Ready-to-hand Dean Eckles blogs on people and technology

TechCrunch and others have been joking about Apple’s rejection of an app because it uses shiny chat bubbles, which the Apple representative claimed were trademarked:

Chess Wars was being rejected after the six week wait [because] the bubbles in its chat rooms are too shiny, and Apple has trademarked that bubbly design. [...] The representative said Stump needed to make the bubbles “less shiny” and also helpfully suggested that he make the bubbles square, just to be sure.

One thing that is quite striking in this situation is that it is at odds with Apple’s long history of strongly encouraging third-party developers to follow many UI guidelines — guidelines that when followed make third-party apps blend in like they’re native.¹

It’s important to not read too much into this (especially since we don’t know what Apple’s more considered policy on this will end up being), but it is interesting to think about how responsibility gets spread around among mobile applications, services, and devices — and how this may be different than existing models on the desktop.My sense is that experienced desktop computer users understand at least the most important ways sources of their good and bad experiences are distinguished. For example, “locomotion” is a central metaphor in using the Web, as opposed to the conversation and manipulation metaphors of the command line / natural language interfaces and WIMP: we “go to” a site (see this interview with Terry Winograd, full .mov here). The locomotion metaphor helps people distinguish what my computer is contributing and what some distant, third-party “site” is contributing.

This is complex even on the Web, but many of these genre rules are currently being all mixed up. Google has Gmail running in your browser but on your computer. Cameraphones are recognizing objects you point them at — some by analyzing the image on the device and some by sending the device to a server to be analyzed.

This issue is sometimes identified by academics as one of source orientation and source equivocality. Though there has been some great research in this area, there is a lot we don’t know and the field is in flux: people’s beliefs about systems are changing and the important technologies and genres are still emerging.

If there’s one important place to start thinking about the craziness of the current situation of ubiquitous source equivocality is “Personalization of mass media and the growth of pseudo-community” (1987) by James Beniger that predates much of the tech at issue.

1. I was led to think this by a commenter on TechCrunch, Dan Grossman, pointing out this long history. [↩]

Is this etching a self-portrait by Leonardo da Vinci created hundreds of years ago? That’s what I was told by a Californian friend who had “gone native” in Florence. Another matter: is this, in fact, a commonly believed and shared legend, and what other variations are there on it?

I shared the story with some fellow visitors in Florence on a lunch-time return to the piazza. Ed Chi tried to verify the rumor using a Web search, but with no success.  At least in English, there didn’t seem to be much on this in the Web. (See my photo and comments on Flickr.)

I posted the photo on Flickr. I asked questions on LinkedIn and Yahoo! Answers, with no success. I also asked for help from workers on Mechanical Turk. Here’s part of how I asked for help:

There is a portrait etched in stone on the wall of Palazzo Vecchio in Piazza della Signoria in Florence (Firenza), Italy. It is close behind the copy of the David there. I have heard that there is a legend that this is a self-portrait by Leonardo da Vinci. I am looking for any information about this legend, alternate versions of the legend, or information about the real source of the portrait.

What results have been offered seem to suggest that this legend exists — though perhaps it is “actually” (at least as captured online, since perhaps the Leonardo theorists aren’t as active digital content creators) about Michelangelo:

• Palazzo Vecchio in Italian Wikipedia
• Florentine Legends: Fact or Fiction (in Italian)
• Curiosities in Florence

The best way of finding out seemed to actually be my Flickr photo itself, since that’s where Daniel Witting provided the first two links above — however, this was a few months after the photo was first posted to Flickr. Turkers provided a couple useful links also (”Curiosities” above) on a shorter schedule and with a higher price. (I should have also tried uClue — where many former Google Answers researchers now work. This was recommended by Max Harper, who has studied Q&A sites in detail.)

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Question and answer services along the lines of Yahoo! Answers rose to global (and U.S.) significance only after success in Korea, where Naver Knowledge iN pioneered the use of an online community to power a Q&A site. A major motivation Korea was the limited amount of Korean content online. With Naver’s offering, Korea’s Internet saavy, English population made information newly available in Korean (and did plenty of other interesting work).

This is as significant a motivation for Q&A sites by English-speaking folks in the U.S., but the present case is an exception.

Some of the questions that made this case interesting to me:

• What culturally-shared beliefs get manifest online? During this whole process, I and others wondered whether perhaps this local legend was only shared orally. It seems that it is represented online after all — at least the Michelangelo variant, but it could have been otherwise.
• How does the pair of languages a task requires knowledge of determine the processes, structres, and communities that are optimal for completing the task? For example, it seems quite important whether the target or source language has many more speakers than the other. (One could think about this simplistically in terms of conditional probabilities of skills with language A given skill with language B and vice verse.)

Mobile phones are gateways to our most important and enduring relationships with other people. But, like other communication technologies, the mobile phone is psychologically not only a medium: we also form enduring relationships with devices themselves and their  associated software and services (Sundar 2004). While different than  relationships with other people, these human–technology relationships are also importantly social relationships. People exhibit a host of automatic, social responses to interactive  technologies by applying familiar social rules, categories, and norms that are otherwise used in interacting with people (Reeves and Nass 1996; Nass and Moon 2000).

These human–technology relationships develop and endure over time and through radical changes in the situation. In particular, mobile phones are near-constant companions. They take on roles of both medium for communication with other people and independent interaction partner through dynamic physical, social, and cultural environments and tasks. The global phenomenon of mobile phone use highlights both that relationships with people and technologies are influenced by variable context and that these devices are, in some ways, a constant in amidst these everyday changes.

Situational variation and attribution

Situational variation is important for how people understand and interact with mobile technology. This variation is an input to the processes by which people disentangle the internal (personal or device) and external (situational) causes of an social entity’s behavior (Fiedler et al. 1999; Forsterling 1992; Kelley 1967), so this situational variation contributes to the traits and states attributed to human and technological entities. Furthermore, situational variation influences the relationship and interaction in other ways. For example, we have recently carried out an experiment providing evidence that this situational variation itself (rather than the characteristics of the situations) influences memory, creativity, and self-disclosure to a mobile service; in particular, people disclose more in places they have previously disclosed to the service, than in  new places (Sukumaran et al. 2009).

Not only does the situation vary, but mobile technologies are increasingly responsive to the environments they share with their human interactants. A system’s systematic and purposive responsiveness to the environment means means that explaining its behavior is about more than distinguishing internal and external causes: people explain behavior by attributing reasons to the entity, which may trivially either refer to internal or external causes. For example, contrast “Jack bought the house because it was secluded” (external) with “Jack bought the house because he wanted privacy” (internal) (Ross 1977, p. 176). Much research in the social cognition and attribution theory traditions of psychology has failed to address this richness of people’s everyday explanations of other ’s behavior (Malle 2004; McClure 2002), but contemporary, interdisciplinary work is elaborating on theories and methods from philosophy and developmental psychology to this end (e.g., the contributions to Malle et al. 2001).

These two developments — the increasing role of situational variation in human-technology relationships and a new appreciation of the richness of everyday explanations of behavior — are important to consider together in designing new research in human-computer interaction, psychology, and communication. Here are three suggestions about directions to pursue in light of this:

Design systems that provide constancy and support through radical situational changes in both the social and physical environment. For example, we have created a system that uses the voices of participants in an upcoming event as audio primes during transition periods (Sohn et al. 2009). This can help ease the transition from a long corporate meeting to a chat with fellow parents at a child’s soccer game.

Design experimental manipulations and measure based on features of folk psychology –  the implicit theory or capabilities by which we attribute, e.g., beliefs, thoughts, and desires (propositional attitudes) to others (Dennett 1987) — identified by philosophers. For example, attributions propositional attitudes (e.g., beliefs) to an entity have the linguistic feature that one cannot substitute different terms that refer to the same object while maintaining the truth or appropriateness of the statement. This opacity in attributions of propositional attitudes is the subject of a large literature (e.g., following Quine 1953), but this  has not been used as a lens for much empirical work, except for some developmental psychology  (e.g., Apperly and Robinson 2003). Human-computer interaction research should use this opacity (and other underused features of folk psychology) in studies of how people think about systems.

Connect work on mental models of systems (e.g., Kempton 1986; Norman 1988) to theories of social cognition and folk psychology. I think we can expect much larger overlap in the process involved than in the current research literature: people use folk psychology to understand, predict, and explain technological systems — not just other people.

References

Increasing valuable annotation behaviors was a practical end of a good deal of work at Yahoo! Research Berkeley. ZoneTag is a mobile application and service that suggests tags when users choose to upload a photo (to Flickr) based on their past tags, the relevant tags of others, and events and places nearby. Through social influence and removing barriers, these suggestions influence users to expand and consistently use their tagging vocabulary (Ahern et al. 2006).

Context-aware suggestion techniques such as those used in ZoneTag can increase tagging, but what about users’ motivations for considering tagging in the first place? And how can these motivations for annotation be considered in designing services that involve annotation? In this post, I consider existing work on motivations for tagging, and I use tagging on Facebook as an example of how multiple motivations can combine to increase desired annotation behaviors.

Using photo-elicitation interviews with ZoneTag users who tag, Ames & Naaman (2007) present a two factor taxonomy of motivations for tagging. First, they categorize tagging motivations by function: is the motivating function of the tagging organizational or communicative? Organizational functions include supporting search, presenting photos by event, etc., while communicative functions include when tags provide information about the photos, their content, or are otherwise part of a communication (e.g., telling a joke). Second, they categorize tagging motivations by intended audience (or sociality): are the tags intended for my future self, people known to me (friends, family, coworkers, online contacts), or the general public?

Taxonomy of motivations for tagging from Ames & Naaman

On Flickr the function dimension generally maps onto the distinction between functionality that enables and is prior to arriving at the given photo or photos (organization) and functionality applicable once one is viewing a photo (communication). For example, I can find a photo (by me or someone else) by searching for a person’s name, and then use other tags applied to that photo to jog my memory of what event the photo was taken at.

Some Flickr users subscribe to RSS feeds for public photos tagged with their name, making for a communication function of tagging — particularly tagging of people in media — that is prior to “arriving” at a specific media object. These are generally techie power users, but this can matter for others. Some less techie participants in our studies reported noticing that their friends did this — so they became aware of tagging those friends’ names as a communicative act that would result in the friends finding the tagged photos.

This kind of function of tagging people is executed more generally — and for more than just techie power users — by Facebook. In tagging of photos, videos, and blog posts, tagging a person notifies them they have been tagged, and can add that they have been tagged to their friends’ News Feeds. This function has received a lot of attention from a privacy perspective (and it should). But I think it hints at the promise of making annotation behavior fulfill more of these functions simultaneously. When specifying content can also be used to specify recipients, annotation becomes an important trigger for communication.

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See some interesting comments (from Twitter) about tagging on Facebook:

• noticing people tagging to gain eyeballs
• exhorting others not to tag bad photos (and thanks)
• collapsing time by tagging photos from long ago
• tagging by parents

(Also see Facebook’s growing use and testing of autotagging [1, 2].)

References

At the Social Media Workshop, Katarina Segerståhl presented her on-going work on what she has termed extended information services or distributed user experiences — human-computer interactions that span multiple and heterogeneous devices (Segerståhl & Oinas-Kukkonen 2007). As a central example, she studies a persuasive technology service for planning, logging, reviewing, and motivating exercise: these parts of the experience are distributed across the user’s PC, mobile phone, and heart rate monitor.

In one interesting observation, Segerståhl notes that the specific user interfaces on one device can be helpful mental images even when a different device is in use: participants reported picturing their workout plan as it appeared on their laptop and using it to guide their actions during their workout, during which the obvious, physically present interface with the service was the heart rate monitor, not the earlier planning visualization. Her second focus is how to make these user experiences coherent, with clear practical applications in usability and user experience design (e.g., how can designers make the interfaces both appropriately consistent and differentiated?).

In this post, I want to connect this very interesting and relevant work with some other research at the historical and theoretical center of persuasive technology: source orientation in human-computer interaction. First, I’ll relate source orientation to the history and intellectual context of persuasive technology. Then I’ll consider how multi-device and multi-context interactions complicate source orientation.

Source orientation, social responses, and persuasive technology

As an incoming Ph.D. student at Stanford University, B.J. Fogg already had the goal of improving generalizable knowledge about how interactive technologies can change attitudes and behaviors by design. His previous graduate studies in rhetoric and literary criticism had given him understanding of one family of academic approaches to persuasion. And in running a newspaper and consulting on many document design (Schriver 1997) projects, the challenges and opportunities of designing for persuasion were to him clearly both practical and intellectually exciting.

The ongoing research of Profs. Clifford Nass and Byron Reeves attracted Fogg to Stanford to investigate just this. Nass and Reeves were studying people’s mindless social responses to information and communication technologies. Cliff Nass’s research program — called Computers as (or are) Social Actors (CASA) — was obviously relevant: if people treat computers socially, this “opens the door for computers to apply [...] social influence” to change attitudes and behaviors (Fogg 2002, p. 90). While clearly working within this program, Fogg focused on showing behavioral evidence of these responses (e.g., Fogg & Nass 1997): both because of the reliability of these measures and the standing of behavior change as a goal of practitioners.

Source orientation is central to the CASA research program — and the larger program Nass shared with Reeves. Underlying people’s mindless social responses to communication technologies is the fact that they often orient towards a proximal source rather than a distal one — even when under reflective consideration this does not make sense: people treat the box in front of them (a computer) as the source of information, rather than a (spatially and temporally) distant programmer or content creator. That is, their source orientation may not match the most relevant common cause of the the information. This means that features of the proximal source unduly influence e.g. the credibility of information presented or the effectiveness of attempts at behavior change.

For example, people will reciprocate with a particular computer if it is helpful, but not the same model running the same program right next to it (Fogg & Nass 1997, Moon 2000). Rather than orienting to the more distal program (or programmer), they orient to the box.¹

Multiple devices, Internet services, and unstable context

These source orientation effects have been repeatedly demonstrated by controlled laboratory experiments (for reviews, see Nass & Moon 2000, Sundar & Nass 2000), but this research has largely focused on interactions that do not involve multiple devices, Internet services, or use in changing contexts. How is source orientation different in human-computer interactions that have these features?

This question is of increasing practical importance because these interactions now make up a large part of our interactions with computers. If we want to describe, predict, and design for how people use computers everyday — checking their Facebook feed on their laptop and mobile phone, installing Google Desktop Search and dialing into Google 411, or taking photos with their Nokia phone and uploading them to Nokia’s Ovi Share — then we should test, extend, and/or modify our understanding of source orientation. So this topic matters for major corporations and their closely guarded brands.

So why should we expect that multiple devices, Internet services, and changing contexts of use will matter so much for source orientation? After having explained the theory and evidence above, this may already be somewhat clear, so I offer some suggestive questions.

1. If much of the experience (e.g. brand, visual style, on-screen agent) is consistent across these changes, how much will the effects of characteristics of the proximal source — the devices and contexts — be reduced?
2. What happens when the proximal device could be mindfully treated as a source (e.g., it makes its own contribution to the interaction), but so does a distance source (e.g., a server)? This could be especially interesting with different branding combination between the two (e.g., the device and service are both from Apple, or the device is from HTC and service is from Google).
3. What if the visual style or manifestation of the distal source varies substantially with the device used, perhaps taking on a style consistent with the device? This can already happen with SMS-based services, mobile Java applications, and voice agents that help you access distant media and services.

References

1. This actually is subject to a good deal of cross-cultural variation. Similar experiments with Japanese — rather than American — participants show reciprocity to groups of computers, rather than just individuals (Katagiri et al.) [↩]