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February 24, 1991
FREEWILL.ASC
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This file courteousy of Double Helix BBS at 212 865 7043.
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We all seem to have the belief that we live in a world ruled by
knowledge of what is right, and that mankind, as a whole, is
advancing because of this. In other words, greater knowledge and
understanding is accumulating daily in all the disciplines of study;
we discover first the laws of physics, then we invent the airplane,
now we gain deeper insights into ourselves and the world through the
arts and humanities.
Our civilization, now more than ever before, places a premium
on the excavation of knowledge and the means by which that knowledge
is excavated. What this all seems to imply is that this should
propel our civilization onward to a better way of living, of
governing ourselves and running our society. The more we know, and
the more we apply our ways of knowing, the more advanced we should
become. Nothing could be farther from the truth.
The reason for this is we haven't developed a criteria for
deciding, in an objective fashion, what is *right*. The argument I
propose is that for any given situation, a set of rules can be
adopted which will determine the *proper* course of action to be
taken. If these rules, having been determined to be the best course
of action, are followed, then we can advance, if decisions are not
based on such rules, then the wrong course of action is taken, and
we fail to advance.
The difficulty then, is in determining the proper set of rules
or criteria by which to act, while abandoning the improper ones.
Such rules will undoubtably differ depending upon the situation for
which they are formulated, but commonalities should run through all.
Civilization, as it exists today, abounds with these rules; they
tell us that nature acts in particular ways, which are seldom
violated, and that we and the systems of government which rule us
must act in particular ways, or else risk punishment or change.
However, these laws are not used to guide us, either as
individuals, or as a society, in making decisions and determining
plans of action.
What is used instead is the simple judgement of the individual,
or the mass judgement of many individuals in the form of a vote. It
is through these two means that our future as a civilization is
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determined. The problem is that we place greater faith in free will
and personal judgement when the decision is to be made by the
individual, and on the democratic process when the decision is to be
made by a group, than on the rules.
Let us start at the level of the individual. Everyday, each of
us faces numerous decisions, some of which are of little
consequence, others which will change the course of our lives
depending on their outcome.
How are these decisions made? Well, it appears that we think
of all the possible actions which we could take, and then evaluate
what the outcomes of these actions are. The outcomes are then
evaluated in terms of those which are most beneficial to the
organism.
One plan may save time, another money, another effort. The
organism concludes, for example, that it would rather stick with one
of the possible plans over another because it considers its outcome
the most beneficial.
In order to illustrate this, an example is needed. Let us
suppose that after breakfast, you consider what you plan on doing
for the day. You know that you must study, go grocery shopping, and
visit the bank, but are expecting an important call sometime late in
the morning. What should you do?
A set of rules can be followed in such cases to make the
correct decision, if all the possibilities are specified, and the
outcomes, in terms of their beneficence to the organism are known.
If we abbreviate studying S, groceries G, and bank, B, then the
possibilities are as follows:
Figure 1.
possibility criteria satisfied beneficiality
(1-best, 4-worst)
1) SGB CE, not T............. 2
2) SBG CTE................... 1
3) GBS TE not C.............. 2
4) GSB neither CTE........... 4
5) BSG T not C or E.......... 3
6) BGS TE not C.............. 2
We next impose an order of beneficiality on the possibilities, by
forming constraints.
The first constraint we have already mentioned, and is the
telephone call.
The second is that going to the bank cannot be performed
last, because it closes early.
The third is that it is a waste of both effort and gas to
leave the house, come back, and leave again.
If these are the only constraints and possibilites, making the
correct decision becomes possible. We see that choice 2 is the best,
because you stay in to receive the call, get to the bank on time,
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and waste neither gas nor effort in leaving and returning only once.
Choices 1, 3 and 6 are second best, because in each you satisfy
two of the constraints, but not the third, time being sacrificed in
1, and the call in 3 and 6.
Choice 5 is third best, because only the time constraint is
satified. 4 is our worst choice; none of our constraints are
satisfied.
If we abbreviate our 3 constraints as C for making the call, T
for having the time to get to the bank, and E for the effort, either
of car or person, then which of these possibilities satisfy which of
these constraints may be illustrated in the second column of figure
1.
Most people, in making such a decision would have decided which
they thought constitued the most important of the criteria, and
would have simply studied first, in giving the phone call priority,
or gone to the bank first and came back if giving this ultimate
priority.
The point of this example is that all the criteria can be
satisfied and the best decision made if the possibilities and the
criteria are known. In other words, the more we know about these
important qualities of the decision, the better the decision we are
able to make. Obviously, as decisions become more complex, so do the
means of solving them efficiently. But this is just the point.
Most people, in performing even the simplest of decisions, fail
to follow any such ideal process or rule, either giving one criteria
ultimate importance, or not using any criteria at all, as when
emotion or instinct form the basis for a decision.
The way in which theories are formed in science also fail to
show any sort of systematicity, or rule-governed behavior. This is
especially intriguing, because it is the job of the sciences to
describe nature according to these very principles.
Scientific theories have traditionally been either accepted or
rejected on the basis of inductionism and falsificationism.
Inductionism is the process of reasoning from particular empirical
results to more abstract, generalized ones. Falsificationism is the
process of rejecting theories by proving them wrong, also only on
the basis of empirical evidence.
Pursuing science in accordance with inductivism is profoundly
damaging in that it leads to the acquisition of vast amounts of
observational and experimental data devoid of any theoretical
interest or importance, while falsificationism, because it only
allows empirical evidence as grounds for falsifying a theory,
excludes all non-empirical means, such as philosophical,
metaphysical and methodological considerations from science.
(see Maxwell, 1976 and 1984, for a complete criticism of
these methodologies and of the way in which science is
conducted, also see Kuhn, 19?? for a good discussion of
scientific progress)
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Other problems exist in the sciences. One is that in trying to
explain their field of study, scientists often fail to address large
issues. After tackling a smaller problem in the field which they
hope will shed light on the larger issues, they often become
absorbed by these smaller issues, failing to relate them to the
general issues of the field as a whole. This results in a
fragmentation, in which scientists end up formulating models for
particular phenomenon, without regard to the functioning of these
phenomenon in relation to the larger systems of which they are a
part, and the other systems with which they must interact.
Even worse, scientists have, in the past, decided the course
with which science progresses through personal choice and
popularity. A new theory, even a good one, is always slow in being
accepted by the scientific community.
Frequently, older theories will continue to be relied on, even
though newer, competing ones can better explain the data. A case in
point is the development of Einsteinian physics during the early
part of the 20th century.
Einstein's theories were scoffed at initially, because they
were so different, but were eventually accepted because they were
better able to explain the physical phenomenon. One wonders what
would have occurred had the opinion of the scientific community been
less in his favor. Thus we see that a true theory may die, because
the scientific community as a whole, votes to support a different
one.
This method of 'voting', where the majority of people favoring
one issue decide the outcome in favor of that issue, constitutes the
second means by which decisions are usually made. Individual
scientists, in making their own decisions as to which theory they
favor, may decide its future. Those with the greatest reputations
play a greater stake in this, but the overall number in each of the
opposing camps is just as important.
We have already seen that individuals are usually incapable of
making correct decisions, because they fail to take into account all
of the information, as well as the pros and cons of each piece of
information, in order to perform the appropriate evaluations and
conclusions. Are we to let science be run by the whims and decisions
of a few people?
If one person is unlikely to make a correct decision, then
increasing the number of people having to make the decision does
nothing to increase the likelihood that the correct decision will be
made, because more people will make correct decisions, but the
number of people making incorrect decisions also increases, with the
net result no more appoximating the truth.
In fact, the situation is made even worse when a number of
people together vote on an issue by taking sides, because many
individuals become swayed by the opinions of others.
This process of voting to make decisions is hardly limited to
the realm of science. We see it everywhere. In the legal system, a
person is proven innocent or guilty by a jury of 12 men and women,
where the sum of their decisions determine the verdict.
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In government elections, the sum of the decisions by the people
determine who will run the country. In all these cases, decisions
are made subjectively, through the pooled opinions and decisions of
the many.
Clearly, something should be done about how decisions are made,
such that mankind may benefit and progress. If we have learned
anything at all in this information age, it should be how to use the
vast amounts of information and problem-solving skills we have
acquired, and apply them to these decision making processes. It is
the decisions which we, as people, make which determine our lives
and whether or not we ultimately progress as a civilization.
Therefore, what I propose is that we develop methods of
decision making which will permit us to overcome these inadequacies.
To begin, personal decision-making could benefit from early
instruction. Different methods of problem-solving could be taught to
children and then practiced on in-class examples. In this way, more
objective and logical evaluation skills could be learned and
engrained early on, so that as adults, such thinking would come more
easily.
Such training might emphasize the ways in which emotions might
interfere with, or cloud our decisions, and ways in which to be
aware of, and prevent such interference. Too often, the curricula
in our schools emphasize the memorization of facts over the training
of analytic and critical thinking.
Also, there have been proposed new methodological means for how
science should go about its business. Dobson and Rose (1984)
elaborate on a model which eliminates many of the previously
mentioned problems of scientific advancement. Their proposal
consists of the following stages:
1) Define the problem or phenomenon to be studied. If we are
interested in studying the visual cortex, then a complete
definition of what the visual cortex is and does, as well as
its relations with other brain areas, needs to be accounted
for. This all-inclusive definition must be agreed to by all
those studying it.
2) Formulate an exhaustive range of functional theories to
explain the phenomenon in question. Since all possible
models should be built and tested, we need a way to prevent
the numbers of these models from becoming infinitely large.
3) Discriminate among models starting first at the highest, or
most abstract, level of explanation, and then work downwards
on more specific models. For example, one theory might
explain very well how we perceive a number of visual
illusions, but less well the more general phenomenon of the
visual cortex, such as pattern recognition, locomotion, etc.
4) After finding out which low-level specialized models are
successful and which are not, the merits of higher-level
solutions can be assessed and appraised. In this way, the
success of more specific models can serve as feedback to
determine which of the higher level models are best. This
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stage alone can eliminate the tendency for scientists to
become focused on smaller issues.
Through this process, we will eventually come to one or a few
models which will best describe the phenomenon in question. Theories
at any level in this process can be evaluated against each other
according to a number of criteria:
1) Efficiency - again, sticking with the example of the visual
cortex, the most efficient model would be one which would
require a minimum amount of information processing,
biochemical energy required to work it, and amount of gene
space demanded to reproduce it.
2) Reliability - how well does the model function in the face
of adverse, or difficult conditions? Here, we could build a
connectionist model, introduce random informational 'noise'
into the inputs or circuitry and then measure the extent to
which the model's ability to perform its overall function
deteriorates.
3) Simplicity - models should be no more complicated than
neccesary. A model with fewer parameters should be favored
over one with more.
4) Developmental coherence - can the system develop from
previous stages? This is especially important when the
theory is driven from an evolutionary or developmental
standpoint.
5) Working coherence - do the subsystems which compromise the
system work cooperatively, or 'pull in different
directions'?
6) Logical coherence - does the sytem function in the same
metaphysical state as other models of related systems? For
example, does this model of visual processing work according
to the same fundamental principles as the similiar model
which specifies auditory processing?
7) Completeness - how much of the phenomenon in question does
the model cover? It can explain orientation selectivity,
sure, but can it explain spatial frequency selectivity,
aftereffects, etc.
8) Empirical evidence - does the evidence obtained from
experimental work support the theory?
Thus we see that there do exist models for systematically
determining choices. Of course even these models in no sense permit
us to come up with the *right* choice, but they do enable us to more
closely approximate the truth, and in reaching a decision which is
certainly more *correct* than those obtained through individual
choice or votes.
The idea here is that we can come up with working models, which
can themselves later be modified after we have learned more about
them through use. These models may differ, depending upon their
application.
Page 6
For example, the methods for making personal decisions,
deciding among scientific theories, determining guilt or innocence,
electing government officials, running the government itself etc.,
will all differ, although they should contain some common elements.
We have already seen that the following principles will play an
important role:
1) Define the problem - if all that is needed is the
performance of 3 tasks, as in the personal decision problem
given at the outset of this paper, then the tasks themselves
define the problem. In trying to discover how the visual
cortex functions, though, defining the problem space is much
more difficult.
2) Enumerate all the possibilites or theories - again, in
working within a limited domain, as when given 3 tasks, the
number of possibilites is mathematically specified, but when
dealing with more complex issues, this number may become
infinite. Even one theory may be split up into an almost
infinite variety, if subtle changes are introduced.
3) Establish criteria by which to distinguish among the
possibilities or theories - this is a tricky issue, because
in some instances, or depending upon your theoretical
viewpoint, some criteria become more important than others.
4) Discriminate among the possibilities or theories using the
criteria to arrive at the single best or several best - if
we arrive at a tie, then how do we decide what is ultimately
the best?
Clearly, then, what I suggest for the future is the adoption of
these 'decision-methods'. An important task for the future is to
discover such methods, elaborate upon them, improve them, and adapt
them for use in particular domains. We put too much faith in free-
will, and in our ability to make choices, using only our innate
abilities, and only further complicate this problem by
institutionalizing free-will in the process of a democratic vote.
What is needed is an objective system of decision-making free
from subjective biases. This is the take home lesson that we should
be receiving from this age of information and technology and method,
but is one which we blatantly ignore.
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Vangard Notes...
This paper is highly reminescent of the political system
devised in the 40's and which was known as the TECHNOCRAT
party.
The TECHNOCRATIC movement believed that ALL government should
be run by Scientists and Engineers. This would ensure that all
operations of Supply and Demand would be optimized to achieve
their most efficient mode through the use of mathematics,
cycles, statistics and all aspects of the sciences.
It was a most admirable system not only because it sought the
greatest good without the acquisition of power or the inflation
Page 7
of ego, but even included members of the ministerial ranks to
assist in decisions relating to moral issues.
We have a very rare book about the movement which will someday
result in a file detailing some of their proposed methods.
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REFERENCES:
Dobson & Rose. (19??). Models of the Visual Cortex.
Kuhn. (19??). The Structure of Scientific revolutions.
Maxwell, N. (1976). What's Wrong with Science? Bran's Head Books,
Middlesex.
Maxwell, N. (1984). From Knowledge to Wisdom: A Revolution in the
Aims and Methods of Science, Blackwell, Oxford.
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as this paper covers, please upload to KeelyNet or send to the
Vangard Sciences address as listed on the first page.
Thank you for your consideration, interest and support.
Jerry W. Decker.........Ron Barker...........Chuck Henderson
Vangard Sciences/KeelyNet
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