Since it has to do with evolution, it’s no surprise that the behavior of technology mirrors the process of natural selection. Who does the selecting? People do. We do. Processes, like Twitter, and tools, like the iPhone, live and die at the hands of users around the world who are quick to capitalize on new perks and are equally determined to move on to something else when their needs aren’t met. Both Twitter and the iPhone evolved from and came to be as a result of existing technology.

The iPhone was a spontaneous mutation, in evolutionary terms, and arrived on the market with no equal. Twitter also existed alone and was created to fill a void left by other social networking sites – but with no guarantee of success. Each was selected by users, either by chance, because of novelty, or some other reason, and continue to thrive in the midst of competition because they were amplified – more users jumped on board, or there was no alternative good enough to persuade people to move. So, people help technology to evolve.

But it also appears as though technology is helping people to evolve.

The Royal Melbourne Institute of Technology in Australia recently released the research of Dr. Larissa Hjorth, who is a digital ethnographer, or “someone who charts cultures as technocultures.” In “Social networking around the world” she talks about how styles of technology adoption vary with culture.

“Each culture massages and transforms a technology. So devices such as the mobile phone are used in different ways according to the cultural context”

Hjorth uses China as an example of a society whose use of social media and mobile devices is beginning to blur the lines that previously separated entire classes and generations. A huge impact is being made on the way ideas are communicated and knowledge is acquired, which is why some networks have been under scrutiny by Chinese higher-ups. The decentralization of power is one thing in a circle of friends, an organization, or a democratic society. In China, it’s something else that has already become controversial – I submit Google’s argument with China.

Brian

You don’t see extensive sociological or psychological research done on couples interested in adoption. But increase the sample population to, say, the size of an organization and all of a sudden the problem – and the solution – become intensely more complicated. So many people, so much to address. Complexity at its finest.

“User Acceptance of Information Technology: A Unified View” by Venkatesh, Morris, Davis, and Davis (not a typo) is a weighty scientific paper that puts forward a methodology and initial results for a model of assessing technology implementation called UTAUT – Unified Theory of Acceptance and Use of Technology. Unfortunately, it was all too easy to glaze over the science while looking for more practical conclusions and information. However, there were some specific elements that stood out as broad, contextually understandable psychological theories about people and they way they behave.

The Motivational Model (MM) neatly encompasses the intrinsic and extrinsic features of technology that can persuade an employee to change behavior. Intrinsic motivation applies to situations where people may be sincerely interested in the task at hand and are comfortable doing whatever is necessary to complete it. That is the extent of their commitment. Extrinsic motivation, on the other hand, is where the task is essentially baited by promises of pay or other valued commodities, and the employee has interest only because they are looking to achieve a separate end goal.

The Innovation Diffusion Theory views technology integration from a sociological perspective that has been shown to offer a predictive advantage for its users. It reviews core elements of the organization that can affect the way employees perceive or acclimate to a different workflow with new technology: relative advantage, ease of use, the image (perceived practicality), visibility (are other people seen using it?), compatibility (does it do what I need to do?), results demonstrability (proven track record), and voluntariness of use (perception of there being free-will and no obligation to use it). If nothing more, these ideas allow IT departments to consider specific aspects of organizational implementation that may otherwise be ignored or misunderstood.

That’s it for now, but there is certainly more to review. And it will be done. As time permits, I will edit this post and report back on the latest readings.

EDIT 2/13/10: Continued…

Fuller, Hardin, and Scott published “Diffusion of Virtual Innovation” in 2007 as a digital-age expansion “on Rogers’ diffusion of innovations theory”. The authors conduct a comprehensive review of both bottom-up and top-down techniques, and they differentiate between the perception of usefulness and other a priori conclusions in individual assessments of technology and the issues of relative advantage and compatibility that become important at the organizational scale.

The Theory of Reasoned Action is brought up as a significant theoretical perspective on the way individual people arrive at decisions that can influence their tendency to adopt a certain technology, especially when it is virtual (digital). While ease of use and usefulness are, again, shown to be important here, virtual technology offers more benefits that fall outside of the scope of these two ideas. For instance, users’ perception of ease of use and usefulness may actually depend on how easily they can customize content and take full advantage of the new technology in innovative, forward-thinking ways. This suggests that people might actually be more interested in adopting an entirely new workflow, instead of just using new tools to accomplish the same goal in the same way. Things like dynamic “creative self-efficacy” can begin to emerge once employees recognize new features and ‘branch out’ from their prescribed tasks.

Of course, computer self-efficacy – that is, the technology’s ability to lessen, instead of just improve the workload – can also become an issue. The complexity of technology in organizational systems means that organizational culture will need to change, if for no other reason than to specifically make workers comfortable and familiar with the idea of the technology, in addition to being comfortable and familiar with the technology itself.

When the goal of technology adoption orients itself with a shift in corporate culture, the responsibility for embracing virtual innovation shifts from the employees to management and the way they embrace the most fundamental aspects of the idea. Acceptance at the top will signal the bottom that it is ‘okay’ to start getting interested.

I suppose, with all of this, the worst case scenario would be a child adoption company that is looking to use new technology. Then, I just don’t know.

Brian

The idea of chaos theory is really quite humbling when you realize that scientists themselves are at a loss for words to articulate it.  But our inability to describe chaos does not mean that the theory is indescribable.  Despite short definitions that have been put forward, most people still find it difficult to wrap their heads around the real meaning.  In 1999, Neil McBride said it can be considered “ordered disorder” and James Gleick said in 1988 that, to some, chaos is a “science of process rather than state, of becoming rather than being”.  But most research papers on the subject admittedly defer any definition with essentially one phrase: “see complexity”.

So now we’re left trying to simplify an already loosely-defined chaos with something called complexity.  Bonus points for the cynical name-givers in the world of science.

Nevertheless, chaos and complexity are mates.  I’ll give a shout out to the Santa Fe Institute (SFI) for their work in unraveling the mystery.

Complexity simply talks about the way things become complex.  With all the individual people in a world that is constantly changing with rules and laws and expectations that evolve just as steadily as the clock ticks forward, we can’t possibly sit here and consider the impact of every possible decision made tomorrow, in an hour, in a minute, or while I type the ellipses at the end of this paragraph…

Yet this kind of rationale has been the backbone of traditional economic theory and Newtonian mechanics, which work on the assumption that everything is calculable and predictable.  We don’t consider every statistical option or conduct a perfect cost/benefit analysis when we’re shopping for freeze-dried TV dinners, and the universe is not a figurative system of gears and wheels that operates in ways as predictable as we would like.

This scenario (which, by now, should start to sound like the world we live in) is representative of a system.  A complex adaptive system, actually, which is more broadly and scientifically defined as having (1) many interacting agents, (2) a dynamic environment, and (3) evolving rules.  There are regular ‘complex systems’ out there, but the existence of changing parameters – whether it’s laws that govern us or survival instinct with which we’re biologically wired – affects each agent and has a significant impact on their behavior.

Ants are a popular way to visualize complexity.  On its own, a single ant is worth very little.  It just sits there, pokes through the air with its feelers and hopes that it is far, far away from some kid with a magnifying glass.

But we seldom see one ant.  And we seldom see many ants doing something short of amazing.  Anthills, production lines, distribution channels, and cavernous tunnels are carved out by a colony of workers whose very colony is the result of complexity.  Running down the list and making very basic conclusions in the process, we see how thousands of interacting agents (ants) have amassed to construct something beyond the wildest dreams of any individual ant.  We also see that their success is contingent on an environment that is conducive to their survival, or at least was at the time of selection (ants will infest homes with food and shelter, until it is fumigated – hence dynamism – and forces them to regroup and ship out).  And, in some ways similar to the environment, the rules by which the ants exist are well defined but also adaptable.  Some are wired to simply “take something from the guy on my left and hand it off to the guy on my right”.

With a system like this, structure inevitably emerges with no handbook, no policies, no regulatory framework.  Just ants.  And complexity.

Organizations – companies, agencies, stores, governments – are all complex adaptive systems as well.  But saying that something is a complex adaptive system is like saying that a muffin is just muffin mix and water (or whatever muffins are made of – I haven’t had one in a while).  We use chaos theory to explain how complex adaptive systems behave.  How the world operates.  Our MO, whether ants or Amazon.com.

So that circuitous definition scientists like to give for chaos sounds something like this, courtesy of McBride in 2005:

This chaotic behaviour does not indicate a lack of order. Rather, the order is difficult or impossible to describe in simple terms and requires complex narrative description.

This post is already quite long so let’s break it off here.  Chaos will come in the next post.  For now, enjoy a PDF version of a Powerpoint I gave in class in conjunction with Scott Renick about chaos, complexity, and systems theory.  Elaborate ramblings will come soon enough.

In his first book – Enterprise 2.0 – McAffee identifies three trends in Web 2.0 that have allowed it to be come as successful and prevalent as it is today.  First, he discusses the need for a platform for a communication that is both free and easy; second there must not be an inherently imposed structure; third, structure must be allowed to develop organically.

The most startling example McAffee gives of this is Wikipedia.  Jimmy Wales’ first stab at creating a high-quality encyclopedia was Nupedia, a bureaucratic process of expertly-reviewed articles that generated 24 entries in 42 months.  Wikipedia, on the other hand, had no such stipulations and allowed anybody to submit and peer-review articles.  It published over 19,000 high-quality encyclopedia entries in less than 12 months.

While the expectation might be absurd, the fact that Wikipedia’s hundreds (if not millions) of users successfully generate accurate and high-quality content is impressively outrageous.  But it works.  Remember: just because there is no imposed structure does not mean there is no structure at all.

As an activity that involves human behavior, Wikipedia or Twitter are complex adaptive systems – participants are constantly acting and reacting in ways defined by other people’s own actions and reactions.  The network of connections within an organization that allows this is intertwined, very complex, and unpredictable though not irrational.  The theory of complexity goes hand-in-hand with the ‘orderly disorder’ that is presented in a theory called chaos.  But that’s for another discussion.

Like many, I’m sure, I first learned about the earthquake in Haiti over Twitter and it has been the dominant news story in all forms of media for the past week.  Peter Shankman is a published author and self-proclaimed CEO, entrepreneur, and adventurist, but with his journalism experience and social media prowess, he came up with a list of ways to use Twitter to report breaking news.  His very suggesting of ways to use Twitter might look like he’s butting heads with the open-source and free-form fabric of social media, but Shankman’s list actually compliments McAffee’s points nicely as the list on his blog reflects the structure autonomously created and accepted by Twitter users and not Twitter itself.

This means that social norms and social media are friends.  About this, McAffee writes on page 75:

Most decisions are made by consensus among senior members of the community…As Wales has put it, “The wiki model…gives you an incentive when you’re writing.  If you write something that annoys other people, it’s just going to be deleted.  So if you want your writing to survive, you really have to strive to be cooperative and helpful.”

The social aspect of social media – whether it’s in the form of an organizational network or a group of friends on Facebook – comes with the same baggage as ‘real life’ social networks and groups.  We want to be popular.  We want to fit in and be noticed as having worthwhile contributions instead of ostracized and ignored.  The extent to which we crave this varies, but the same motivations do apply online and have been guiding the structure of Web 2.0 since the beginning.  The Nupedia/Wikipedia numbers illustrate the potential quite nicely and now, those who embrace Enterprise 2.0 will be able to support the same kind of creativity and innovation in their own boardroom.