Does your dualism lose its flavor on the bedpost overnight?
Unblock your inquiry with a dose of Peirce’s Elixir Triadic❢
☞ Inquiry Driven Systems • Are There Apps For That?
Frequently encountered complementarities, dualities, or design trade-offs
- Integrating data-driven (empiricist) and concept-driven (rationalist) modes of inquiry.
- Integrating model-theoretic and proof-theoretic methods for evaluating theories.
- Bridging the gap between qualitative and quantitative research methodologies.
- Relationship between emergent-evolved systems and engineered systems.
- Relationship between descriptive sciences and normative sciences.
Relationship between emergent-evolved systems and engineered systems
I am taking a systems-theoretic view of the inquiry process, but I am focused on the kinds of systems we engineer to a specific purpose, for example, computational support for scientific inference. With that aim in mind the kinds of understanding we gain from connectionist, emergent property, genetic algorithm, or self-organizing systems research typically falls short of telling us how scientific inquiry can manage to work in the frame of time that human beings have at their command.
When we set about engineering artificial systems to augment our natural capacities — the way we build microscopes and telescopes to extend the reach of our eyes — our success in doing that naturally depends on how well we understand the natural system we are trying to extend.
One form of understanding is achieved when we draw on principles embodied in a natural system that are general enough to be embodied in very different artificial systems. That is the method of analogical extension, and it turns on the recognition of an abstract principle that can be shared by otherwise diverse systems.
Inquiry Into Inquiry 
“Relationship between emergent-evolved systems and engineered systems.”
That goes a long way towards addressing what I referred to earlier as the “natural history” of cognition, inquiry, logic, mathematics, language, etc. We might learn things from the natural, sequential development of such faculties and systems that could be either prescriptive or proscriptive for modern engineering practice.
I like looking for the earliest and simplest instances of things. Unfortunately the early natural history of most things is largely unknown. Take the evolution of the triangle or the number three in human cognition, for example. But even in the absence of historical data we might gain something from thought experiments or inferences about what the evolutionary sequence might have been in the light of things we do know about the human bio-computer.
I call that question —
Ah, so.
Incidentally, thinking about threes and triangles, the basic transistor (perhaps a fairly close man-made analogue of a primitive neuron or a even a bit of DNA) that we now “print” with exotic nano-particle ink is a thing with a tripartite configuration. I guess such three-part structure actually applies to most switches, many instances of which greatly predate biology.
When I was a kid I learned about diodes and triodes and the difference it made when De Forest inserted a third element, a grid, between the anode and cathode of a vacuum tube. And the rest is hysteresis …
BTW, as context for engineering apps, the human brain dissipates about 10-20 Watts.
What watts would the pate of Watts dissipate
If the pate of Watts should dissipate watts?
Watts in a name? Meter the one you’re with …
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