TGN is equipment for looking

a twinkle in the eye as we behold a cartoon

If you’re connected with ‘tech people’ in AEC on LinkedIn, you can’t turn around in place without bumping into another repeat of 20 year old rhetoric about ‘BIM’ and even the same tired complaints about “old fashioned people who keep doing things the old ways because they work… instead of doing the new” (not new anymore) thing, whatever it is. 

But what about the presence of so many people, more and more all the time, who’ve gone through all of this, all in, high skill, high collaboration, for decades already, and having done it for so long now, find themselves gone full circle, saying: 

“wait a minute, everything that matters has only decayed and…why is that?”

The decay of comprehension. The decay of thinking things through. The decay of clear thought clearly conveyed. The decay of digital modeling over the last 20 years. The decay of attentive focus and visual close study. The decay of the engine of thought. The decay of the means of keeping it running. The decay of knowing the difference. The downward spiral.

“hit the proverbial nail on the head, BIM has decayed critical thinking in a lot of scenarios. I just don’t think we have quite gotten where we were aiming for. I see a lot of it is due to aiming at efficiencies rather than focusing on critical information transfer at set points in time, something a lot of people are only just realizing at least locally”

That’s negative statement with strength. But the damage done calls for words stronger still.

Digital modeling undermines the engine of thought itself

We see that over the last 20 years. 

Early on, unnoticed, the engine of thought gets de-tuned and starts losing power. Year after year, less and less power. The process is far enough advanced now that we can anticipate that the current state approaches engine shut down. It’s in sight anyway.

That’s where we’ve arrived after these decades: the impending shut down of thought itself.

That’s far removed, isn’t it, from the target we had in sight 20 years ago when we started down this path (30+ years for some). 

Shut down

We can see that, coming at us now. And the reason is clear. 

We’ve undermined our form of engagement with models. The very form of engagement that drives the engine of thought itself, that drives mental model formation and its development toward adequacy.

Digital modeling as we know it, the current paradigm, undermines that at the root. It hacks at the roots of cognition itself. This is no secondary effect. And it has nothing to do with minor causes, for example, that “users need more training or an attitude adjustment.”

Even while the decay is recognized, and denied by no one, the critical situation remains hidden by wishful thinking, by the effects of techno-evangelism, by retreat into dogma, and by belief, even, in measuring AEC industry health in terms of software company stock values. 

But decay is also hidden by confusion, and in general, by various forms of burying our heads in the sand, and scapegoating. 

But more generally, decay is hidden by exhaustion.

Exhaustion sets us up as marks, again, for bedazzlement. We’re seduced by cartoon SIMULATIONS of thought’s outcome. We forget how to engage, and think, and develop the required outcome. And we lose, progressively, the ability to even know the difference. 

We’re not fully engaged. Our mind, not well engaged, is not well and truly at work. (remember the physical definition of work: energy has to be applied and not wasted)

We do things that look like work but aren’t. We work work work but we go only sideways. No forward progress is made. Worse, actually, than sideways. It’s decay. We’re moving backwards.

Digital models seduce.

We’re working working working working…, in desperate attempt to raise the digital model up above the (too low) mark of “obviously junk”.

Of course, when we reach that low mark, model quality still remains completely inadequate.

In tandem and at the same time, we struggle to attain visual clarity at enough locations of attentive visual focus within the models.

We fail to attain the level of such expressions that were handled in previous decades by earlier generations who had no digital tools at all

Our poor comparison to the past is brushed off because:

well, just look here at our beautiful model. 

We’re seduced by a cartoon, of something that looks superficially like a well developed model but isn’t.

It isn’t. But it dazzles.

This is siren song. We’re gonna crash on the rocks. 

We’ve hacked at the roots of cognition itself. 

Our form of engagement with the model, the engagement that drives the engine of thought that develops our understanding to the level required, we’ve sacrificed that. 

In its place we’re left only with a twinkle in our eye as we behold a cartoon instead, a cartoon we’ve exhausted ourselves to build, and about which we say, 

yeah, looks pretty good to me. 

And 

What were we doing anyway?

And look, yeah, we forgot. 

This is a downward spiral, and the down force is self-reinforcing.

At this point down the shaft we’d be better off abandoning the endeavor entirely and going back to drawing boards, drawing with pen and pencil in hand, on paper. A growing number of people see that. 

There is a way to rehabilitate digital modeling through evolution in our form of engagement with it, to reverse the screw and bring things back up again. I’ll get to that (scroll down). But we have to see:

What did we do wrong? 

Why is the engine of thought shutting down?

A review of basics:

We’ve always had models.

Models were mental before they were digital.

And we’ve always had (what I call) visual close study equipment (VCS equipment). VCS equipment in the traditional form of expression by which it is known, is technical drawing.

As models transformed over the last 40 years from mental to digital, or, that is, actually, from mental model, to mental model supplemented by digital model, slippage has occurred. 

Cognitive grasp, of the model, slipped. Backwards. This seems paradoxical, unexpected.

Why it slips, sadly is obvious in hindsight. 

No digital model has ever meant anything to anyone, without adequate mental model formation in tandem, which is built via close observation of the digital model. 

If this isn’t obvious, take a second to think about it.

Mental model formation

How does the mental model come to be formed? And how does it develop beyond superficial bedazzlement into an adequate state? 

In technical fields, ‘adequate’ refers to the degree of understanding, of very complex environments, and the complex tasks required within them. Superficial impressions are not enough. So digging deeper, through effective forms of engagement, and specialized equipment for this, are required.

The prize is interpretive adequacy, which refers to the movement of understanding to a point at which it’s good enough to support real work. Real work. Not work about work. Not meta-work. More direct: work that actually gets the useful things done.

How does that happen?

Do a test:

Think of something you’re familiar with, say, your bicycle, or, the chair you’re sitting in. Observe your mental model of this thing, the bike or the chair. What do you see? Is it adequate?

You can see, your model is very fuzzy, vague, has many things completely inaccurate, and more, missing. It has many gaps. Your model is hardly adequate. Your understanding, barely superficial. But you don’t need more. Usually. It depends on the task.

Most of us are not designing and fabricating our bikes and chairs. We just ride them (bike) or sit in them (chair). That’s it. Superficial understanding is adequate. It’s enough. We need no more. This is true for most things in everyday life. Hopefully we don’t treat our human relations this way. That’s another story. I’ll stay focused on things, not beings.

The mental model I formulate of a bike or a chair need only supply answers to basic questions.

Bike color, size, general appearance, is it my bike or someone else’s? 

The mental model of the bike supports my primary interactions with it:

unlock, sit on it, feet on pedals, push pedals, go, turn, brake, arrive, park, lock…

Beyond that, task requirements reach no further so the mental model need develop no further; surface appearance is enough.

The understanding I need of the bike, just to ride it, is different than the understanding reached by the people designing it, or the people in the factories building it.

They have to dig deeper, and engage with model formation differently.

Think some more. You already proved your mental model of your bike, chair, or try your car if you wish, is very fuzzy, inaccurate, full of gaps. OK, but what if I scan the bike? What if I make a NeRF or Gaussian splat or otherwise digitize the bike through photogrammetry or some other scanning method? 

Well, it’s the same problem. Again, the proof in 2 seconds:

The model is no better than THE REAL THING, right? The real bike, in the real world, you can look at it any way you wish. Look from any angle. Measure this or that. You can do the same against the digitized model. And you end up in the same place:

  • superficial engagement 
  • superficial understanding
  • fuzzy mental model, vague, inaccurate, full of gaps
  • support only for simple tasks like:
    • sitting in a chair, not designing or building it.
    • riding a bicycle, not designing or building it.
    • driving a car, not designing or building it.

Adequacy of mental model formation then, correlates with the kind of task it’s called upon to support.

So here are a few things that get overlooked:

  1. Task determines the degree and kind of thought that must be applied. Thought, and model formation, rises to the task required. Tasks such as:
    • Ride it (bike) or sit in it (chair), for example, or,
    • Design it.
    • Build it.
  2. The ENGINE OF THOUGHT is a TWO-POLE DYNAMIC OF INTERPLAY, between
    1. the wide expanse of the mental (and digital) model in formation, and, 
    2. our FORM OF ENGAGEMENT with the model, engagement that articulates our act(s) of visual close study (VCS) within the model.
  3. The ENGINE OF THOUGHT loses power when either pole in the two-pole interplay is disparaged or overlooked because of overemphasis on the other, and the ensuing exhaustion that comes from fighting against the inevitable decay, and the energy-wasting scapegoating and wishful thinking, bedazzlement and so on that ensue in place of focused, on-target 🎯 work.
  4. A downward spiral of decay ensues when (3) the engine loses power. The downward spiral is self-reinforcing. The people spiraling down with it are powerless to do anything to reverse it. Progressively the engine of thought de-powers toward shutdown.
  5. The down spiral (4) happens gradually such that the capacity to notice the difference also decays in tandem, further reinforcing the down spiral.

3, 4, and 5 are the unintended consequences of software that seemed so promising 20 years ago.

We could return to rooms filled with drawing boards and drafters drawing by hand with pens on paper. Look, the mind is fully engaged there and you can’t fake it.

You can’t do that work, technical drawing, without a mind fully engaged in:

  • Envisioning the (VCS) visual close study expressions you’re working on (your drawings) in-situ within the mental model you’ve put into formation and that you are
  • making progressively less fuzzy through the articulation of your FORM OF ENGAGEMENT with, and within, that model:
    • your VCS expressions within it, your drawings.

This (above) is the engine of thought, at work.

By the way, it’s worth repeating: What do drawings draw? What’s being drawn, by any drawing?

The answer is YOU. They draw you, into your model. They are about getting YOU, your attention, drawn into the model where you become well and truly engaged with the model, not superficially, but adequately, seriously. VCS equipment IS your form of engagement with models. With the mind fully engaged, through VCS equipment, then mental model formation can become adequate.

I should say again, although it’s truism and repetitive:

The same is true whether models are mental or digital.

Look, for the sake of argument, let’s just stipulate the perfectly complete digital model. There it is in front of you. Then what?

Can your mind digest it whole? Can you push a button and automate the interpretation of that model such that you just understand everything that needs to be understood instantaneously?

Or, can you fly around in the digital model haphazardly, raising that way your understanding above the superficial support of only the simplest tasks (like sitting in a chair or riding a bike)?

No.

Flying around in a model looking at whatever, superficially, doesn’t get the job done. No amount of superficial engagement will lead to anything but superficial understanding supporting only the simplest tasks.

Beware the Siren Song

Here’s the warning from 20 years’ industry evidence. We’re hearing the siren song of bedazzling seduction, the CARTOON of a well formed mental model that’s not. We’ve followed this song onto the rocks. And worse, it’s not just a ship wreck. It’s de-powering the engine of thought itself, step by step shutting it down. We’re hacking at the roots of cognition, disparaging one pole the two-pole interplay between wide expansive environment and narrowed attentive focus, between model and VCS equipment (drawing), smiling all the way down:

“look at my pretty model, …my precious”

Yeah, into the volcano with that ring.

The idea that one side of the interplay can be either discarded or stuck in a non-evolving centuries-old form of expression and externalized from the digital model is simply self-defeating and counterproductive, maximally. 

There’s another way out. if there is hope of reversing the decay brought by 30 years of digital modeling, then it is by pursuing a path that reverses the downscrew and restarts the engine of thought, through better forms of visual engagement with models.

We must put weight, again, on the other side of this two-pole interplay. The model is one pole. Our form of engagement with it is the other. The interplay dynamic between them is the engine of thought. In that interplay understanding grows.

We must give serious attention to the VCS equipment we’ve had traditionally (technical drawing), and how that equipment has to develop and evolve in support of the INTERPLAY through which we build our understanding of what we see, and what we’re doing.

An Open Source Proposal for the Development of the Future of VCS Equipment

This is an open source proposal for the whole AEC industry (and similar industries). Message me on LinkedIn if you’d like to participate in the open source development project just recently underway: https://www.linkedin.com/in/robsnyder3333/

The proposed development is outlined, specified, and demonstrated at my website https://tangerinefocus.com 

TGN is equipment for visual close study of digital models, just as drawing is equipment for close study of mental models.

So-called ‘CAD Drafting’, and the pre-digital form of it, technical drawing by hand, is well described as the expression and articulation of the act of (VCS) visual close study, of, or attentive focus within, mental models.

There’s a nice future ahead, for evolution in VCS equipment’s form of expression within digital models, no matter the manner of generation of those models.

Here’s a proposal for VCS development. It foresees a co-evolution of VCS equipment and generative digital modeling.

It’s a co-evolution we should have had all along these last 30+ years. We didn’t though, largely because of the magnetic attraction of the disruption-obsolescence-replacement narrative, the ‘out with the old; in with the new‘ enchantment prescribing the end of drawings via their replacement by digital models.

Some knew long ago that this was a slogan without load-bearing thought supporting it. If not for the thought-terminating power of the slogan, how much further ahead would model utility and usage have developed by now?

Much, I say. But I’m asking you to see what’s not there, to envision the path not taken as if it had been. Not easy, to see what should be there but isn’t.

Let’s make the next 30 years better.

These few short articles describe a forthcoming evolution in the development of equipment for visual close study (VCS) within digital models of all kinds in the architecture, engineering, and construction (AEC) industry and similar industries:

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