Home » Change, Digital

Intelligent Devices / Collective Intelligence

Submitted by Joshua-Michéle on June 8, 2011 – 7:09 amView Comments

If you're new here, you may want to subscribe to my RSS feed. Thanks for visiting!

Recently I had to jot down a few talking points  on some ways that the network economy is impacting business strategy.   I dealt with about three trends.  Below is the first set:


1.

Everything that can be networked, will be networked (phones, computers, books, music players, automobiles and even our own health data thrown off from bathroom scales, pedometers and the like ).   Each device, once connected,  becomes capable of extraordinary things; They will be smarter, they will have memories, they will know who you are and they will have extraordinary powers of prediction.   And the more data it connects to – not just from you – but from other devices,  the more valuable it gets.  In this inevitable future, a connected device is really just software in a very cool package  and the more data is has to process, the smarter or more valuable it gets. “Dumb” gadgets become commodities. As the “always-on” world awakens to the need for a continuous stream of compelling content, the data exhaust from sensors embedded in our connected devices becomes a living narrative and a source of high value content.  Examples: FitBit, NikePlus etc.


2.

The brushed aluminum back of the iPad Wi-Fi

Image via Wikipedia

Intelligent devices become distribution channels for higher value content or data.

Think about how the iPad becomes a a distribution platform that allows us to monetize once-free content now that it is “packaged” within an app.  The same goes for much of what is taking place on the  Android, Apple and Ovi app stores. (see Jim Stogdill’s excellent Radar post on this subject: (http://radar.oreilly.com/2010/04/the-ipad-isnt-a-computer-its-a.html).

3.

As devices get connected, the ecosystems they belong in (the user data and sensor data they collect and utilize, the user experience they connect to  across paid, earned, owned media etc.) becomes so complex as to be entirely unmanageable by human beings. The opportunity is to abandon a “central planning” approach and begin programming for collective intelligence, that is coding ecosystems that evolve based on real analysis of how customers are using them (what Web 2.0 has been saying all along).   Programming for Collective Intelligence allows us to move away from centralized planning towards a system that course-corrects based on real usage patterns of users and provides dashboard visualization as a sort of cockpit from which to tweak the overall direction (business goals, KPIs) against which the system is designed to optimize.  While this approach has been fairly obvious in the management of complex supply chains and massive data processing tasks such as online search, we have seen very little true optimization of customer experience.

Enhanced by Zemanta
  • Share/Bookmark

  • Ted Herman

    Point 4 would be the role of Cloud as the place where the streams fuse, and become mined.  Point 3 does not acknowledge the fundamental, intrinsic difficulty of distributed (decentralized) self management: higher-level thinkers usually dispatch such things as mere engineering concerns.  But the dream of truly distributed self-organization (and self-healing, positive evolution, etc) will likely run into deep limits and basic conflicts of goals.  And this gets us back to Point 1.  Once we become aware of the costs and problematic choices, we may decide that *not* everything will get connected.  Beyond the costs, we may find that collective intelligence is a capricious thing, unstable without selective application and guidance.  The specification of "collective intelligence" itself is quite vague, so we really don't know what to expect.  

    Above, my thinking is to the distant future, not the next few coming years. When I think of business strategies, getting on board with Big Data, formalizing more data with the aim of converting it to information, using better computational tools, and a general "mashup" approach to doing things (with lots of other memes thrown in) does seem to be the trend, and it's sensible not to fight the trend.  However, it's also wise to be careful of product designs with too much reliance on evolving platforms.  A product that relies on five service platforms to perform robustly is inherently less vulnerable than one that relies on ten service platforms.  Control those dependencies.

  • joshuamross

    Ted - fantastic.
    Yes - the cloud is the precondition that allows for all of this data to be pooled.  

    But your comment on point 3 (from my POV, that we will need to program for collective intelligence in order to manage the proliferating touchpoints  that any sizable organization is trying to operate) - is what I find most interesting.   I approached the subject from watching organizations struggle with the transaction costs of trying to  deal with such complex "ecosystems" - and thinking that it resembles central planning.  Once these plans leave the design room they hit user behaviors and expectations and things quickly get out of control.  Central planning usually has poor measures, slow feedback and reality is created "in the building" and not out in the world where things are actually taking place.   Your point is well-taken.  I have not worked at any organization that has effectively been able to deploy against Big Data as you suggest.  

blog comments powered by Disqus