Designing the Democratic

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The role of the information architect (IA), interaction designer, or user experience (UX) designer is to help create architecture and interactions which will impact the user in constructive, meaningful ways. Sometimes the design choices are strategic and affect a broad interaction environment; other times they may be tactical and detailed, affecting few. But sometimes the design choices we make are not good enough for the users we’re trying to reach. Often a sense of democratic responsibility is missing in the artifacts and experiences which result from our designs and decisions.

Noted scholar on democracy James Banks simplifies its definition: democracy means rule by the people.1 Philosopher and pragmatist John Dewey, however, interprets democracy more deeply as a way of living together as well as a kind of government.2 A “way of living together,” in our evolving globalization, means one or more different cultures in contact and interacting. Though this interaction across and between cultures has always existed to a greater or lesser degree, technology enables a historically unequaled degree of such interaction.

Whether it’s clearly recognized cultures interacting (i.e., the business practices between an Australian firm and a Chinese corporation), or less obvious subcultures interacting with a dominant culture (yuppies, castes, etc.), every member is entitled to democratic representation within the user experience. This means acknowledgement of, respect for, and empowerment regarding cultural dynamics of those for whom we design. Users may be of diverse cultures categorized by social class, gender, sexual orientation, religion, ethnic identity, age, racial group, industry, language, ableness, political power and control, and technological capability to name a few.  

I’d like to discuss several elements of democratic responsibility we might have some control over, touching briefly on potentially deeper implications for the design decisions we make. It’s folly to try to establish a canon of best practices in this regard because each of us is informed by a unique roster of experiences—personal, professional, and cultural—when making decisions that influence the user experience. Instead, I am suggesting that we get in the habit of reflecting on our decisions with special attention to the degree to which we are meeting our democratic responsibility.

One-way Design

The most common type of user experience occurs when a user interacts with artifacts in an onscreen ecosystem authored by someone else. Online shopping, music downloads, and rich internet applications are easy examples.

For this type of user experience, generally speaking, designing toward a democratic responsibility is under the control of the design and development team. They are in charge of the content, language and tone, visuals and layout, database management, and all the other aspects of making an end product. Whatever this team comes up with is what the user experiences. So, in addition to the regular tenets of information architecture and design we practice, careful thought about the cultural dynamics of the users is another necessary level of responsibility.

One thing we can do, particularly during the early stages of the design and development cycle, is to recognize the influence of our own culture on our methods, standards, practices, and expectations. Because  a great deal of the computer technology used today was standardized by American and Western European cultures, those of us from those cultures may take for granted many things that make their way into the onscreen ecosystem: feedback style, metaphors, icons, business processes, decision-making, the semantics of buttons or functions, problem solving, aesthetics, image use, etc. Hegemony of these dominant features within most aspects of the technology potentially leads to ineffectiveness ranging from confusion to offense in members of other cultures. To put it in IA-speak, the right information stops getting to the right people at the right time.

By being aware of our own cultural proclivities, we can reflect on our influences and how they may be at odds with those of other cultures. Then we can architect a more democratically responsible user experience. To not do this, particularly for cultures dominant in computing technology, becomes a form of technological imperialism where some users “remain at the mercy of other people’s decisions.”3 Some even consider this a sort of ethical imperialism based on one’s culture dictating what is “good” and “bad” and what “ought to be good.”4 For example, the presence or absence of certain navigation elements on an e-commerce site may inadvertently validate participation by one demographic while disregarding the needs of another. It’s imperialism with modern resources, imperialism in the form of business practices and popular culture imposed on those with less power.5

This has more serious implications as emerging countries struggle to participate in the global marketplace. For example, bandwidth-heavy interactions defeat the helpful intentions between the United States and Kenya as the US tries to share information with medical institutions there.6 What message is this sending to Kenyans and how does it affect their experience? What can IAs and designers do to maintain the integrity of the interaction and content while at the same time accommodating Kenya’s infrastructure?

Representing multiple cultures in an online environment is a challenge, and doing it poorly risks the participation by one or more groups. At best, you might lose them; at worst, you could marginalize or alienate them. For example, the wording of a survey or a form may perpetuate stereotypes, unintentionally convey an agenda, or reinforce control of one group over another. Or persuasion links may impact interaction patterns by other-culture users in unexpected ways, resulting in incomplete communication or lost revenue. For example, because of cultural influences on their mental modeling or on the perceived value of using technology, members of a given group may not understand the organization of a taxonomy you’ve instituted; it can be tricky to establish paths or processes so that users from differing societies can get to crucial features or pages.

Interaction patterns and hierarchy in rich internet applications may be another trouble spot. Because usage patterns, priorities, and functions differ from culture to culture, naturally these differences would need to be reflected or acknowledged onscreen. Users in some cultures may not yet understand the newer interface metaphors of sliders, accordion panels, and other manipulatives. Or they may need to control and organize information in ways that are meaningful to them but have not been considered by the designers and developers. For example, some cultures think contextually, others in a linear fashion. For the IA in this case, integrating a task list function and a calendar suddenly requires deeper cultural consideration.

There will always be instances when there is no choice but to make a design decision which favors one culture over another. But we must make the effort to reflect on the implications of our choices in the hope of coming up with a solution that will result in a positive user experience. How will design decisions affect the function or the business goal for other cultures? How will they affect the meaning of the experience for targeted users?

A good illustration, based more on experience design than IA, is modern coffee makers which may alienate an older demographic (subculture). These devices are often confounding because they rely on assumed knowledge of digital programming and a button-click interaction. How does it feel when you want coffee and have no choice but to interact with a device you don’t understand? Instead of feeling empowered or respected, you’re more likely to feel discounted and helpless. It should be a simple task—running hot water over ground coffee beans—but instead it becomes complex and defeating for that group of users.

Social Media

The need for another kind of democratic responsibility emerges as the use of technology evolves. Social media, commonly labeled Web 2.0, is a stage for users to both obtain and supply content for the interaction or technology space. Examples of such collaboration and information sharing include wikis, social networking sites, folksonomies, and shared databases. How can the characteristics of social networking and Web 2.0 bolster democracy? How can they hinder it?

Nielsen says that online networks that rely on users to contribute content suffer from a participation inequality—most users don’t participate very much.7 They use the site in a traditional “one-way” fashion. Based on statistics which mirror Zipf’s law,8 he has developed a rule he calls the 90-9-1 rule:

  • 90% of users read or observe, but don’t contribute
  • 9% of users contribute from time to time
  • 1% of users participate a lot and account for most contributions

For example, Wikipedia sometimes draws heat because a relative few are contributing a relative majority of the work. (For Wikipedia, the stats suggest that 1% of the users author 50% of the content.)

For as much as social media sites put power in the hands of the people, or crowdsourcing, it can mean an opportunity for revisionist interpretations of history, people, accomplishments, etc. Or, less diabolically, if only certain groups of people contribute, they “out-voice” others and the content becomes unintentionally biased. Users from a technologically emerging nation, for instance, may be at a particular disadvantage because they do not understand the benefits of social networking or how to effectively contribute. Or because of social mores they may not feel comfortable making contributions which become public. As a result, for example, information about one’s own country might be contributed by a foreign visitor who doesn’t have the insight of a native.

Another aspect of social media is the visual elements within a participatory ecosystem. The graphics and visualizations themselves become artifacts with social appeal, impacting the subsequent direction of participation.9 These visualizations might support personal or group identities (encouraging robust participation), they might be relatively neutral, or they might marginalize or ostracize certain people or groups (i.e., the visuals may be defamatory, perhaps inaccurate or manipulative, or they may not be understood by certain groups).

In all cases, social media begs for democratic responsibility from those who are given power to influence that technological environment. As a solution, Chris Wilson suggests we move from “wisdom of the crowds” to “wisdom of the chaperones.”10 This means practicing stewardship and offering principles to guide those contributing to social media. Again, there is no set of rules for accomplishing this. Each social media space is unique in context and requires its own examination to establish a democratic responsibility. In fact, it may be up to us to recommend that a social media setting is not appropriate. Perhaps cultural aspects of the user base mean that some things are better placed in a one-way ecosystem instead of in a participatory setting.


As IAs and UX designers, it’s important to convey the meaningfulness and relevance of democratic responsibility to other cultures or those in developing countries. Sometimes it may seem like we are making more work for ourselves or working to a low common denominator (like the connection to the Kenyan medical institutions). But by demonstrating these qualities with the technology, we encourage an evolving participation which ultimately raises standards. Or the result may be ambassadorial efforts which further the mutuality between two or more culturally diverse populations—a responsiveness which is necessary for healthy globalization. Perhaps the onus is on the more technologically advanced societies to model this democratic responsibility so technologically emerging cultures will more easily understand the value of it as they grow.

Marshall McLuhan’s idea of the Global Village involves the profound impact of information technology on the development of complex relationships within and between cultures. But in order to understand another culture, we must understand our own. In our respective disciplines, we make design decisions based on context, so it’s not hard to see how we can make democratically responsible design decisions relative to the contextual understanding of culture.

The habit of reflecting on the choices and recommendations we make is a big step in the right direction. Designing requires a balance of reason and intuition, an impetus to act, and an ability to reflect on actions taken.11 It is reflection we undertake conscientiously that makes us good IAs, good designers…and good citizens.


[1] Banks, J. A., Banks, C. A. M., Cortés, C. E., Hahn, C. L., Merryfield, M. M., Moodley, K. A., et al. (2004). Democracy and diversity: Principles and concepts for educating citizens in a global age. Seattle: University of Washington, Center for Multicultural Education, College of Education, 17.

[2] Dewey, J. (1961). Democracy and education. New York: Macmillan. (Original work published 1916.)

[3] Nielsen, J. (2006). The digital divide: the three stages. Alertbox, 20 Nov. 2006

[4] Martin, J. N., & Nakayama, T. K. (2000). Intercultural communication in context (2nded.). Mountain View, CA: Mayfield Publishing Co.

[5] See Banks, Democracy and diversity: Principles and concepts for educating citizens in a global age, 20.

[6] Kirch, D. G. (2008). Supporting a culture of collaboration across professional medicine. MedBiquitous Annual conference, 13-15 May 2008. Baltimore, MD.

[7] Nielsen, J. (2006). Participation inequality: encouraging more users to contribute. Alertbox, 9 Oct. 2006

[8] Zipf’s Law. (n.d.). Retrieved May 12, 2008 from

[9] Viégas, F. & Wattenberg, M. (2008). Many eyes, democratizing visualization. PARC Forum, Jan 31, 2008

[10] Wilson, C. (2008). The wisdom of the chaperones; Digg, Wikipedia and the myth of Web 2.0 democracy. Slate.

[11] Rowland, G. (1993). Designing and instructional design. Educational technology research and development, 41(1). 79-91.


Cues, The Golden Retriever

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In every waking moment, our brains are processing the stimuli in our environment and responding, consciously and unconsciously, to what is going on around us. This may mean something simple like stopping automatically at a crosswalk based on the color of the traffic signal. Or it may mean something more deliberate, like deciding to turn left after orienting yourself by reading a street sign.

Both consciously and unconsciously, we also make decisions while interacting in an onscreen environment. We move automatically during routine tasks and through familiar interfaces. But what do we do when the interaction onscreen requires a very deliberate and thoughtful interaction—how do we determine the correct response to the stimulus? We need cues to help us draw from our experience and carry out an acceptable response. Cues are like little cognitive helper elves who prompt us toward a suitable interaction, reminding us of what goes where, when, and how. Cues can be singular reminders, like a string tied around your finger, or they can be contextual reminders, like remembering that you also need carrots when you are shopping for potatoes and onions in a supermarket.

When we’re arranging content and designing interactions for the onscreen environment, providing cues for users helps them interact more effectively and productively. Increased customer satisfaction, job performance, e-commerce, safety, and cognitive efficacy rely on deliberate interaction with the technology and thus easily benefit from the smart use of cues.

I’d like to frame a discussion of cues by touching on a mixture of topics including memory, a few theories from cognitive psychology, and multimedia research. It may get a little dry, but stick with me. The integration of these three areas not only affects how information is encoded and retrieved, it influences how and when cues might best be used.

Remembering Memory

Let’s refresh your memory on the topic of memory—stuff you probably already know. This is the foundation of how and why cuing is effective.

First, there’s the idea of encoding and retrieval (or recall). Encoding is converting information into a form usable in memory. And we tend to encode only as much information as we need to know. This is a safety valve for over-stimulation of the senses as well as a way of filtering out what we don’t need for later retrieval. Retrieval is bringing to mind for specific use a piece of information already encoded and stored in memory.

Memory is generally labeled long-term memory and short-term memory (or working memory, in cognitive psychology parlance). Our working memory holds a small amount of information for about 20 seconds for the purpose of manipulation—deciding what to do with sensory input from one’s environment or with an item of information recently retrieved from long-term memory. The familiar rule is that humans have the capacity to hold seven items (plus or minus two) in working memory. In contrast, long-term memory is considered limitless and information is stored there indefinitely. Information from working memory has the potential to become stored in long-term memory.

The Integration of Multimedia and Memory

Ingredient 1
By its nature, interaction in an onscreen environment can be considered multimedia. At the very least, visual elements (images, application windows, the cursor, etc.) are combined with verbal elements (semiotics, language, aural narration, etc). These are called modalities and they are processed differently in the human mind using different neurological channels: this process is called dual coding and it’s when images and words create separate representations for themselves in the brain[3]. This is important because cues unique to a given modality can be used to better retrieve information originally processed with that modality. For example, color coding the shapes of the states on a map as red or blue helps us store for later recall the political leanings of a given state—the shape of the state triggers our remembering the color.

In a “real world” environment, stimuli from the visual and verbal modalities (among others) guide the way we interact with that environment—influencing our working memory and long-term memory. These stimuli can get to be a lot of work for the little grey cells and it helps when the two modalities share the load—the cognitive load—of processing information. The same is true for the onscreen environment as well.

Ingredient 2
Cognitive load[1] describes the tasks imposed on working memory by information or stimuli from the environment, in our case the onscreen environment. How much information can be retained in working memory—how much can we encode before our working memory is full and new information has no place to go? And if it escapes working memory, chances are slim that the information will make it into long-term memory.

So what happens when a modality is limited by cognitive load? In short, the working memory gets full fast. Encoding, cuing, and retrieval are affected. The interaction onscreen impacts the encoding necessary for later recall, particularly when different modalities are vying for attention. A limited working memory makes it difficult to absorb multiple modes of information simultaneously[2].

But if the modalities compliment one another, more information can be processed when they work in tandem than would be possible using a single modality. A large body of research exploring the use of multimedia and computers yields a couple of useful general guidelines:

  1. When presenting information onscreen, text and visuals are not as effective as seeing visuals and hearing narration.
  2. If text is the chosen way to convey verbal information, it should be in close proximity to the visual element it is related to (like labels on a map).

A big no-no is narration which is redundant to the text visible onscreen. This is a bad practice because the brain works too hard mediating continuity between the two cognitive channels; the reader is distracted from the content because of the mechanics of constant comparison of text and voice. It actually detracts from successful encoding. Naturally, if the encoding is faulty any use of cues used for later recall of that information is compromised.


Okay, now let’s look at cuing a bit more closely. The idea of cues and cuing is a theory more formally known as encoding specificity by its pioneer Endel Tulving. Memories are retrieved from long-term memory by means of retrieval cues; a large number of memories are stored in the brain and are not currently active, but a key word or visual element might instantly call up a specific memory from storage. In addition, the most effective retrieval cues are those stimuli stored concurrently with the memory of the experience itself[5]. (This implies that most cues are external to the individual and we’ll accept this characteristic for the sake of this discussion.) Citing a popular example, the words “amusement park” might not serve to retrieve your memory of a trip to Disneyland because during your visit you didn’t specifically think of it as an amusement park. You simply thought of it as “Disneyland.” So the word “Disneyland” is the cue that retrieves the appropriate gleeful memory from all the other memories warehoused in your brain.

It’s important to note two chief categories of cues—discrete or contextual. In other words, it may be that a user is being asked to respond directly to an onscreen prompt, or she may be interacting with the technology in a certain way because of the elements present in her onscreen setting. Most of us are probably familiar with the Visio interface and can recognize it instantly. When we’re working in it, we automatically use its features without thinking about the act of using its features. When concentrating on a project, we grab an item from a stencil, move it onto the workspace, size it, label it, etc. We don’t use Visio to try to re-sample a photograph’s resolution or check a hospital patient’s vital signs—we “remember” that Visio is capable of certain functionality because of the cues surrounding us in the Visio environment. This is an example of contextual cuing.

Reminiscing about Disneyland is one thing, but some tasks and interactions require more cognitive load to complete and the cues should be employed appropriately. For example, onscreen controls for a large piece of machinery, one which is dangerous when used incorrectly, require an operator’s focused attention. Cues provided in such an onscreen environment need to be deliberate and explicit. For example, a large red stop sign icon appears onscreen to warn the operator that he has forgotten a safety procedure.

External cues such as work environment, physical position, or teaming around a table may also affect interaction onscreen. If we anticipate the physical environment in our designs, we can control the cues onscreen to accommodate the users in that environment. In our large machinery example, perhaps onscreen cues are related to observing its movement or the sounds it makes. Or if crucial interaction needs to take place in a busy or noisy environment, like punching your numbers into an ATM, discrete and/or contextual cues which accommodate that external environment appear onscreen.

Cues also need to be salient and germane—they need to have meaning and relevance appropriate for the situation, task, or environment. They need to fit into the schema[4] of the interaction. Schema can also be regarded as a semantic network[6], where information is held in networks of interlinking concepts; it’s linked to related things that have meaning to us. Tim Berners-Lee says “a piece of information is really defined only by what it’s related to, and how it’s related.” So naturally the cue that recalls such a piece of information will need to be related to it, too.

The use of meaningful cues is tied to how memory functions. Memory is bolstered when its meaning is more firmly established by linking it to related things. This is because it’s less work for the short-term memory to plug new information into an existing schema: if the new information is encoded relative to its context, the cue that retrieves the information should also be related to that context. A rather glib example might be memorizing several new varieties of wine using colored grape icons to represent different flavors. When recalling those wines, cues in the form of smiling farm animals would do no good in helping you select a wine that goes well with spaghetti.

Humans are fallible, though, and sometimes even the best thought-out cues may not be effective. For example, if the context or subject matter is unfamiliar, cues which rely on it will not be helpful. In fact, sometimes the context is so unfamiliar that cues are not recognized for what they are; if information is not recognized as relevant or meaningful, it will be disregarded. People are better at recalling information that fits into their own existing schemas. There’s a semantic network unique to each of us. Fortunately, Tulving (1974) assures us, “even when retrieval of a target event in the presence of the most ‘obvious’ cue fails, there may be other cues that will provide access to the stored information” (p. 75). One preventative measure against designing ineffective cues is a thorough usability study. Or we may provide cues that address more than one modality. Each situation is as unique as its context, so it’s not possible to make recommendations here; the issue of ineffective cues can arise and it is important for us to acknowledge the risk (and any potential fallout!).

One general prescription for the symptom of ineffective cues is to provide the cue immediately before the desired recall, either immediately preceding interaction or positioned near the recall artifact (e.g., password field or bank account number field). In other words, cues need to prime the information they are designed to help retrieve. Another strategic method of cuing is pattern completion—the ability to recall complete memory from partial cues. The simple act of grouping items may be a sufficient retrieval cue. It may even help establish a context or schema for the user, thus increasing the subsequent effectiveness of your cuing system.

Related form and function in the onscreen environment can also act as cues. Context dependent menus are a perfect example of this, like the grouping of drawing tools in Word. The four-sided icon represents the function for drawing boxes. The same icon indicates very different functions in other Word tool palettes (or in other applications)—the user doesn’t have to remember exactly what each of the four-sided icons does: their context is the cue for reminding the user of their function. An easy text-based example might be placing an arts festival event with an ambiguous title in the same column onscreen that lists similar events.

Jason Withrow’s B&A article Cognitive Psychology & IA: From Theory to Practice explores this idea in greater detail.

Another cuing strategy is one mentioned above in passing, the use of mixed-modality cues. This strategy draws on the advantages of splitting the cognitive load between two encoding systems.2 , 3 Cues for one modality can be presented in another modality if the original encoding matches that set-up (i.e., an image-text mix is the cue for recall of the same image-text mix). A perfect example is discussed in Ross Howard’s article on what he terms ambient signifiers. Audio is piped over the PA of a large transportation network. Each train station in a large city has a unique audio melody associated with it. As Howard points out, not only is the destination station’s audio a cue to get off the train, the commuters memorize the melody for the station prior to their destination, priming them for their actual destination. This is an interesting example because it also takes into account the environment in which the stimulus-response cue is introduced. With preoccupied or bored daily commuters crowding onto a train stopping at homogenous-looking stations, what cues might help them successfully get home? The computer game Myst used a similar technique by using sound cues to help the intrepid player solve puzzles.

But what happens when elements of the onscreen environment are really similar (or ubiquitous)? Our brains err toward efficiency: events and elements that are similar are generally encoded in terms of their common features rather than their distinctive characteristics. This is great for helping us fold new information into existing schemas and contexts. But it interferes when the IAs and designers need the user to distinguish between the similar events or elements. This situation is described in the interference theory, which states that the greater the similarity between two events, the greater the risk of interference. So it becomes a balancing act: maintain continuity across the interactive environment while at the same time establish a distinction between elements you want the user to retain. Something as simple as color-coding might be a means of distinguishing information onscreen. Position may be another. Think of a process being taught or conveyed on a training website, a process whose stages have big bold numbers respectively highlighted across the top or side of an interface. Not only does this help with chunking (breaking the information into digestible bits to avoid an unreasonable cognitive load), but when enacting the process later, like on a factory floor, it’s easier to visualize the numbers and remember the correct procedure.

Two notable phenomenon are related to using position onscreen as a cuing strategy. Primacy effect is the increased tendency to recall information committed to memory first and recency effect allows that items memorized last are also easier to recall. This may influence how the information is organized on a web page and how the cues might be used. (By the way, recency items fade sooner than do primacy items). One example might be a corporate intranet website with crucial information buried in a feature article. If you place that information in a single sentence synopsis at the top of the home page, you may plant the important points more permanently than forcing the readers to sift through the longer article. Any cues related to that information will likely be more effective.

Philosophy from 10,000 Feet Up

There’s a Chinese proverb that says “the palest ink is better than the sharpest memory.” I include this proverb because the palest ink serves as metaphor for how even the most understated of cues employed in an onscreen environment can be an effective recall or feedback strategy. And this strategy nurtures the perception that the computing technology is in concord with what is natural for the human user.

It’s been encouraging to watch the evolution of computing technology move away from forcing the human user to adapt to its form, function, architecture, and singularity. The continued momentum toward a more human-centered, ubiquitous interaction environment is encouraging. Humans are very dependent on the dynamics of stimulus-response cues in their natural environment; it’s important to establish a similar dynamic as we take part in designing interaction within their technological environment. The conscientious use of cues is not a panacea, of course. Because the use of cues onscreen mirrors the common stimulus-response paradigm which humans are used to in the natural world, however, it’s one of the more effective tools we can use when we design interactions.


fn1. Sweller, J., & Chandler, P. (1994). “Why some material is difficult to learn.” Cognition and Instruction 12(3): 185-233.

fn2. Mayer, R. E., & Moreno, R. (2003). “Nine Ways to Reduce Cognitive Load in Multimedia Learning.” Educational Psychologist 38(1): 43-52.

fn3. Paivio, A. (1986). “Dual coding theory.” Mental representations; a dual coding approach. New York, Oxford University Press: 53-83.

fn4. Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals and understanding; An inquiry into human knowledge structures. Hillsdale, NJ, Lawrence Erlbaum Associates.

fn5. Tulving, E. (1974). “Cue-dependent forgetting.” American Scientist 62(1): 74-82.

fn6. Collins, A. M., & Quillian, M. R. (2004). “The structure of semantic memory.” In Douglass Mook (ed.) Classic experiments in psychology. Westport, Conn.: Greenwood Press: 209-216.