, not a proposed method for reverse-engineering.

And there is another illustration of the problem.  For the developing embryo interacts with its environment from the start, even before the brain begins to form.  Adaptation of the developing foetus is well underway before there is a brain.  So talk of “content of the brain prior to learning and adaptation” is seriously confused.

As best I can tell, Kurzweil seems to be thinking of the brain as a fixed designed thing that is engineered from a detailed blueprint in the genome.  And he takes this fixed designed thing to be an information processing system.  He sees adaptation as an information processing detail.

By way contrast, I see adaptation as distinctively biological.  If I look at a tree in my back yard, I see how it adaptively grows, and thus modifies its own shape, so as to better gain access to the available light.  And if I were to look at the roots, I expect that I would find the same kind of adaptive growth to better find nutrients in the soil.  This cannot be a matter of information processing in the brain, for the tree has no brain, no neurons.

The goal of reverse-engineering the brain is the same as for any other biological or nonbiological system – to understand its principles of operation.

Fair enough.  But Kurzweil assumes that those “principles of operation” are information processing principles.  It is far more likely that they are biological principles, not information technology principles, and that those biological principles are already being intensively studied within biology.  In terms of biological principles, my brain probably works in much the same way as Kurzweil’s brain.  In terms of information processing principles, the chances are that any two brains are very different.

September 4, 2010

Consciousness and evolution

by Neil Rickert

From time to time the question of consciousness comes up in the creationism, ID (intelligent design), evolution debates.  The proponent of creationism or ID raises the issue of consciousness as something that is not explained by science, and uses that to argue that consciousness could only arise from the actions of a divine intelligent designer.  For a recent example of this kind of argument, see Granville Sewell’s post on Human Consciousness in the “Uncommon Descent” blog.

It is really a typical “God of the gaps” argument.  It is a mystery to me that theists continue to make such arguments.  By now it should be obvious that if they are going to define their god based on the gaps in human  knowledge, then sooner or later that god will be exposed as a charlatan.

In this post, I shall argue that consciousness actually poses a far greater problem for the theist than it does for the evolutionist.  The attempts to explain consciousness have all been attempts to understand how we would go about designing a conscious agent.  That such attempts have not succeeded would seem to pose a problem for the idea of design.

Here is how Sewell finishes his argument:

And if you don’t believe that intelligent engineers could ever cause machines to attain consciousness, how can you believe that random mutations could accomplish this?

Sewell’s argument appears to be that since we have failed in our attempts to understand how to design consciousness, therefore consciousness must be designed.  Perhaps he did not notice the incongruity of such an argument.  An alternative conclusion, and I think a more plausible one, might be that consciousness is only possible in an evolved system, and could not be present in a designed system.

There are three problems that seem to arise in attempts to understand consciousness.

  1. How can a designed system have free will?  It always seems that a designed system (a robot, for example) will be carrying out the intentions or purposes of its designer, and therefore cannot be said to be able to act of its own free will.
  2. How can a designed system be said to appreciate that the data it collects from the world is about something (i.e. is about part of the world)?  This is the intentionality problem that John Searle raised in his famous “Chinese Room” argument.  It is easy enough to see how the robot can collect data that is meaningful to its designer, but it is not clear how that data can be meaningful to the designed system (or robot) itself.
  3. How can the designed agent actually experience the world?  This is approximately the qualia question.  Roughly speaking, and using “through the eyes” metaphorically, it is the question of how the robot can see the world through its own eyes, instead of it merely behaving in accordance with the way the world is seen through the designer’s eyes.

The clear solution to these problems would be to have an agent that, in some sense, designs itself.  Then to say that the agent acts in accordance with the will of its designer is to say that it acts on its own free will.  To say that the data collected is meaningful to the agent’s designer is to say that the data is meaningful to the agent itself.  To say that the agent behaves in accordance to how the world is seen through the designer’s eyes is to say that the agent behaves in accordance with how the world is seen through its own eyes.

With an evolved creature, we cannot quite literally say that it designed itself.  But the evolved creature does come as close to that as we could hope.  Up until the time of conception, the creature can be said to be designed by its parents as part of an inter-breeding group.  The biological development that follows conception can reasonably be considered self-design.

My personal conclusion: consciousness is only possible in evolved systems.  If God had wanted the world to have conscious creatures, he would have created a system of evolution as a way to produce such creatures.

September 4, 2010

On similarity and partitioning

by Neil Rickert

John Wilkins has an interesting post on similarity.  Since this is closely related to my ideas about evolutionary epistemology, I am adding my two cents.

A great deal of philosophical explanation is based on similarity.  For example, it is often said we apply names such as “cat” and “dog” based on the similarity to some sort of archetype that we are said to have in our heads.  However, it is never explained how similarity works, nor how that archetype gets into our heads in the first place.

My own view is that philosophy has much of this almost exactly backwards.  The view of philosophers is that organize the world by grouping or categorizing similar things together.  My apparently heretical alternative view is that we organize the world according to whatever ways we can find that work to organize the world, and that prove useful to us.  Of particular importance is that our ways of organizing the world must be reliable and repeatable and useful (pragmatic).  That is to say, we organize the world in a way so that if we went back and did it again in the same way, we would come up with the same result, and we do it in order to make it easier for us to negotiate our way around our world.

Once we have a reliable way of organizing the world, then we can call things “similar” to the extent that our method of organization groups those things into common categories.

Allow me to redescribe this in terms of what I call “partitioning”.

What is immediately available to us, or immediately available to a newborn infant, is a world, but perhaps a world with no known structure.  In order to better apprehend the world, we try to find reliable ways of dividing that world up into parts.  For example, the newborn infant eventually learns how to partition the world into daytime and nighttime, and that ability is welcomed by parents when it finally allows them to get a good night’s sleep.  Once we have partitioned, we can then further subdivide or partition those partitions into finder sub-partitions.  The result is a scheme of nested partitioning.  Then, the further down this hierarchy that two things are found in the same partition at that level, the more similar they will seem to us.

The overall point.  Our idea of similarity is a consequence of how we organize the world, rather than the underlying principle that we use to carry out that organizing.

September 2, 2010

What’s a fact, anyway?

by Neil Rickert

It is common for discussions of knowledge and science to emphasize the role of evidence, where “evidence” usually refers to facts.  Typically, facts are said to be the starting point.  But what, exactly, is a fact?  That’s what I want to examine here.

Let’s start with a standard fact, and use that as an illustration.  The city of Paris, France, is at latitude of 2.33 E.  It is convenient to use decimal notation, though the latitude is often listed as 2 degrees 20 minutes East.  Similarly, in decimal notation, the longitude of Paris is 48.8 North.  As a reference, I used an Infoplease web page.

In order to be able to express this fact, we first need the system of latitude and longitude as a way of specifying locations.  It should be obvious that the latitude and longitude system is itself a human construct, defined in effect by a system of human conventions.  The idea of using latitude and longitude was apparently first proposed by Eratosthenes in the 3rd century BC.  However its common use is more recent, due to the difficulties involved in determining longitude.

Mathematically speaking, latitude and longitude provide a system of spherical coordinates.  Such a coordinate system is standardized by specifying an axis and a fixed point not on the axis.  The latitude is then based on angular distance from the axis.  The longitude is based on the angular amount of rotation from the fixed point around the axis.  The choice of both the axis and the fixed point are arbitrary.  In practice, we use the North pole/ South pole line as the axis.  This is the most sensible pragmatic choice, as it connects the geographic coordinates with the rotation of the earth.  There isn’t any important reason to prefer one fixed point over another, but for historic reasons the Greenwich observatory is used as that fixed point.

Once we have established the latitude/ longitude system as a coordinate system, we can begin to express locations as facts within that system.  The definition of the coordinate system is itself a matter of convention.  So if we want to consider that definition to be factual, then we should consider it to consist of conventional facts (as contrasted with empirical facts).  Likewise, that the equator is at latitude zero is a conventional fact, for that latitude comes directly from the conventions.  Similarly, that Greenwich is at longitude 0, is a conventional fact.  However, once the conventions are established, then the location of Paris at 2.33E, 48.8N is then an empirical fact.  It is, however, an empirical fact that is subordinate to the conventional facts that define the coordinate system.

If we examine the physical sciences, we will find a widespread use of conventions.  These can include measuring conventions, simple naming conventions, or classification conventions such as those used by Linneaus in his systematization of biological naming.  It is likely that all scientific facts are either conventional facts or empirical facts that are subordinate to the conventions that they depend on.

When we come to ordinary non-technical language use, it becomes more difficult to track down conventions.  Where there are conventions, these are often informal conventions that develop and evolve in the cultural world of interpersonal communications.  However, it seems likely that all facts are either conventional or subordinate to conventions, where in some cases those conventions will be the informal agreements that determine the rules of the language game being followed in the natural language that is used.

Traditional epistemology and philosophy of science tend to emphasize starting with facts.  My point, in this post, was to show that they should start before there are facts.  They need to start with the establishing of conventions, upon which the facts are dependent.

This should suggest that acquiring knowledge is not so much a matter of acquiring facts, as it is a matter of acquiring the conventions which we follow in order to form facts as needed and in order to understand and use facts that are presented to us.

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