Ready-to-hand Dean Eckles on people, technology & inference

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

Every person who logs into Facebook is met with the same interface but with personalized content. This interface is News Feed, which lists “news stories” generated by users’ Facebook friend. These news stories include the breaking news that Andrew was just tagged in a photo, that Neema declared he is a fan of a particular corporation, that Ellen joined a group expressing support for a charity, and that Alan says, “currently enjoying an iced coffee… anyone want to see a movie tonight?”

News Feed is an example of a particular design pattern that has recently become quite common – the activity stream. An activity stream aggregates actions of a set of individuals – such as a person’s egocentric social network – and displays the recent and/or interesting ones.

I’ve previously analysed, in a more fine-grained analysis of a particular (and now changed) interface element for setting one’s Facebook status message, how activity streams bias our beliefs about the frequency of others’ participation on social network services (SNSs). It works like this:

• We use availability to mind as a heuristic for estimating probability and frequency (Kahneman & Tversky, 1973). So if it is easier to think of a possibility, we judge it to be more likely or frequent. This heuristic is often helpful, but it also leads to bias due to, e.g., recent experience, search strategy (compare thinking of words starting with ‘r’ versus words with ‘r’ as the third letter).
• Activity streams show a recent subset of the activity available (think for now of a simple activity stream, like that on one’s Twitter home page).
• Activity streams show activity that is more likely to be interesting and is more likely to have comments on it.

Through the availability heuristic (and other mechanisms) this leads to one to estimate that (1) people in one’s egocentric network are generating activity on Facebook more frequently than they actually are and (2) stories with particular characteristics (e.g., comments on them) are more (or less) common in one’s egocentric network than they actually are.

Personalized cultivation

When thinking about this in the larger picture, one can see this as a kind of cultivation effect of algorithmic selection processes in interpersonal media. According to cultivation theory (see Williams, 2006, for an application to MMORGs), our long-term exposure to media makes leads us to see the real world through the lens of the media world; this exposure gradually results in beliefs about the world based on the systematic distortions of the media world (Gerbner et al., 1980). For example, heavy television viewing predicts giving more “television world” answers to questions — overestimating the frequency of men working in law enforcement and the probability of experiencing violent acts. A critical difference here is that with activity streams, similar cultivation can occur with regard to our local social and cultural neighborhood.

Aims of personalization

Automated personalization has traditionally focused on optimizing for relevance – keep users looking, get them clicking for more information, and make them participate related to this relevant content. But the considerations here highlight another goal of personalization: personalization for strategic influence on attitudes that matter for participation. These goals can be in tension. For example, should the system present…

The most interesting and relevant photos to a user?

Showing photographs from a user’s network that have many views and comments may result in showing photos that are very interesting to the user. However, seeing these photos can lead to inaccurate beliefs about how common different kinds of photos are (for example, overestimating the frequency of high-quality, artistic photos and underestimating the frequency of “poor-quality” cameraphone photos). This can discourage participation through perceptions of the norms for the network or the community.

On the other hand, seeing photos with so many comments or views may lead to overestimating how many comments one is likely to get on one’s own photo; this can result in disappointment following participation.

Activity from a user’s closest friends?

Assume that activity from close friends is more likely to be relevant and interesting. It might even be more likely to prompt participation, particularly in the form of comments and replies. But it can also bias judgments of likely audience: all those people I don’t know so well are harder to bring to mind as is, but if they don’t appear much in the activity stream for my network, I’m less likely to consider them when creating my content. This could lead to greater self-disclosure, bad privacy experiences, poor identity management, and eventual reduction in participation.

References

Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1980). The “Mainstreaming” of America: Violence Profile No. 11. Journal of Communication, 30(3), 10-29.

Kahneman, D., & Tversky, A. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5, 207-232.

Williams, D. (2006). Virtual Cultivation: Online Worlds, Offline Perceptions. Journal of Communication, 56, 69-87.

Today I’m attending the Social Mobile Media Workshop at Stanford University. It’s organized by researchers from Stanford’s HStar, Tampere University of Technology, and the Naval Postgraduate School. What follows is some still jagged thoughts that were prompted by the presentation this morning, rather than a straightforward account of the presentations.¹

A big theme of the workshop this morning has been transitions among production and consumption — and the critical role of annotations and context-awareness in enabling many of the user experiences discussed. In many ways, this workshop took me back to thinking about mobile media sharing, which was at the center of a good deal of my previous work. At Yahoo! Research Berkeley we were informed by Marc Davis’s vision of enabling “the billions of daily media consumers to become daily media producers.” With ZoneTag we used context-awareness, sociality, and simplicity to influence people to create, annotate, and share photos from their mobile phones (Ahern et al. 2006, 2007).

Enabling and encouraging these behaviors (for all media types) remains a major goal for designers of participatory media; and this was explicit at several points throughout the workshop (e.g., in Teppo Raisanen’s broad presentation on persuasive technology). This morning there was discussion about the technical requirements for consuming, capturing, and sending media. Cases that traditionally seem to strictly structure and separate production and consumption may be (1) in need of revision and increased flexibility or (2) actually already involve production and consumption together through existing tools. Media production to be part of a two-way communication, it must be consumed, whether by peers or the traditional producers.

As an example of the first case, Sarah Lewis (Stanford) highlighted the importance of making distance learning experiences reciprocal, rather than enforcing an asymmetry in what media types can be shared by different participants. In a past distance learning situation focused on the African ecosystem, it was frustrating that video was only shared from the participants at Stanford to participants at African colleges — leaving the latter to respond only via text. A prototype system, Mobltz, she and her colleagues have built is designed to change this, supporting the creation of channels of media from multiple people (which also reminded me of Kyte.tv).

As an example of the second case, Timo Koskinenen (Nokia) presented a trial of mobile media capture tools for professional journalists. In this case the work flow of what is, in the end, a media production practice, involves also consumption in the form of review of one’s own materials and other journalists, as they edit, consider what new media to capture.

Throughout the sessions themselves and conversations with participants during breaks and lunch, having good annotations continued to come up as a requirement for many of the services discussed. While I think our ZoneTag work (and the free suggested tags Web service API it provides) made a good contribution in this area, as has a wide array of other work (e.g., von Ahn & Dabbish 2004, licensed in Google Image Labeler), there is still a lot of progress to make, especially in bringing this work to market and making it something that further services can build on.

References

1. Blogging something at this level of roughness is still new for me… [↩]

[Update: This post uses an older Facebook UI as an example. Also see more recent posts on activity streams and the availability heuristic.]

Over at Captology Notebook, the blog of the Stanford Persuasive Technology Lab, Enrique Allen considers features of Facebook that influence users to update their status. Among other things, he highlights how Facebook lowers barriers to updating by giving users a clear sense of something they can right (“What are you doing right now?”).

I’d like to add another part of the interface for consideration: the box in the left box of the home page that shows your current status update with the most recent updates of your friends.

This visual association of my status and the most recent status updates of my friends seems to do at least a couple things:

Influencing the frequency of updates. In this example, my status was updated a few days ago. On the other hand, the status updates from my friends were each updated under an hour ago. This juxtaposes my stale status with the fresh updates of my peers. This can prompt comparison between their frequency of updates and mine, encouraging me to update.

The choice of the most recent updates by my Facebook friends amplifies this effect. Through automatic application of the availability heuristic, this can make me overestimate how recently my friends have updated their status (and thus the frequency of status updates). For example, the Facebook friend who updated their status three minutes ago might have not updated to three weeks prior. Or many of my Facebook friends may not frequently update their status messages, but I only see (and thus have most available to mind) the most recent. This is social influence through enabling and encouraging biased social comparison with — in a sense — an imagined group of peers modeled on those with the most recent performances of the target behavior (i.e., updating status).

Influencing the content of updates. In his original post, Enrique mentions how Facebook ensures that users have the ability to update their status by giving them a question that they can answer. Similarly, this box also gives users examples from their peers to draw on.

Of course, this can all run up against trouble. If I have few Facebook friends, none of them update their status much, or those who do update their status are not well liked by me, this comparison may fail to achieve increased updates.

Consider this interface in comparison to one that either

• showed recent status updates by your closest Facebook friends, or
• showed recent status updates and the associated average period for updates of your Facebook friends that most frequently update their status.

[Update: While the screenshot above is from the "new version" of Facebook, since I captured it they have apparently removed other people's updates from this box on the home page, as Sasha pointed out in the comments. I'm not sure why they would do this, but here are couple ideas:

• make lower items in this sidebar (right column) more visable on the home page -- including the ad there
• emphasize the filter buttons at the top of the news feed (left column) as the means to seeing status updates.

Given the analysis in the original post, we can consider whether this change is worth it: does this decrease status updates? I wonder if Facebook did a A-B test of this: my money would be on this significantly reducing status updates from the home page, especially from users with friends who do update their status.]