Galambos on Innovation, Systems of Systems, and Logistics

Here is Jim Galambos on Voices from DARPA, talking about platform design and cost disease:

What do we mean by system of systems? It’s really this idea that as our defense has matured over the last few decades and we make more and more capable platforms–and a good example of this would be, say, an airplane or a submarine–these are becoming very sophisticated platforms, very capable, but they’re also expensive. They also take long time to make and what we’re finding is, to make them even better costs a lot of money and time and you don’t necessarily get that much more capability than you had. If you will its kind of creating an asymptote, as you put more effort into it its getting incrementally better.

This problem has been recognized for a while now. The 1972 COPG Report provided an illustration of what, over the prior decade, had been referred to as the “technological plateau.” It finds that the marginal benefit of R&D investment decreases in a specific technical approach. It implies that disruptive innovations, new ways of doing things, are the only source of long-run progress.

Reproduced figure from the 1972 Commission on Government Procurement (COGP) Report, depicting the leveling-off of performance gains as more dollars are expended on a specific technology. The figure suggests the importance of discovering new technologies, the only source of progress in the long-run.

DARPA’s program manager Galambos recommends dis-aggregating functions from major platforms as one way of decreasing cost while increasing performance. However, if you take, for example, sensors off of a platform, they need to operate and communicate reliably. Then you have more signals that must be processed. Here’s Galambos:

So we talk a lot about, hey, how can we have machine learning and [artificial] intelligence help pull this stuff together and interestingly what we almost always end up with is logistics, because one of the issues is, now I’ve got more things spread apart, how do I get them there and how do I sustain them.

The body works well, the eyes come with the head, its a nice package. Now I’ve got these two extra eyeballs out there. Whose going to hold on to those and keep them cared for, fed, etc.

So if you can have multiple sensors located in different areas, you can “see” more, it’s harder for the enemy to countermeasure, and the system’s performance degrades “gracefully” when a sensor is taken out because you can employ them redundantly. 

But the downside is logistics, and in war, the logistics associated with physical and informational goods is precarious. For example, Russia is building a drone-jamming force. Maybe the dis-aggregation concept, for now, works better in a counter-insurgency context than near-peer warfare.

Different environments create unique forces toward centralization and decentralization. It reminds me of how slime molds can exist as independent cells when times are good, but they work together under stress. As Steven Johnson writes in Emergence:

When the environment is less hospitable, the slime mold acts as a single organism; when the weather turns cooler and the mold enjoys a large food supply, “it” becomes a “they.” The slime mold oscillates between being a single creature and a swarm.

In the market economy, I like to think of the price mechanism as a system that intermediates information on a decentralized basis. It provides feedback about whether it is efficient to pursue more centralized coordination (increasing the scale of firms), or whether it is efficient to pursue more decentralized coordination (more contracting, start-ups, etc.). Prices also discipline firms, which determines whether they decentralize themselves such as found in subsidiaries, or 20% time at Google, or the 2-pizza rule at Amazon.

How can a military system of systems overcome the logistics problem in a sufficiently far-from-equilibrium environment? How does the system flex between decentralized and centralized structures? Galambos recognizes the challenges but also the payoffs of success.

This is why we’re doing this at DARPA. It’s not 100 percent certain that this is the way to fight in the future. It’s our hypothesis, and there’s a lot of evidence to suggest that if you can do it it’s a great way, but that’s a big if and that’s why we’re doing the research…

For slime molds and in nature more generally, it appears that environmental perturbations and feedback loops create coordination whose processing power is decentralized. This form of coordination might then beat out competitors in the evolutionary filter. It does not take a centralized processing system with fail-proof communication.

Here’s Steven Johnson again on the aggregation and dis-aggregation of slime molds:

Cells would being following trains created by other cells, creating a positive feedback loop that encouraged more cells to join the cluster…

If each solo cell was simply releasing cyclic AMP based on its own local assessment of the general conditions, Keller and Segel argued in a paper published in 1969, then the larger slime mold community might well be able to aggregate based on global changes in the environment – all without a pacemaker cell calling the shots. [Emphasis added.]

Slime molds, such as Trichia varia shown here, can aggregate and dis-aggregate according to the environment, but each cell does so according to local conditions and positive feedback loops. It doesn’t require centralized command such as a “founder” or “pacemaker” cell, which requires logistics and communication.

“The response was very interesting,” Keller says now. “For anyone who understood applied mathematics, or had any experience in fluid dynamics, this was old hat to them. But to biologists, it didn’t make any sense. I would give seminars to biologists, and they’d say, ‘So? Where’s the founder cell? Where’s the pacemaker?’ It didn’t provide any satisfaction to them whatsoever.” Indeed, the pacemaker hypothesis would continue as the reigning model for another decade, until a series of experiments convincingly proved that the slime mold cells were organizing from below. “It amazes me how difficult it is for people to think in terms of collective phenomenon,” Keller says today.

That’s as far as I’m willing to speculate on systems of systems. Here is Galambos on his early days experimenting at Los Alamos:

It was the first time that I was in a laboratory and we were trying to do something that we did not know how it was going to turn out. Previous to that, in classrooms and laboratories or science fairs in high school, you were usually just trying to make something work that you knew the answer to but it was just could you make it happen. And it was at Los Alamos where I finally saw, we were doing experiments and I realize these really bright people, they hoped they would know what was happening, but the reality was we we did experiments to find out. That was very exciting to me.

More defense policy needs to be based on the idea that, even in engineering development, smart people cannot predict exactly what will happen. As Michael Polanyi argues, if we demand of an idea that it be completely articulated before it be given the appellation “knowledge,” then we will find we know nothing at all.

This was interesting too:

We were looking at was can I create an undersea shock-wave, which means basically light off an explosive under water, but do it in a way that we could shape those shock-waves to all pile up on top of each other and smash something like a mine. So we were actually looking at mine clearance doing that.

Because the concept deals in fluid dynamics, outcomes depends on the unpredictable nature of turbulence and can only be arrived at experimentally. Good luck having tried to calculate that design before experimental data.