Has the OODA Loop Gone Mainstream and Digital?

Our economy may be going through yet another fundamental change, from the Information Economy to the Feedback Economy.  Forbes thought the idea was buzzworthy enough to reprint the article linked below.  The concept begins with the familiar paradigm of the OODA loop used by fighter pilots.

Military strategist John Boyd spent a lot of time understanding how to win battles. Building on his experience as a fighter pilot, he broke down the process of observing and reacting into something called an Observe, Orient, Decide, and Act (OODA) loop. Combat, he realized, consisted of observing your circumstances, orienting yourself to your enemy’s way of thinking and your environment, deciding on a course of action, and then acting on it.

OODA Loop

The most important part of this loop isn’t included in the OODA acronym, however. It’s the fact that it’s a loop. The results of earlier actions feed back into later, hopefully wiser, ones. Over time, the fighter “gets inside” their opponent’s loop, outsmarting and outmaneuvering them. The system learns.

According to the author, this “system learning” is now becoming digitized for everyone by communications infrastructure, massive platforms, data mining and machine learning, all linked to human experience.

We’re drowning in data. Bits are faster than atoms. Our jungle-surplus wetware can’t keep up. At least, not without Boyd’s help. In a society where every person, tethered to their smartphone, is both a sensor and an end node, we need better ways to observe and orient, whether we’re at home or at work, solving the world’s problems or planning a play date. And we need to be constantly deciding, acting, and experimenting, feeding what we learn back into future behavior.

We’re entering a feedback economy.

You can read the whole thing here:  The feedback economy – O’Reilly Radar.  It’s an interesting perspective, and not overly technical.  However, the article gives only cursory consideration to the delicate legal and privacy issues associated with data collection, mining and machine learning.

A cautionary perspective is posted below the break.