techniques for making sense of complex environments, IN those environments…
By coincidence, or rather maybe at random, I’m skimming this book today: “The Elements of Statistical Learning, Data Mining, Inference, and Prediction”. The graduate student who showed it to me (thank you Yifan) says that the book, published in 2008 and written by leaders in the field (Trevor Hastie, Robert Tibshiran, and Jerome Friedman), would be better known today by the title: “Machine Learning”; because statistical learning is a large part of what is now known as “machine learning”.
See this, at the beginning of the book’s preface:
“We are drowning in information and starving for knowledge.”
–Rutherford D. Roger
Also randomly, at an airport yesterday I picked up the Harvard Business Review, not because I’m happy about the $16.95 price, but I like the articles. A couple of quotes jump out of the June 2015 issue.
On page 27, in discussing problem solving through discussion with experts from analogous fields:
“…the client – someone in a branch of the U.S. military – was interested in finding ways to pluck crucial data points from a stream of confusing information. The participants included a police detective, a fire chief, a stock broker, a novelist, an air-crash investigator, a historian, and a major-league baseball scout, all of whom described how they gather information and separate important data from noise…”
And on page 32, in an article about visual memory:
“…But we’re also dealing with attention saturation. It would be overwhelming and maladaptive to mentally record everything we see. So subconsciously we let some things fall away.”
I come back to this topic on this blog, often. From this post, “focus- attention”, citing http://en.wikipedia.org/wiki/Focus_(cognitive_process):
“Attention is the cognitive process of selectively concentrating on one aspect of the environment while ignoring other things. Attention has also been referred to as the allocation of processing resources.  …The relationships between attention and consciousness are complex enough that they have warranted perennial philosophical exploration. Such exploration is both ancient and continually relevant, as it can have effects in fields ranging from mental health to artificial intelligence research and development.”
And, here, Intelligibility Machine:
Rodolfo Llinás is the guy who noticed that every multi-cellular organism that moves, has a brain.http://www.americanscientist.org/bookshelf/pub/from-motricity-to-mentality#! And he proposes why: …organisms that move need to predict (or visualize) the future, and their place in it. What happens if I move there as opposed to there, or there? (Do I jump into a lion’s mouth?) The brain processes a complex information environment (the world), brings to it a coherence sufficient to allow detection of what matters and what doesn’t, thereby supplying focused, clarified, information for reflection and affirmation supporting action (where to move next in the environment). This is sense-making. Without this ability, we’re simply overwhelmed, unable to act, think, function…
The problem is generalizable and universal. Data environments, of any kind, in any domain or field, as well as in everyday life, always impose on users twin burdens: information overload, and information omission uncertainty (or doubt); overload and doubt. Mitigating these pervasive and constant twin burdens requires application of certain mental capacities and effective technique.
Would we expect the field of architecture, engineering, construction (AEC), or engineering, procurement, construction (EPC), to be an exception to this? No, and on the contrary, AEC/EPC is a particularly good case study, of technique and method that sorts through and makes sense of exceedingly complex information environments.
In AEC/EPC, just as in all other domains and fields, and in everyday life, there are two buckets, two categories of things:
- The first bucket is all the data you have, your hybrid environment of complex data. In AEC/EPC, the information environment is composed of various different types of data including models, point clouds, photos, videos, databases and so on. All of this is bucket 1. Typical goals for the development of bucket 1 are to allow the bucket to grow, as new data is acquired and developed, and, to align all the data types into a continuous hybrid environment of information
- The second bucket is all the kinds of techniques and methods you use to make sense of bucket 1… all the techniques you use to focus in and narrow down, to articulate, to communicate, to clarify, and to affirm, declare and assert. In other words, everything you do in the data, all the techniques you use, actions you take, to draw attention to things that matter, to show things in ways that support understanding and informed action.
Typically in AEC/EPC bucket 2 is done in the abstract, outside of bucket 1, outside of the rich hybrid spatial environment. One of the techniques for doing this…
for narrowing down and focusing in, for clarifying, asserting, communicating, for drawing attention to what matters and showing things in ways that support understanding and informed action
…is a technique industry is familiar with: the production and use of a set of drawings. The technique (a set of drawings) is indeed so familiar that these days we tend to deal with drawings from habit and easily overlook their full functional value. That being the case, it seems a good time to take a fresh look at drawing, and more fully consider both its scope and limitations. Let’s begin with scope.
The production and use of a set of drawings is a systematic method, or device, or technique, for looking at, sorting, making sense of what is otherwise an overwhelmingly complex environment of information. That environment of information, against which the technique of drawing is applied for sense-making, may exist either in the mind (imaginary), or in software (digital), or in the real world, or, of course, the information environment may exist in all three of these at once. To produce and use a set of drawings, is to systematically pick out what matters, to narrow down and focus in, on specific locations and/or events that matter in the environment (in the space of a proposed project). Through “drawing”, what is drawn in fact is one’s attention to what matters, to a communication that renders overwhelming complexity intelligible. As is always the case with focus and attention, the goal is intelligibility and understanding, the support of informed action through articulate affirmation, declaration and assertion.
Drawings, let’s not understate, are significant in scope. But let’s consider also limitations. While their scope is to communicate, their reach in achieving this is imperfect. There is ample room for improvement. Overcoming limitations and finding improvements may come from recognizing that drawings exist typically outside of bucket 1, which is to say, they are delivered in the abstract.
Naturally, abstraction from the information environment was necessary and unavoidable when models were imaginary, held in the mind only, before computers. To communicate, with focus and clarity, drawings necessarily were external to, decontextualized and abstracted from, the mental model, for obvious reasons.
This separation is no longer necessary however. Today, bucket 2 sense-making technique, devices and events, may be expressed inside of bucket 1, inside and in-situ within modeled information environments. This possibility is shown, in the case of drawing (which is a primary sense-making device and technique in AEC/EPC), by recent developments in software that express the function of drawing, in a literal way as a first step, in-situ within modeled environments. That first step appeared in software from Bentley Systems in 2012 (more information here and here).
Certainly this is just a beginning.And it is opportune now for all of us to imagine not only the expression of conventional bucket 2 techniques inside bucket 1, like those in this demo playlist on YouTube, but to imagine new kinds of powerfully effective sense-making technique, new kinds of clarifying events and devices expressed in-situ within our increasingly rich and complex information environments. What could be the scope and limitations of this possibility? We need to find out. Imagine the possibility; see how far it can go.
Who will pick up the ball and run with it? The frontier is wide open.