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Desire and Intent

Given the semantic nature of the argument, I’ve tried to avoid splitting this hair. But I’m started to see an important distinction between two very similar words which are often used to describe a user’s potential behavioral motivation–desire and intent.

While these two words appear to have the same meaning in certain contexts, I think they probably have very different origins. It may be anecdotal and even difficult to demonstrate, but I believe there is an argument that while the two concepts may lead to the same end result (i.e. behavior), they’re really two separate devices which often facilitate a user’s decision making in combination with each other, like two spinning cogs.

Let’s take a look at the definitions.

According to New Oxford the word desire means, “a strong feeling of wanting to have something or wishing for something to happen.”

The word intent, on the other hand, means, “resolved or determined to do (something).” And according to Merriam Webster this something is “usually clearly formulated or planned [...]”

So, intent then seems to require some level of forethought, whereas desire requires nothing but a longing. I’ll take it a step further and say that within interaction design intent usually takes a specific action. This action is usually rooted in a basic need (i.e. to do something),

Meanwhile, desire has more to do with a thought process rooted in a basic want (usually to know something). Perhaps this is oversimplifying a bit, but I think the two ideas are isolated enough for closer examination.

This distinction can manifest itself in many ways within a typical human-centered design. The easiest example I can think of are the everyday links found on many e-commerce sites to either “Learn more” or “Buy now.” While it could be argued that both are intents (or desires), the link to learn more is usually designed to precede any decision-making by a user. Therefore, if we accept that intent requires forethought or planning, the learn more link becomes much more about the fulfillment of the user’s on-demand desire (and if I’m honest, to instill enough confidence into the user for them to ultimately have the intent to purchase).

Of course, desire can lead to other decisions, insights, or navigational paths, while intent is usually more directed and orchestrated by a specific design or process. Again, I may be simplifying an already gray area, but I think this contrast may reflect a basic design tension in and of itself and can be used to resolve designs that require various levels of decision making by an end user.

Usable Taco Shell Design

The patent for this invention takes 65 paragraphs to explain a design that’s utterly, if not painfully, obvious in hindsight–the square taco.

The self-standing taco shell makes it easier to prepare multiple tacos at the same time. This advantage is especially desirable in fast food, cafeteria and party environments where multiple tacos are being prepared at one time.

Still another advantage of the present tacos is that even if taco breakage occurs along either connection between flat base and sidewall, the flat base and remaining sidewall forms a ledge minimizing loss of the added fillings to allow for consumption completion with reduced mess.

Also, another advantage of a taco made using the taco shell of the present invention may be presented for consumption in an upright and filled orientation.

Some low-level testing at dinner validated this premise. Soon afterward, Mrs. Usability was heard saying in a self-satisfied tone, “It’s about time.”

Mind Mapping

If you overlook the sensational title from Newsweek’s Mind Reading is Now Possible, there’s something worth pointing out here. Scientists are finding that thoughts and ideas map to predictable patterns in the brain.

Scientists at Carnegie Mellon University showed people drawings of five tools (hammer, drill and the like) and five dwellings (castle, igloo …) and asked them to think about each object’s properties, uses and anything else that came to mind. Meanwhile, fMRI measured activity throughout each volunteer’s brain. As the scientists report this month in the journal PLoS One, the activity pattern evoked by each object was so distinctive that the computer could tell with 78 percent accuracy when someone was thinking about a hammer and not, say, pliers. CMU neuroscientist Marcel Just thinks they can improve the accuracy (which reached 94 percent for one person) if people hold still in the fMRI and keep their thoughts from drifting to, say, lunch.

As always, the results have to be replicated by independent labs before they can be accepted. But this is the first time any mind-reading technique has achieved such specificity. Remarkably, the activity patterns—from visual areas to movement area to regions that encode abstract ideas like the feudal associations of a castle—were eerily similar from one person to another. “This establishes, as never before, that there is a commonality in how different people’s brains represent the same object,” said CMU’s Tom Mitchell.

If what your brain does when it thinks about an igloo is almost identical to what mine does, that suggests the possibility of a universal mind-reading dictionary, in which brain-activity pattern x means thought y in most people. It is not clear if that will be true for things more complicated that pliers and igloos, however. “The more detailed the thought is, the more different these patterns get, because different people have different associations for an object or idea,” says Haynes. “We’re much closer to this than we were two years ago, but still far from a universal mind-reading machine.”

Wireframes Left, Visual Designs Right

Thoughts on Interaction Design Deliverables

Eventually, I would like to share with you the design theory I’m working on (I may even have settled on a name for it), but for now allow me to explain a small part of it which at one point served as the theory’s main catalyst.

During my work as a user experience designer, I’ve become increasingly convinced that an interesting parallel exists between the two cerebral hemispheres of the human brain and two common deliverables associated with interaction design practices–specifically the development of low-fidelity wireframes into highly detailed visual designs (sometimes also referred to as visual comps or mock-ups).

This observation pronounces a fact that is usually assumed as a common goal among practitioners looking to build a strong user experience design team; find candidates who are well-rounded and possess strengths in analytical know-how and creative conceptualization.

It could be argued, as I’ll start doing now, that the need for this specialization is never more apparent during the life cycle of a design then at the transition point from wireframe (when the design is defined by boxes and mostly black and white text) to visual design (when the design is alive with color, graphics, and seductively shiny buttons, or other aesthetic elements). At this critical turning point, while the fundamental design goals still underly similar tensions, the designer(s) involved in defining and resolving these different artifacts often–although not always–derive their solutions from opposite ends of the cognitive playing field.

So, presumably then, if one is to design user experiences (or any product, such as cars, clothing, or computer animations, for that matter) by focusing wireframes into some other creatively articulated end result, it makes sense to be cognizant of how different operations get started within the brain.

Consider the widely known and somewhat diametrically opposed functions of the left and right brain hemispheres.

While these attributes may not have a one-to-one relationship with each deliverable on any design project, there should be enough cause to consider a somewhat clinical hypothesis–sensitivity to and explicit focus on left and right brain functions during the design process can serve to optimize certain aspects, if not design decisions, in a predictable fashion. After all, these elements are digested by a consumer in the same cognitive way once the design has become a product.

As best I can tell from my own experience and from working with others in the design industry, specific attributes which determine the ultimate success or failure of these deliverables fall along similarly opposite sides of the fence.

There are, of course, many other deliverables such as storyboards, as well as offshoots of other design methodologies that muddy the water of this split. Adaptive Path’s advocation of sketchboards is a good recent example. I’m not suggesting practitioners follow a rigid form of design by any means. I think communication formed in any artifact which tries to engage both sides of the brain simultaneously is a good practice and probably very necessary for certain kinds of problem solving or even within the confines of a given project.

I’m only observing that certain results are highly predictable and can serve to enhance design decision-making or touchpoints, if you will, within their optimal spaces because the very nature of human brain chemistry supports it.

By isolating functions performed almost exclusively within each of these deliverables a more relevant definition of design becomes apparent. It first takes on a rational form, which is adapted and synthesized into a final product. Examining this structure overall can amplify design decisions and help further delineate touchpoints within that assumed structure.

Learning Politics Through Design

CNN’s Election Center 2008 delivers not only a monumental amount of well thought out data-driven design, information architecture and Flash/AJAX wizardry, but the site itself may quite possibly represents the largest lesson in politics that’s ever been delivered to the American public in one full sitting.

Think about it.

Newspapers have tried in the past, but they’ve always been a day late and a dollar too much–not to mention totally degradable. Television, at the risk of being cliché, just reduces everything into meaningless sound bites. And radio can’t even come close to the the level of granularity needed to compare data as contained in multiple charts, graphs, and interactive widgets. While I’ve taken issue with the way CNN has egregiously presented visual data in the past, I think the job they’re doing with Election Center is for the most part exceptional.

Where else can you learn that Tom Hanks gave Barack Obama‘s campaign $4,600, while only giving Hilary Clinton $2,300? Or that the process of using delegates is completely different between parties. After digesting a good chunk of the visualized information on CNN, it’s become apparent to me that I still have a lot to learn about things I just assumed to know.

This kind of instructional reach should be especially encouraging to future generations. Ultimately, it’s their gain should they continue to consume and expand upon the Internet as it’s being used today. Because as they become more informed about the government through simple methods of user interaction and experience, they might also become inspired, if not empowered, into changing it one day.