View source for Exploratory engineering


Exploratory engineering is the exclusively usage of well established knowledge in a fail-safe wasteful way to gain rough but reliable  knowledge about the lower bounds of what is in principle doable. It allows one to probe the timeless fundamental limits of technology.

It does neither necessarily give hints how to get there from the current technological capabilities nor does it necessarily give hints about economic viability along the way. <br> "Easy" predictability of a technology does not imply that it is easily accessible.

'''Exploratory engineering is not a science'''.
''Science is a breadth search for new and highly '''unpredictable''' phenomena''.
One major objective in science is to gain masses of measurement data that can be used to improve and extend new and barely tested models. It requires a tight loop between hypothesis and measurement.
In the book "Radical Abundance" by E.K.Drexler the [//en.wikipedia.org/wiki/Blind_men_and_an_elephant blind men and the elephant] are used for illustration.
Precision and generality are main desiderata in science. Work is usually conducted in independent explorer groups with little common goal.

'''Exploratory engineering is one polar opposite of science'''.
''It is a depth search for highly '''predictable''' working designs''.
At every step one of the best understood and most likely to work choices is taken. Limiting oneself rigorously to well established knowledge (mathematical models) enables one to predict certain things with considerable certainty that are so far from our current capabilities that they can't yet be tried or be measured well. Those things are not useless. They serve as a guiding target and allow preparatory development.
In exploratory engineering one wishes for reliably model-able abstract parametric designs (without specific details) that can give trustworthy knowledge.

Ingredients:
* usage of: conservative engineering methodology
* usage of: established knowledge like: textbook physics - empirical knowledge
* usage of: standard modeling techniques

''' Conventional engineering lies in between science and exploratory engineering'''.
Certainty that a design will work (like required in exploratory engineering) is usually not the prime objective of engineering.
In conventional engineering the designs must always be almost right away physically manufacturable and the fine details need to be worked out.
To be competitive one needs to push the border of what is manufacturable. One needs to minimize cost and or maximize performance.
Thus one often needs to steps into not yet well understood domains and consequently needs to occasionally create and do tests with prototypes.
Tests/experiments are necessary not quite as often as in pure science/research but still regularly needed.
There is an optimal number of tests per "development unit" that lie between the very many for science and the very view for exploratory engineering. 
In contrast to science in conventional engineering coordinated teams that are focused on specifically chosen directions are an absolute necessity to end up with compatible parts that fit together. In the book "Radical Abundance" by E.K.Drexler it is discussed what would happen if "pure-breed scientists" are given the (engineering) task of constructing a car. It turns out you'd end up with a huge plethora of parts but none would fit together. (see: molecular sciences, [[Atomically precise structure|AP building blocks]])

= Comparisons =

== Science vs engineering (in general) ==

=== Basic purpose ===

* '''science:''' provides knowledge – "What knowledge can we discover?"
* '''(conventional) engineering:''' provides products – "What products can we make?"
* '''exploratory engineering:''' provides knowledge – "What capabilities does physical law permit?"
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Exploratory engineering is prone to be confused with (bad) science since instead of products (like engineering) EE provides knowledge (like science).
Knowledge in form of predictions. Predictions that are difficult or not even yet possible to test experimentally. No less. (Reasons why this is ok in EE later). 
Hence the confusion with '''>bad<''' science.

Beside that a confusion of exploratory engineering with science is problematic because EE is much nearer to engineering in most other respects.
For a prime example of some consequences of such a confusion see section "best knowledge" below.

=== Information flow ===

* '''science:''' physical world => model
* '''(conventional) engineering:''' model => physical world
* '''exploratory engineering:''' same as conventional engineering but just showing a target not the path leading there

=== best models ===

* '''science:''' best descriptions (=)
* '''(conventional) engineering:''' reliable bounds (>=)
* '''exploratory engineering:''' very reliable bounds (>>)

Confusing exploratory engineering with a science leads one to assume that it tries to make exact predictions.
And exact predictions are fragile.
But actually one of the core principles of exploratory engineering is to strictly follow a 
'''conservative design methodology''' (meaning '''large safety margins''' - example: a cable holding ten times more than the nominal load) to make predictions. And such predictions are robust.

The robustness from large safety margins is another of the reason why EE in contrast to science is allowed to make predictions that are hard to test or not yet testable without breaking down. At least not immediately.

Exploratory engineering is somewhat like conventional engineering in this regard but not quite. (See section: "larger (design) margins" for details)

=== best results ===

* '''science:''' surprising discoveries
* '''(conventional) engineering:''' predictable behavior
* '''exploratory engineering:''' (highly reliable predictions)

When one confuses exploratory engineering with science one is lead to think that EE tries to predict surprising discoveries.
Which's impossibility should be obvious when stated this way.

But EE does not aim at surprising discoveries near the fragile outermost border of our knowledge.
It aims at highly reliable predictions that are implied by the deepest most solidified core of our knowledge.
Predictions of things where we just don't yet know that we already know them. The "unknown knowns".

While strongly connected in "knowledge space" results of EE are detached (often hugely) in "technology space".
Which is one of the aspects which distinguish EE from conventional engineering.

The focus on the innermost most solidified core of knowledge instead of the outermost most fragile part as the basis for work 
is one of the reasons why EE in contrast to science is allowed to make hard to test or not yet testable predictions without breaking down. At least not immediately. (An other reason for that is conservative design methodology. More on that elsewhere. See section: "best models")

=== best knowledge ===

* '''science:''' exclude all alternatives
* '''(conventional) engineering:''' know many alternatives
* '''exploratory engineering:''' (same as conventional engineering)
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'''Trapdoor warning:''' "Castle in the sky"<br>
When one confuses what is actually an engineering problem with what is actually a scientific problem it can lead one to a premature judge that there are no paths at all (to a goal preliminary identified by EE that is here assumed to be sound) if just one step in one path turns out to be obviously broken.

With an increasing number of starting locations and an increasing focus of them (from starting fronts with a general direction towards more concrete starting points) the problem of reaching a goal set by EE increasingly turns from a scientific one to a engineering one.

In this regard one could classify EE in:
* '''weakly acessible target EE''' ... few known starting locations towards the target predetermined by EE – still much science needed to start
* '''strongly acessible target EE''' ... many known starting locations towards the target predetermined by EE – engineering already possible to start

Drawing a line where a problem switches from a scientific one to an engineering one can be hard. There's a somewhat contradictory regime in-between.
* untargeted science <> targeted science <> untargeted engineering <> targeted engineering
Note: "untargeted" means "few relevant paths known" and "targeted" means "many relevant paths known" <br>
While "targeted science" may sound reasonable its mirror partner is "untargeted engineering" which does not so much.

Even in cases where no relevant paths are visible yet and it's really a pure science problem (not the case in APM!) EE may have some merit. Arguably less though. Some (fundamentally unpredictable) scientific discoveries may (with a big question-mark) unlock a path later. Or the EE might lead in an unexpected direction and identify a goal that may actually already have visible starting points pointing to it.

'''APM:'''
In regards to paths towards advanced forms of APM there are more than plenty of starting points.

Unfortunately there is a bit of a dilemma here:
* People only put effort in looking for and finding some paths if they closely look at and understand the goals character.
* People only put effort in closely looking at and understanding the goals character if they look for and find some paths.

=== organization ===

* '''science:''' independent groups
* '''(conventional) engineering:''' coordinated teams
* '''exploratory engineering:''' independent groups or even individuals

== Conventional engineering vs Exploratory engineering ==

=== basic constraints ===

* '''conventional engineering:''' manufacturing
* '''exploratory engineering:''' valid modeling

* In engineering there always has to be a physical design that you can manufacture.
* In EE there has to be design that can be modeled in a valid way worthy of the name "knowledge".

Since in EE there only has to be a modeled design and no physical product one might be led to not consider EE not as a form of engineering (enginnering in general) but instead consider it a form of science. Despite the fact that EE in most respects is much more near to conventional engineering than science.

=== level of design ===

* '''conventional engineering:''' detailed specification
* '''exploratory engineering:''' parametric model

Concept illustrations can lead one to confuse exploratory engineering with conventional engineering.
This can lead one to critique that specific implementation details are missing. Common remark: "But this is not solved yet".<br>
(Side-note: This refers to lack of details in the far off prediction. Not to lack of details of the path there. The path is a different topic.)

But it is important to notice that the things that are not worked out in concrete detail (atomistic details, concrete geometry of robotics, ...)
are only the things of which it is known that they do not matter much. In other words the things of which it is believed that it should be straightforward to solve them.

In EE going into too much detail would actually be a fallacy.
* Too much details can shrinks design margins and consequently diminishes robustness of predictions.
* Too concrete designs are likely to diverge too much from what actually will be built. 

Very important to note though is that the level of detail is a relative property.
In some areas one can get quite detailed in absolute terms.
Especially when using EE to work backwards to accelerate the process of closing the gap between current technology and proposed target.
----
'''In regards to advanced APM''' a good (if not the best) example of EE that is highly detailed in an absolute sense is the preliminary design and analysis of tool-tips for the [[mechanosynthesis]] of diamond and its polymorphs.

An example that seems to be violating the "avoid too much details" rule would be the preliminary design of [[crystolecule]]s.
Concrete designs of "crystolecules" could be considered too detailed since the chance of one of >exactly< these [[design of crystolecules|crystolecule designs]] to actually be built and used in massive scale is very low. (Except one builds a gargantuan library maybe. But there is no economic motivation for this. Except making it into a game maybe ... solving graphically pleasing puzzles has some recreational value after all).

The reason for why an overly detailed implementation here was not a violation of the "avoid too much details" rule
is that there was the strong need to have at least some prototypical examples representing this general class of objects.
Since instances of the general class of [[crystolecule]]s are per definition built in large scales when advanced APM is reached.

The other way around the "poductive nanosystems" concept video is often criticized for a lack of implementation details in some areas where EE actually has very good reasons not to work them out in too great detail, because it would be fragile and useless guesswork.
Of course there are "white areas" where indeed more detailed EE is possible and likely useful.

Going even farther those "white areas" are sometimes overlooked (e.g. sorting pumps).
Especially if they are not depicted at all in concept visualizations (e.g. microscale [[Vacuum lockout]]).

=== main cost ===

* '''conventional engineering:''' production, operation
* '''exploratory engineering:''' design, analysis

=== design margins ===

* '''conventional engineering:''' enable robust products
* '''exploratory engineering:''' enable robust analyses

=== larger (design) margins ===

* '''conventional engineering:''' raise costs
* '''exploratory engineering:''' lower costs

= Example =

A prime example of successful exploratory engineering in history can be found in the preparations for making low earth orbit and beyond accessible.
For non-involved people without sufficient internal knowledge of the then present technological capabilities it understandably seemed [http://en.wiktionary.org/wiki/lunatic lunatic] to want to go to the [http://en.wiktionary.org/wiki/luna moon]. Turned out they where wrong.

Advanced atomically precise technology ([[Main Page|APM]]) suffers from a similar situation.
Thus one of the goals of [[Main Page|this wiki]] is to provide such sufficient internal information in a way that's somewhat digest-able for the average scientifically interested reader.

= Spacial analogy =

Although we'll not be able to directly test it anytime soon we know with (for all practical purposes) certainty that on a planet far away in a different solar system of our galaxy stones will fall just the same way as they fall here on earth. We can know that with (for all practical purposes) certainty due to our possession of newtons (well tested!) laws.

Just as pretty certain answers can be given for questions regarding sensibly chosen questions about some isolated stuff that resides so far away in space that we cannot jet reach and directly verify it, the same can be done for sensibly chosen questions about isolated stuff that lies in the not so near future.

= Notes =

* It's called exp'''lo'''ratory and not ex'''tra'''p'''ol'''atory engineering which would make sense too - even more so perhaps.

* The book [[Nanosystems]] is a prime example for exploratory engineering.

* good translation to german: "erkundendes Konstruktionswesen"

['''Todo:''' Find out and discuss how this relates to the commonly known scientific method [https://en.wikipedia.org/wiki/Scientific_method (Wikipedia)] ]

= Related =

* [[Science vs engineering]]
* Exploratory engineering can lead to a [[theoretical overhang]] in technology.
* Somewhat complementary: [[The source of new axiomatic wisdom]] {{speculativity warning}}

= External links =

* Wikipedia: [//en.wikipedia.org/wiki/Exploratory_engineering exploratory engineering]
* Wikipedia commons: [https://commons.wikimedia.org/wiki/File:UnknownUnknownsEN1.svg?uselang=de unknown knowns]
[[Category:General]]
* Video (YT channel FHIOxford): [https://www.youtube.com/watch?v=zQHA-UaUAe0 Eric Drexler: Physical Law and the Future of Nanotechnology (2011-11-22)] features some focus on exploratory engineering.