Zefra

A friend sent me a copy of the book Crisis in Zefra, a fictional story about a future peacekeeping/counterinsurgency deployment, intended as a longer-term scenario planning document.

It was written by Karl Schroeder and can be downloaded from his site here. The book was commissioned by the Canadian military to help think through the shape of future missions. It is set, notionally, in about 2025.

The book covers a short period of time in the run-up to elections in a sub-Saharan city, beginning with an apparently normal day, during which counterinsurgents mount a major attack.

The book attempts to extrapolate technologies that are in use today to the 20-year-out timeframe — with varying degrees of success. Overall the book is interesting and worth reading for anyone who’s interested in asymmetric warfare and associated technologies.

As with most scenarios, the most interesting aspects are the blind spots. There are, of course, endless possibilities for how particular technologies might develop and so there are many potential arguments about whether this or that technology will be usable in that time frame. But there seem to me to be a couple of more strategic issues:

1. Although there is a strong awareness of data analysis and knowledge discovery as important technologies, they are regarded as analyst tools to be invoked for a specific purpose when something attracts an analyst’s attention. For example, the technology to go back through satellite imagery and track back the trajectories of trucks and other vehicles is imagined. However, there is not sufficient awareness that these technologies can be used in a less-supervised way: by analysing such data constantly and reporting anything that appears anomalous, for example. In fact, these technologies are often most effective when they are used in a symbiotic way, with analyst and analysis software working in a tightly-coupled way, in which both sides develop their “understanding” and “techniques”.
2. As I’ve commented before, when talking about sensemaking, most asymmetric and counterinsurgency settings should be regarded as complex systems, not complicated ones (in the Cynefin sensemaking sense). This difference is not appreciated in the analysis — the underlying attitude is that understanding the threats of the city is a big, messy problem, but one that could be fully dealt with, given enough time and resources. There’s not enough awareness of the unexpected, and broad planning for contingencies (“unknown unknowns” in the late-lamented phrase).
3. Granted the existence of the level of technology in the story, not enough attention is paid to its prophylactic use. For example, it’s assumed that each patrol is proceeded by chemical sniffers that are able to detect the presence of explosives (the presumed solution to today’s huge problem of IEDs). However, given this technology, it would make sense to deploy it to provide barriers across which it would be difficult to take explosives at all — making it hard to get explosives into the city in the first place. Even if it is not practical to put a complete ring around the city, there are lots of benefits (as I’ve suggested in earlier discussions of defence in depth) to putting a border in place and looking hard at who tries to sneak around it.
4. The one place where the technology extrapolation seems to be badly off is the assumption that the counterinsurgents will have biological weapons that can target anyone not a long-term inhabitant of the city because of their bone composition. This, it turns out, depends on what’s in the water that people drink over time. The technology to make these kind of assessments exists — there have been stories about police using them to determine where a body has come from; and no doubt we’ll see an episode of Bones that depends on this soon. But it’s a huge step from being able to detect such things in the lab, and being able to develop a biological vector that could be based on them. Not only is this probably too big a step for 20 years, but it’s also probably always going to be a bad idea because of the probability of unintended consequences.
5. Maybe this is a blind spot for me, but the book assumes that patrols will continue to be an essential part of a deployment. And this in a world of semiautonomous devices that are at least as well equipped as an infantryman. I continue to be puzzled about the point of sending out patrols as a routine thing in Afghanistan. I can’t see any point to them in a city environment. Obviously, there are reasons for the military to go outside the perimeter of a secure area, but I don’t see the point of doing so to “show the flag” or any other diffuse goals.

These are not meant as criticisms of the book, which is an interesting and thought-provoking read.

Sensemaking

Sensemaking is the way in which people understand the world at large scale: how they decide what kind of goals are reasonable to try for and what kinds of strategies are worth trying or using. Sensemaking is related to what the military call situational awareness.

One of the best ways I’ve come across for thinking about sensemaking is the Cynefin framework, developed by Kutz and Snowden.

They suggest that it’s helpful to think of the world, or systems, as being of five kinds:

1. Known systems, where cause and effect are clearly understood, and the “rules” are understandable and widely understood.
2. Knowable systems, where causes and effects are separated, but analysis, systems thinking, scenario planning, and other mental tools can produce some level of understanding.
3. Complex systems, where causes and effects only make sense with hindsight, and patterns are seductive but entirely misleading.
4. Chaotic systems, where there is no discoverable relationship between cause and effect.
5. Disordered systems.

Most adversarial situations, and many others, are complex systems. The danger is that they get treated as knowable (complicated) systems.

Kurtz and Snowden give two great examples of the problem caused by confusing the two. A group of West Point graduates were asked to manage a kindergarten. They developed objectives, made plans, identified back up plans; and the whole thing was a total disaster.

In another case, marines were taken to Wall St and played against traders using trading simulators. Unsurprisingly, the traders won. Then the traders were taken to Quantico and played war games against the marines. Again the traders won!

In both cases, the situations are complex, and so rational planning is not the way to approach them. A better approach is to look for aspects that are considered positive and find ways to enhance or reward them, and look for situations that are negative and discourage them. The traders did better than the marines because they were able to see and exploit transient opportunities. Kindergarten teachers don’t base kindergarten activities on a carefully worked out plan either.

This structure is characteristic of complex systems, where the Law of Unintended Consequences rules. Systems can be nudged in a good direction, but only nudged, not pushed wholesale. If a nudge turns out to make things worse it’s easy to back off, and maybe to reverse it.

Insurgencies are complex systems, and so are terrorist attacks, and it’s both dangerous and fairly useless to try and defend against them using techniques appropriate to knowable systems.

Knowable system approaches still tend to creep in. Here’s a quotation from U.A. Army Field Manual FM3-24 Counterinsurgency (the famous Petraeus manual in use in Iraq):

The underlying premise is this: when participants achieve a level of understanding such that the situation no longer appears complex, they can exercise logic and intuition effectively.

(of course, “complex” here doesn’t mean in the Cynefin sense.) Much of the language in paras 4-2 to 4-13 has an implicit assumption that counterinsurgency situations can be understood by rational planning, given enough time, effort, and thought.

In insurgencies and terrorism, it’s probably not possible to get such an understanding, and perhaps foolhardy to try. It seems helpful to be able to distinguish the two kinds of situations that might look superficially similar, but are hugely different underneath.

(There are many other interesting ideas in the Cynefin framework. A good starting place is here.)