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The Influence of Anthropomorphism and Agency on Social Judgment in Virtual Environments

Kristine L. Nowak
University of Connecticut


Abstract

This project examined how information provided in virtual worlds influences social judgment. It specifically tested the influence of anthropomorphism and agency on the level of uncertainty and social judgment, using a between-subjects experimental design. Anthropomorphism had three levels; a high anthropomorphic image, a low anthropomorphic image and no image. Agency had two levels; whether the participants were told they were interacting with a human (avatar condition) or a computer (agent condition). The results showed that the virtual image influenced social judgment. The less anthropomorphic image was perceived to be more credible and likeable than no image, which was more credible and likeable than the anthropomorphic image. There were no discernable differences in social judgment between participants who were told they were interacting with a human as compared to those told they were interacting with a computer agent, consistent with findings from previous reports. Neither anthropomorphism nor agency influenced reported levels of uncertainty. Implications of these results for those designing and using virtual environments are discussed.


Introduction

People have used telecommunication systems for everything from forming and maintaining interpersonal relationships (Becker & Mark, 2002; Donath, 1999b; O'Sullivan, 2000; Palmer, 1995; Parks & Floyd, 1996) to social support, education and museums (Donath, 1999b; Schroeder, 2002) to business meetings and remote collaboration on projects (Burke & Chidambaram, 1995; Schroeder, 1996, 2002). There are a number of predictions about how the use of these systems will influence the person perception process, especially as technological advances continue to alter the way people are immersed in and represented by the computer (Nass & Moon, 2000; Riva & Galimberti, 2001). Progressive embodiment, or the increased prominence of the user's body and immersion of people's senses into the computer (Biocca, 1997; Biocca & Nowak, 2002), is occurring simultaneously with advances in artificial intelligence that are increasingly blurring the distinction between human-human and human-computer interactions (Brent & Thompson, 1999; Dryer, 1999).

This simultaneous progression of embodiment and advances in artificial intelligence raises a number of issues regarding the processes involved in making social judgments of others as well as people's level of uncertainty during computer mediated interactions. The experiment reported here tested the influence of the image as well as the extent to which the human/non-human distinction influenced perceived uncertainty and social judgment in a visual virtual environment. The implications of these findings for the design and use of virtual environments are discussed.


Representing People and Objects Inside the Computer

There are a wide variety of telecommunication systems and devices that people use to communicate across geographic distances. Those considered here are computer-based systems that allow people to interact with others from around the world. This section outlines some types of interactive virtual environments that have been used for both social and task-based interactions.

Text and Graphics Form a Consensual Hallucination

The earliest virtual worlds were text-based and existed primarily as a 'shared hallucination' in the minds of the users (Gibson, 1986). They consisted only of text-based descriptions of the "room" and the people in it. Although some text-based environments are still very popular (Schiano, 1999), technological innovation has given rise to new and varied types of virtual environments, some of which include graphics (Becker & Mark, 2002; Cassell & Vilhjalmsson, 1999; Damer, 1997). In these visual environments, people are generally represented by a visible image that others see as they interact (Taylor, 2002).

The images are chosen by the users to represent themselves and do not necessarily have any resemblance to their unmediated (natural) physical appearance, although they can. (See Kollock and Smith (1999) for a more detailed description and examples of uses of both text-based communities and visual chat rooms called graphical worlds.)

Images Represent Interactants in Virtual Environments

Being represented by an image in a mediated interaction allows for people to use the image for identification and to facilitate the turn-taking required for successful remote interactions (Benford, Greenhalgh, Rodden, & Pycock, 2001; Cassell & Vilhjalmsson, 1999; Guye-Vuilleme, Capin, Pandzic, Magnenat-Thalmann, & Thalmann, 1999; Talamo & Ligorio, 2001; Taylor, 2002). Further, the use of an image to identify an interactant is familiar and analogous to the experience of using the unmediated body in the natural world. Therefore, as discussed in this section, the reliance on images in the person perception process is likely to continue in virtual worlds.

The types of virtual images people have chosen to represent them have been as varied and diverse as the people who have used them. The images can vary on a number of levels (Talamo & Ligorio, 2001) from representations of people to animals or even inanimate objects. The images could be simple line drawings, cartoon characters, or very complex animated characters. The virtual images can also vary from unmoving two-dimensional pictures of a character to fluidly moving three-dimensional embodiments that walk, fly or float through the environment in a variety of ways (see Damer, 1997; Donath, Karahalios, & Viegas, 1999; Guye-Vuilleme et al., 1999; Talamo & Ligorio, 2001; Taylor, 2002; Tomlinson, Downie, & Blumberg, 2001).

Theoretically, these virtual environments allow people to interact and "exist in a world free from earthly physical constraints" (Paulos & Canny, 1997), or to "become a lobster," altering one's image to signal a mood change or to communicate something specific (Lanier, 1992). However, not all users utilize this ability. In fact, some users have been reported to use one image consistently during all or most interactions in social environments (Becker & Mark, 2002). These images are likely to be carefully chosen to represent characteristics the user considers essential to his or her identity and this image may be a better reflection of who they 'really' are than their unmediated, or natural body (Taylor, 2002). Perhaps those that choose consistency of representation do so out of a desire to be easily recognized by others, given that keeping track of 'who is whom' is a difficult challenge across time and different virtual bodies and worlds.

It seems that some users have chosen to maintain a consistent image, but others have chosen to take advantage of the ability to change appearance frequently. Oravec (1996) argued that the image selected for an interaction is analogous to clothing selected for a meeting in that both are vehicles of expression. Taylor (2002) reported, "it is not uncommon to find people switching heads based on a particular social situation" (p. 46). Some users have hundreds of images they use to represent them in various moods, locations (Taylor, 1999, 2002), and interaction goals (Benford, et al., 1995; Lanier, 1992). For example certain images may suit work environments such as those that support manufacturing and telemedicine, while others would be better for social interactions.

The impact of the appearance of the virtual image extends beyond the interaction, as it has implications for the construction of self as well as the interactants' perceptions of one another. Further, it is likely that the choice of image will frame how one perceives the user, the medium and the interaction itself (Biocca & Nowak, 2002). Whether or not someone chooses to use one image consistently it is likely that, as Suler (1997) suggested, an analysis of the images users choose to represent themselves would reveal important information about them. The next section introduces uncertainty reduction theory, which explains people's motivations during the social judgment process in initial interactions with others.


Uncertainty Reduction in Visual Virtual Environments

This section introduces uncertainty reduction theory and explains how the level of uncertainty is likely to influence interactions in virtual environments. This theory has its basis in the idea that when strangers meet, their primary goal is to create causal structures to explain their behavior and the behavior of others (Berger & Calabrese, 1975). In essence, the theory argues that a person's primary goal in an initial interaction is to reduce uncertainty about others to allow them to predict future behavior more effectively as well as understand motives and context for current or past behavior. Also, people have been shown to be more attracted to others when uncertainty about them has been reduced (Berger & Calabrese, 1975; Clatterbuck, 1979; Infante, Rancer, & Womack, 1997). Uncertainty is generally reduced when people feel they have enough information to make desired judgments within an interaction. In other words, it is not a sum total of information but the perceived quality of the information, or perceived success in seeking information that influences uncertainty. As Ramerez, Walther, Burgoon, & Sunnafrank (2002) argued, "uncertainty is conceptualized as a cognitive state that fluctuates based on the discrepancy between the information desired and the quality of that acquired" (p. 217).

The level of uncertainty will also be influenced by the context of the interaction (Berger & Calabrese, 1975). Thus, because it is likely that interactions in virtual environments will be less familiar than interactions in the unmediated world, people are likely to feel increased uncertainty and less confidence in their ability to make social judgments of others, especially in situations where no visible image is present. This level of uncertainty is likely to lead to people's working to find similarities or familiar characteristics so they feel more comfortable and the environment feels less strange. The next section explores the implications of the uncertainty reduction process on the likely influence of a person's visual representation on social judgment and during computer-mediated interactions.


The Influence of the Visual Image in Virtual Environments

The design and use of virtual images to represent people during computer-mediated interactions has raised questions about the image's potential influence on interactions and perception. Research has indicated that people rely heavily on the characteristics of a person's unmediated, or natural, body in the social judgment process (Burgoon, Buller, & Woodall, 1996; Ichheiser, 1970) and to reduce uncertainty about the behavior and intentions of others (Berger & Calabrese, 1975; Clatterbuck, 1979; Infante et al., 1997). In this process, people have used a combination of visual and behavioral cues. Research has indicated that the visual indicators, such as those related to the unmediated, or natural, body are the first and easiest to detect and are processed automatically, requiring almost no processing resources (Patterson, 1995; Tagiuri, 1958). People have been shown to rely heavily on appearance in perceiving others in unmediated interactions (Argyle, 1988; Bull, 1983; Bull & Rumsey, 1988; Burgoon, 1994).

Further, a person's appearance has been the basis of how people have identified one another during unmediated interactions (Ichheiser, 1970). Thus, a person's appearance may be seen as the basis of his or her identity (Waskul & Douglass, 1997). Similarly, Hampshier (1991) contended that people exist only because of and through their bodies. This would mean that to some extent a person's unmediated body does more than represent a person because it perceived to be the person. This may well carry over into how people identify one another when interacting in virtual worlds, as images make people and environments seem more 'real' (Taylor, 2002).

Essentially, "the multimedia, full-body electronic surrogates" that represent people in mediated interactions (Oravec, 1996, p. 48) provide a means of identification and recognition (Benford et al., 2001; Cassell & Vilhjalmsson, 1999; Talamo & Ligorio, 2001; Taylor, 2002). Thus, using the virtual image in the virtual world may be the natural inclination of a human used to relying on the unmediated body in the unmediated world. Using similar or analogous characteristics may be familiar and natural and help in the uncertainty reduction process for those interacting in a new or unfamiliar context and medium (see Tidwell & Walther, 2002).

People apparently use any information the interface or medium provides for social judgment during interactions, even pieces of a person's Web page (Sherman et al., 2001), username or domain name (Donath, 1999a). Also, individuals have attempted to draw inferences about the "intentions" and "mental states" of computers when only simplified simulations of cues were provided (Reeves & Nass, 1996; Sproull, Subramani, Kiesler, Walker, & Waters, 1996; Takeuchi & Naito, 1995). People have even tried to interpret facial expressions of roughly simulated computer images (Koda, 1996; Takeuchi & Naito, 1995). Sproull et al. (1996) found that providing a synthetic talking face on a computer monitor caused people to modify their behavior as if they were interacting with another human, Slater and Steed (2002) found that even a virtual audience caused anxiety in those with public speaking phobias, and Becker (2002) found that many social conventions in image usage have translated into analogous usage in virtual environments.

Further, any images representing a person have been perceived as a 'public signal' of who the person is (Taylor, 2002). It also appears that the virtual images influence perception and that different images have different influences (Koda, 1996; Oravec, 1996; Slater & Steed, 2002; Taylor, 2002; Turkle, 1995; Wexelblat, 1997) and the responses to virtual images have reflected responses to analogous natural bodies. For example, in unmediated interactions, people prefer to talk to attractive or interesting looking people (Dion, Berscheid, & Walster, 1972). This has continued to be true in virtual, or mediated, interactions where people represented by more attractive images were more sought after for communication (Suler, 1996), and the image is believed to evoke desire and even sexual attraction (Taylor, 2002).

Although people have responded socially to all interfaces to some degree (Reeves & Nass, 1996), this 'social' instinct appears to be stronger with the more 'human' looking (anthropomorphic) images in virtual worlds (Koda, 1996; Reeves & Nass, 1996; Turkle, 1995). People have reacted as if virtual images with human morphological characteristics (anthropomorphic) represented humans (Koda, 1996; Wexelblat, 1997), and less anthropomorphic images did not represent humans (Slater & Steed, 2002). Virtual images, especially those closely representing human forms, have been reported to be more engaging, interesting and attractive (Koda, 1996; Wexelblat, 1997).

This may be because people are most comfortable to human looking characters that look like them, or that look familiar. People seem to assume that people are 'like them' in the absence of disconfirming information (Gordon, 1986). This has continued to be true in mediated interactions (Walter, 1996). Therefore, an anthropomorphic image is likely to be more engaging and likeable because it is similar to the image people 'expect' to see, or the one they assume to be present when no image is provided by the medium or environment. This may explain why much of the character design work is done with a goal towards recreating life-like or human-like forms (Guye-Vuilleme et al., 1999; Isla & Blumberg, 2002).

At the same time, more anthropomorphic images may set up higher expectations of humanness that could result in negative attributions if these expectations are not met (Hindmarsh, Fraser, Heath, & Benford, 2001; Slater & Steed, 2002). For some communication goals, exaggerated features that clearly emphasize the capabilities and limitations of the environment may be more appropriate than 'realistic' or human-like features (Hindmarsh et al., 2001). The human/not human distinction is further considered in the next section.


Agents and Avatars; the Human/not Human Distinction in Virtual Environments

There are some processes involved in interacting in virtual worlds that will be the same or very similar to processes in the unmediated world. For example, the categorization process of people and scenes is likely to be similar regardless of whether the environment is virtual or unmediated. In the unmediated world, people process each object and person that enters their range of senses while navigating a complex and ever-changing environment (Fiske & Neuberg, 1990; Lakoff, 1987). While perceiving other people requires the same processes as perceiving objects, the use and meaning of different categories may make perceiving people more complicated than perceiving objects (Asch, 1958; Fiske & Neuberg, 1990; Heider, 1958; Sheehan, 1991b). For example, Heider (1958) explained:
Let us assume that we enter an unfamiliar room for the first time and in it we find a few people we have never met before. A glance around the room will suffice to get an approximately correct idea of the shape of the room and of the objects in it. We shall be much more insecure about our judgments of people. (p. 23)
If the processes are similar in virtual environments, the question becomes which categories will be relevant in the process of perceiving others and whether or not people will use 'human' or 'object' categories for agents.

Computers can display features and characteristics that have traditionally been reserved for living things, even those specific to humans. Terms have evolved to express whether the 'puppeteer,' or entity controlling the image in real time, is computer program (an agent), or a human (an avatar) (see also Blascovich, 2002). An agent refers to the case in which the 'puppeteer' is a computer. Specifically, an agent is a computer program that interacts with or on behalf of a user to carry out delegated tasks (Brent & Thompson, 1999; Laurel, 1990; Magnenat-Thalmann & Kshirsagar, 2000). When the 'puppeteer' is a human, the visual image that represents them is called an avatar. Thus, an avatar is a physical or graphic image that allows the user to be embodied in a virtual environment in real time.1

The Influence of Human/not Human Distinction in Virtual Environments

Philosophers have argued the human/non human distinction is significant and have defined humanity as distinct from, if not better than, both objects and animals (Sheehan, 1991a, 1991b). There are a number of things occurring in virtual environments that may blur the human/not human distinction. Those considered here are intelligence and visible image.

Until recently, intelligence and autonomy provided a distinction between humans and all other things, whether living or not. However, advances in artificial intelligence make it increasingly possible for agents to perform tasks that were traditionally possible only for only humans (Goodwin, 1998; Magnenat-Thalmann & Kshirsagar, 2000). These advances in artificial intelligence have made that distinction questionable (Brent & Thompson, 1999; Dryer, 1999; Goodwin, 1998). For example, in experience in the unmediated world all living things likely contain common properties that distinguish them from inanimate objects (Asch, 1958; Heider, 1958). This may not be true in virtual environments.

Also, in the natural world only living things autonomously move and interact in the environment and only humans have interacted socially or displayed 'true' intelligence. These experiences may lead to a variety of assumptions during the categorization process, which may cause confusion where non-humans display autonomous action and intelligence. Further, an agent may be represented by an image and this image could be anthropomorphic. To further complicate the perception process, the same image could also represent a human at the same time (Oravec, 1996). This lack of visible distinction between humans and computers has made it increasingly difficult to differentiate between avatars and agents (Goodwin, 1998).

In support of the idea that human categories are relevant in processing agents, research has shown that people respond socially to agents (Dryer, 1999; Reeves & Nass, 1996). In a program of study, Reeves and Nass (1996) found that people expected social rules to be followed by agents, applied gender stereotypes to simulated voices, and that people followed social norms during interactions with agents. They argued that people automatically interpret stimuli that appear intelligent as driven by a human entity (see also Koda, 1996; Nass, Lombard, Henriksen, & Steuer, 1995; Nass & Moon, 2000).

If it is true that users have a tendency to respond socially to agents, then this may lead to the rise of various types of new and unique 'social' relationships. All of these interactions may not be interpersonal (between two people) but might include some form of non-human intelligence. Regardless of the actual level of 'humanness' of an interaction partner, they may still provide a satisfying interaction that meets their interaction goals (Biocca & Nowak, 2002).

This section outlined the types of virtual environments that people have interacted in, as well as categories of virtual images that they may choose to represent them. It introduced the problem of differentiating humans from computer agents as technology continues to improve.


Social Judgment in Virtual Worlds

The section will explore a few categories and judgments people are believed to make during interactions with intelligent others in the natural world that are likely to remain salient in interactions in virtual worlds.

Social Attraction

Social attraction has been shown to have a number of levels and has been considered an important part of social judgments of others (McCroskey & McCain, 1974, p. 261). This is a determinant of whether or not people avoid or seek out the company of others (Horwitz, 1958). Within this notion is the general concept of interpersonal attraction, which contains evaluative sentiments that are central components of interpersonal relationships.

Credibility

Credibility refers to the judgments made by the perceiver about the believability of information provided by a source and the source's knowledge on a particular topic (McCroskey, 1971; McCroskey, Hamilton, & Weiner, 1974). Receivers have been shown to be more open to communication from sources they perceive to be credible than to others (McCroskey et al., 1974).2

The next section discusses how people's desire to reduce uncertainty in interpersonal interactions is likely to influence the process of social judgment during interactions in virtual environments.


Making Social Judgments in Virtual Worlds: Similarities and Differences

Interactions using computer media are becoming more common, but it is likely that the majority of personal interactions are unmediated and take place with other humans. In these unmediated interactions, people have come to rely on physical characteristics for categorization and social judgment and it is easy to visibly distinguish between humans and non-humans. People have had less experience interacting with images people create to represent them or with non-humans that look human-like or display intelligence. These factors are likely to contribute to the level of uncertainty and social judgment, as explained below.

It appears that people have turned to familiar indicators to enable them to navigate the unfamiliar and relatively new environments created by computers. As in unmediated interactions where people have relied on the relatively stable physical features of the face and body for social judgment (Argyle, 1975, 1988; Hinton, 1993; Ichheiser, 1970), people have continued to use visible indicators for social judgment in virtual worlds (Lipton, 1996; Reeves & Nass, 1996; Spender, 1996; Suler, 1996; Takeuchi & Naito, 1995; Waskul & Douglass, 1997).

It is likely that when people enter an environment, whether mediated or not, they form social judgments of those they encounter to reduce uncertainty. Further, people are likely to continue to place objects and people into categories that are related to those they have previously experienced. The following predictions are based on these assumptions.

Visible Virtual Images Influence People's Social Judgments

As discussed above, more anthropomorphic virtual images have been shown to be more interesting and engaging. Further, people have treated any intelligent others as social actors, especially when they were highly anthropomorphic, and people are likely to continue their reliance on visible indicators for social judgments of others. In the absence of disconfirming evidence, people assume the default other is anthropomorphic. These observations lead to the following predictions:

Hypothesis I: More anthropomorphic partners will be rated as more socially attractive.

Hypothesis II: More anthropomorphic partners will be rated as more credible.

People have less experience interacting with intelligent others who are not human. They are likely to feel less certain making social judgments of less anthropomorphic others. Thus,

Hypothesis III: Less anthropomorphic characters will cause more uncertainty.

Effect of Agency on Social Judgment

Because categories relevant in perceiving humans are different than categories relevant in perceiving objects, people are predicted to assign agents to different categories than they would assign humans to. During interactions, there may be varying levels of "humanness" or qualities that would cause an entity or interaction partner to be categorized as human-like. The distinction between computer agents and humans is predicted to influence social judgment as people's experiences in the unmediated world have shown the human/non-human distinction to be meaningful.

In some ways perceiving an agent may not be so different from perceiving another human during a task-based interaction because the relevant judgments may have to do with qualifications for performing the task. However, it is predicted that there will be discernable differences in social judgments because of the human/non-human distinction.

Hypothesis IV: All other things being equal, people will rate avatars as more socially attractive than agents.

Hypothesis V: All other things being equal, people will rate avatars as more credible than agents.

People do not have as much experience with computer agents, so they may not have a familiar script to perceive or evaluate them (Dryer, 1999). Thus, people will be less confident about their ability to make social judgments of computer agents as compared to their confidence in judgments about humans.

Hypothesis VI: People will express more uncertainty in social judgments of computer agents than humans.


Method

Design

A 2 X 3 between-subjects experiment was conducted using two factors: (1) agency of virtual other with two levels ((a) participants were told they were interacting with a human (avatar condition) or (b) a bot (agent condition)), and (2) degree of anthropomorphism of virtual image with three levels ((a) highly anthropomorphic image, (b) low anthropomorphic image, and (c) no image control).

Participants

134 undergraduates (94 males, 40 females) at a large Midwestern university received extra credit in introductory telecommunication courses for participating in the study. Participants were stratified by sex and randomly assigned to one of the six experimental conditions.

Stimulus Materials

The environment.
This interaction took place in a 3-dimensional environment that appeared on a computer screen and resembled a meeting room. Participants either saw an image representing their interaction partner in the environment, or did not.

Degree of anthropomorphism.
The degree of anthropomorphism was manipulated by inserting one of three types images in a virtual room: (1) a high-anthropomorphic image (click here to see the animated image); (2) a low-anthropomorphic image (click here to see the animated image); or no image at all (see Figure 1).


Figure 1. In the no image condition, participants viewed this scene during the interaction.


Agency.
Both written and verbal instructions contained the agency manipulation. Participants were given one of two versions of the instruction sheet. The avatar version indicated the partner was another student and the agent version said their partner was a computer agent. The experimenter repeated the instructions orally.

Measurement Instruments3

Social attraction.
A 9-item likert-type scale with a 7-point metric from McCroskey and McCain (1974) was modified so all items would be applicable to non-human interactants. The items measured the extent to which participants felt their partner was pleasant or offensive and whether or not the participant desired a future interaction.

Credibility.
A 10-item likert-type scale with a 7-point metric from McCroskey and Wright (1971) was modified so all items would be applicable with non-human interactants. Items measured whether the confederate was professional, cooperative and knowledgeable.

Uncertainty.
A 7-item likert-type scale with a 5-point metric based on Clatterbuck's (1979) Attributional Confidence Scale was used. This included items measuring confidence in predicting their partner's attitudes, values and future behavior.

Procedure

Participants signed a consent form, filled out a pretest measuring computer use and demographics and were given one of the versions of the instruction sheet containing the agency manipulation. They were informed that their goal was to get to a partner who may work with them in the future to compete for a $100 prize on a scavenger hunt on the World Wide Web. The participants sat at a 19" computer screen with headphones, a microphone, and a keyboard.

In the no image condition, participants entered their id numbers and immediately entered the virtual room (see Figure 1, above). In the other conditions, participants entered the id numbers and went to the character selection screen (See Figure 2), where they selected an image to represent them. Then participants entered the virtual environment by pressing the 'enter' button, and saw either the high anthropomorphic (see Figure 3) or low anthropomorphic image (see Figure 4). The interaction partner was already there when participants in all conditions arrived.


Figure 2. In either the high-anthropomorphic or low-anthropomorphic conditions, participants selected one of these characters to represent them.


Figure 3. In the high-anthropomorphic image condition, participants viewed this scene during the interaction with the more-anthropomorphic image shown here.


Figure 4. In the less-anthropomorphic image condition, participants viewed this scene during the interaction with the less-anthropomorphic image shown here.


The average interaction lasted about fifteen minutes. All interactions began with 'Kim' introducing herself (click here to listen this intro). After this introduction, participants saw a green light indicating it was their 'turn.' The participant was then asked to speak into a microphone to give his or her name and other introductory information. Following the introduction, the participant pressed to indicate that his or her turn was over and the green light turned red. After they finished their introductions 'Kim' indicated her skills relevant to doing an online scavenger hunt. All participants heard the same voice and the same skills (click here to listen to her skills). When 'Kim' was finished, the participant again saw a green light indicating that it was their turn to summarize their skills relevant to the scavenger hunt on the World Wide Web and again press when finished. After that, Kim indicated that she had enjoyed meeting the participant and hoped for the ability to work with them in the future (click here to listen to Kim signing off). Then the green light came on again, allowing the participant to say goodbye. When the participant said goodbye and again pressed , the interaction was over. Following the interaction, participants filled out an online post-test questionnaire on a different computer and were debriefed.


Results

Effects coded regression was run to test the influence of the virtual image on social attraction (Hypothesis I), credibility (Hypothesis II) and uncertainty (Hypothesis III). An independent samples t-test for Agency was conducted for Hypotheses IV-VII. The agent variable was effect coded and a regression was run to look for multiplicative interaction, but none was found.

Influence of the Virtual Image

These hypotheses were tested with linear regressions with effects coded values (1= anthropomorphic image, 0 = no image, and -1 = non anthropomorphic image) (see Table 1).

Variable

в

SE в

β

Social Attraction

.32

.11

.24*

Credibility

.12

.6

.18*

Uncertainty

.12

.10

.11

Table 1. Linear regression table with effects coded values (0 = no image, -1 = low anthropomorphic image, 1 = high anthropomorphic image) on social attraction, credibility and uncertainty. *p <.05.


Hypothesis I: More anthropomorphic partners will be rated as more socially attractive.

Six of nine Likert-type items remained in the scale of social attraction after the tests of internal consistency and reliability (Standard alpha = .83). The scale was a 1-7 Likert-type scale. Individual averaged item responses ranged from 1 to 7.

Hypothesis 1 was not supported and in fact data show a significant effect in the opposite direction.

The effect of a high-anthropomorphic virtual body on social attraction is significant though not in the predicted direction, R = .24, F = 8.1, p = .05. These results show a linear relationship, with those in the high-anthropomorphic condition reporting their partners as least socially attractive, followed by those in the no image condition and with people in the low anthropomorphic condition reporting their partners as the most socially attractive. (See Figure 5).


Figure 5. Means of credibility, social attraction and uncertainty by condition: no image condition, high-anthropomorphic image condition and low-anthropomorphic condition.


Hypothesis II: More anthropomorphic partners will be rated as more credible

This hypothesis was not supported and data show a significant effect in the opposite direction.

All ten Likert-type indicators of credibility remained after the tests of internal consistency and reliability (standard alpha = .89). The scale was a 1-7 Likert-type scale and the individual's averaged item responses ranged from 2.67 to 5.33.

The effect of a high-anthropomorphic virtual body on credibility is significant but not in the predicted direction, R = .18, F = 4.36, p = .04. These results show a linear relationship, with people in the less-anthropomorphic condition reporting their partner the most credible, followed by those in the no image condition. People in the more anthropomorphic condition reported their partner to be least credible (see Figure 5, above).

Hypothesis III: Less anthropomorphic characters will cause more uncertainty.

This hypothesis was not supported.

All seven indicators from the Uncertainty Scale remained after tests of internal consistency and reliability (standard alpha = .88). The scale was a 1-5 Likert-type scale and the individuals averaged item responses ranged from 1 to 5.

The effect of a low anthropomorphic visual virtual image on uncertainty was not significant, R = .11, F = 1.58, p = .21.

On the Influence of Agency

Independent samples T-Tests for Agency were conducted to test hypotheses IV-VI.

Hypothesis IV: All other things being equal, people will rate avatars as more socially attractive than agents.

This hypothesis was not supported. The effect of agency on social attraction was not significant, t(132) = .33, p = .74. People did not report their partner to be more socially attractive whether they thought they were an agent (M = 4.25, SD = 1.08) or an avatar (M = 4.31, SD = 1.14).

Hypothesis V: All other things being equal, people will rate avatars as more credible than agents.

This hypothesis was not supported. The effect of agency on credibility was not significant, t(130) = -.88, p = .38. There was no difference in credibility ratings whether people thought their partner was an agent (M = 4.22, SD = .53) or an avatar (M = 4.31, SD = .57).

Hypothesis VI: People will express more uncertainty in social judgments of agents than of avatars.

This hypothesis was not supported. The effect of agency on uncertainty was not significant, t(129) = 1.63, p = .11. People did not feel any less uncertainty interacting with an agent (M = 2.28, SD = 1.00) rather than an avatar (M = 2.02, SD = .79).


Discussion

This article explored the influence of virtual images and agency on perceptions of social attraction, credibility and uncertainty. On the question of the extent to which a virtual image influenced perception there was a linear effect of the image, which was not in the predicted direction. The partner represented by the more anthropomorphic image received the lowest social judgment ratings, followed by no image, with the partner represented by the less anthropomorphic virtual image receiving the highest ratings. The close relationship between those in the high anthropomorphic condition and those in the no image condition supports the notion that the 'default other' is assumed to be anthropomorphic. There was no discernable effect of agency, or the human/not human distinction. This section discusses the implications of these findings, beginning with the influence of images.

The Virtual Image Influenced Perception

These results suggest that the virtual image influences the perception of the person who chooses it. Other research concluded that more anthropomorphic images are more engaging, interesting and attractive (Koda, 1996; Wexelblat, 1997). The results presented above would not support that conclusion, but instead indicate that the features that lead to engagement and interest are more complicated than simply the extent to which an image is anthropomorphic. In this case, looking 'more human' did not make the partner more engaging or attractive. This could be evidence that anthropomorphic images set up higher expectations (Hindmarsh, Fraser, Heath, & Benford, 2001; Slater & Steed, 2002) and in this case these expectations were not met, which resulted in less positive attributions. Future research should examine what characteristics of images influence perception.

At the same time, these results are consistent with previous research in that they indicate that the virtual image influences perception. This may be explained by people's experience in the natural world, where they have relied on the physical, relatively unchanging features of the physical body for social judgment (Argyle, 1975; Chesebro & Bonsall, 1989; Fiske & Neuberg, 1990; Goffman, 1963; Hinton, 1993; Ichheiser, 1970). The reliance on the visible characteristics appears to have extended into virtual worlds where these characteristics are easily altered (Oravec, 1996).

The fact that those who saw no virtual image had similar social judgments to those who saw the more anthropomorphic image provides support for the notion that people create a 'default image' of the other during interactions and that in the absence of disconfirming information, this image is anthropomorphic. The important question to consider is why the judgments of the less anthropomorphic image were significantly more favorable than either no image or the more anthropomorphic image.4

The images selected for this project were distinct and this leaves open a few questions including what would have happened with different virtual images. Future research should continue to examine when and why certain types of images are more favorable than others. However although people can choose to be represented by any body or image in a virtual environment, there are consequences to the choice.

Differentiating Reactions to Humans as Compared to Computer Agents

There was no discernable distinction between agents and avatars with regard to social attraction, credibility or uncertainty. This indicates that people not only liked the agent as much as they liked the avatar and that they would be as likely to seek them out for friendship and for future interactions, but also that both agents and avatars were considered about equal with regard to perceived knowledge and credibility. Finally, people were not any more uncertain about their ability to perceive the intentions and motives of a computer agent than those of another human. This section explores the implications of these results.

Though making conclusions based on null results is questionable, these results support the conclusion of other researchers that people have responded socially to both human and not human others as well as to the computer interfaces themselves (Nass & Moon, 2000; Reeves & Nass, 1996; Slater & Steed, 2002). Reeves and Nass (1996) argued that the tendency to treat all intelligences socially was due to a 'hard-wired' tendency in people's categorization process that any display of intelligence will automatically result in responses that are social. However, there are other possible explanations as well. It is possible that the human brain has not adapted to dealing with entities that look human but are not or entities that are human but do not look it. The human experience in the natural world has only provided interaction with human intelligent others and not with intelligent others who were not human.

If this explanation is true, this distinction may evolve meaning as experience with agents becomes more common. There may be a sufficiency threshold where an intelligent other begins to be perceived as intelligent, or human enough, for the purposes of the interaction. If so, it appears that the threshold was met. Further, if there is a sufficiency threshold, it is likely that the standard for social interactions would be higher than the standard for task-based interactions. It is important that researchers consider the context of their interaction. It is possible that the distinction between agents and avatars would be more influential in a social interaction. Finding this sufficiency threshold, if it exists, may be an important area of future research, especially as more interactions take place online. It is also possible that further experience with non-human intelligences may make the distinction between computer agents and humans salient and meaningful.


Conclusion

People used the mediated image to make social judgments of others, and the human/not human distinction did not influence social judgment. The fact that the virtual image influenced social judgments is not consistent with the notion that cyberspace has become a utopia where all voices are equal, as some early researchers had predicted (Hert, 1997; Lea & Spears, 1992; Rice & Love, 1987; Siegel, Dubrovsky, Kiesler, & McGuier, 1986). Instead, it shows that people are relying on other available information for social judgment in mediated interactions.

This points to the importance of understanding what types of images influence perception in a variety of contexts so that users of these systems can make educated decisions in choosing an image to represent them. As long as people know it is influencing others, they may change their image much like choosing an outfit tailored to the event. This informed control over social judgment might represent a move toward realizing the utopian predictions, as long as everyone has the same choices.

On the other hand, it may not be that electronic persons are not more 'equal' but that people use different criteria to evaluate them (Schmitz & Fulk, 1991; Turkle, 1995). As hinted at in Snow Crash, beautifully designed avatars with fluid movement will be contrasted with the store bought avatars represented by people dialing in from public terminals. In other words, the information utilized to make the attribution that someone is 'from the wrong side of the tracks' will evolve (Clark, 1995; Stephenson, 1993). So instead of being judged by the body a person was born with, people may be judged by the characteristics of the image they choose (or can afford) to represent them (Taylor, 2002).

At the same time, understanding when and how a computer agent can be used in the place of a human will become increasingly important as interactions increasingly move online. In this task-based interaction, responses to humans and computer agents were indistinguishable from people's responses to computer agents. This indicates that everyone with the same image will be responded to equally.

These results show that the virtual body influences social judgment and that the human/not human distinction does not. More research is needed to clarify which features of the virtual image have what type of influence. Further, this task-based interaction cannot address the extent to which either these virtual images or agency would influence perception in a social interaction or whether or not there are contexts in which the human/not human distinction would matter.


Footnotes

1. Neil Stephenson is credited with originally using the term in this way in his science fiction book, Snow Crash.

2. This does not include all dimensions of credibility (see Cronkhite & Liska, 1976).

3. Confirmatory factor analysis and tests of internal consistency were applied to each scale. All items loaded highest on their primary factor. The final number of items in each scale and standardized item alpha is detailed when scale is first used in analysis.

4. See Figure 2. The means for all conditions were above the middle of the scale.


Acknowledgments

This project was carried out at Michigan Sate University's MIND Lab and would not have been possible without the assistance of its director, Frank Biocca. This project was funded in part by the MSU Foundation and the SBC-Ameritech Foundation. The MIND Lab staff, especially Eric Maslowski, created the images used in this study. Thanks also to Carrie Heeter, Kelly Morrison, Sandi Smith, Chip Steinfield, Duncan Rowland and Mark Hamilton for their assistance with this project.


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About the Author

Kristine L. Nowak (Ph.D. Michigan State University) is an Assistant Professor in the Department of Communication at the University of Connecticut, where she is the director of the Human Computer Interaction Lab. Her research examines the person perception process, and people’s sense of presence in computer environments. She is also interested in examining usability issues and predictors of people’s satisfaction with computer media.
Address: Department of Communication Sciences, U-1085, Storrs, CT 06269.

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