[p2p-research] Building Alliances (basic income and entrepreneurship)
Paul D. Fernhout
pdfernhout at kurtz-fernhout.com
Sat Nov 7 17:29:20 CET 2009
J. Andrew Rogers wrote:
> There are two basic mechanisms for "knowing".
> There is mathematics, which is axiomatic and deductive. There is
> science, which is non-axiomatic and inductive, with the caveat that
> the correctness of this model is predicated entirely on the axioms of
> What am I missing? Divine revelation? Astrology?
Or, in fact, all these sorts of modalities listed here, or more:
# 1 Gardner's categories of intelligence
* 1.1 Bodily-kinesthetic
* 1.2 Interpersonal
* 1.3 Verbal-linguistic
* 1.4 Logical-mathematical
* 1.5 Intrapersonal
* 1.6 Visual-spatial
* 1.7 Musical
* 1.8 Naturalistic
# 2 Other intelligences
spiritual, existential and moral intelligence.
All are, to some extent, fundamentally different ways of "knowing".
All reasoning depends on assumptions, and all reasoning is done in service
of values and emotions, and involves a decision about what are acceptable
reasoning tools. None of those choices about assumptions, values, and tools
can be made logically. At best, we can iterate on these things as part of a
process where logic plays a part. So, there is a lot more uncertainty that
scientism tries to paint. For example, are we living in a simulation? What
would that mean? Where do we come from? What happens after we die? How
should that effect our choices now? Our assumptions about a lot of these
things can have some big effects on our behaviors.
"Descartes' Error: Emotion, Reason, and the Human Brain is a book by
neurologist Antonio R. Damasio, in which the author presents the argument
that emotion and reason are not separate but, in fact, are quite dependent
upon one another."
Another way to understand this might be to look at some of Marvin Minsky's
and other's work on multiple representations and artificial intelligence. I
was at a talk Minsky gave around 1999 where he outlined the idea that the
human brain simultaneously kept running several different models of the
world (semantic, 3D, 2D, and so on, don't remember for sure which ones he
discussed) and kept choosing solutions from one of the model as they were
most appropriate. So, there he was talking about building AIs with multiple
ways of knowing, all going on simultaneously. :-) Mathematical and abstract
enough for you? :-)
A first quick reference, showing his thinking on that goes way back:
"A Framework for Representing Knowledge; Marvin Minsky; MIT-AI Laboratory
Memo 306, June, 1974."
The different frames of a system resemble the multiple "models" described in
Guzman (1967) and Winston (1970). Different frames correspond to different
views, and the names of pointers between frames correspond to the motions or
actions that change the viewpoint. Later I discuss whether these views
should be considered as two- or as three-dimensional. ...
If asked about important future lines of research on Artificial or
Natural Intelligence, I would point to the interactions between these ideas
and the problems of using multiple representations to deal with the same
situation from several viewpoints. To carry out such a study, we need better
ideas about interactions among the transformed relationships. Here the
frame-system idea by itself begins to show limitations. Fitting together new
representations from parts of old ones is clearly a complex process itself,
and one that could be solved within the framework of our theory (if at all)
only by an intricate bootstrapping. This, too, is surely a special skill
with its own techniques. I consider it a crucial component of a theory of
>> Last, social change must not be proven in theory, but experimented in
>> practice. Lots of things were impossible in theory, like the Wikipedia and
>> the Arduino, but happened in practice. In that case, theory must be revised,
>> but above all, one must be aware of the relativity of theory at all times.
> Huh? Neither Wikipedia or Arduino are impossible in theory. It is
> silly to assert as much. Indeed, they are *expected* in theory.
Only after the fact. Biofilms are theoretically not possible either,
according to this:
Science usually gets patched up after the fact. No one believed amorphous
semiconductors were possible either, and Stanford Ovshinsky was laughed at
for years in academaia for proposing that.
"Amorphous and Disordered Materials?The Basis of New Industries"
"As in the past, materials will shape the new century. Dramatic changes are
taking place in the fields of energy and information based on new synthetic
materials. In energy, the generation of electricity by amorphous silicon
alloy thin film photovoltaics; the storage of electricity in nickel metal
hydride batteries which are the batteries of choice for electric and hybrid
vehicles. In the information field, phase change memories based on a
reversible amorphous to crystalline transformation are widely used as
optical memories and are the choice for the new rewritable CDs and DVDs. The
scientific and technological bases for these three fields that have become
the enabling technologies are amorphous and disordered materials. We will
discuss how disordered, multielemental, multiphase materials can throw new
light upon metallic conductivity in both bulk and thin film materials. We
will demonstrate new types of amorphous devices that have the ability to
learn and adapt, making possible new concepts for computers."
Could the same be true for how you say other things, whether disordered
amorphous p2p volunteerism, or distributed search, are not theoretically
possible, or are certain to fail? :-)
Ultimately, it is experiment that we need (in reality, though, or simulation).
"Hence, demonizing centralization and glorifying decentralization as the
solution to all our problems would be wrong. An open and experimental
attitude towards the question of different hybrids and mixtures is what the
complexity of reality itself seems to call for. "
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