Function and processing of expectations

because the users have heard the robot speak before but because they assume that all robots (or social robots) do understand speech. In general, in HHI category-based expectations are discarded in favor of more target-based expectations during the interaction (Jones, 1990).

Category-based expectations can be divided into dispositional and normative expectations (Jones, 1990). Dispositional expectations are based on the belief that different members of a group share certain characteristics (dispositions); for example, people participating in HRI studies are interested in robotics and technology in general, or social robots are able to understand speech. Dispositional expectations are more probabilistic than target-based expectations. They tell us what might happen but when the probability is not close to certain, allow us to turn to another expectation quickly. Dispositional expectations are a combination of several expectations about the situation while normative expectations are more strongly bound to the situation in focus.

Target-based expectations vary on a dimension from replicative to structural:

replicative: we expect a person to behave in the same way again if a situation is rather similar

structural: expectations based on a complex cognitive schema or an implicit theory of personality that allows predictions for people with certain traits To conclude, expectation formation is guided by many factors such as the information that is taken into account. Once expectations are formed they are not necessarily stable but part of the dynamic memory that changes with the experiences that agents make. This is true especially for target-based expectations which are less probabilistic than category-based expectations and more likely to be replaced in the case of disconfirmation. For the analyses presented below, it seems reasonable to assume that the users’ expectations are mainly target-based because they have not experienced the interaction with other members of the group, i.e., they have never interacted with a robot before. Therefore, in the model that is introduced below, expectations are regarded as being highly dynamic. Moreover, the expectations are assumed to be replicative, i.e., the users believe that the robot behaves the same in a similar situation because it has done so before. Thus, it can be assumed that the users do not change their behavior if it has turned out to lead to a satisfying result before. The users might also attribute traits to a robot which would be in favor of the structural dimension. However, they barely know the robot. Moreover, transferring different personality traits from HHI to HRI and applying complex cognitive schema would cause additional cognitive load. This is underlined by the finding that most participants found it quite difficult to judge the personality of the robot in a personality questionnaire.¹⁰

In general, the function of expectations is to guide effective behavior by providing a “shortcut”

in mental processing (Endsley, Bolté, & Jones 2003; Roese & Sherman, 2007). Analyzing every situation anew would be very time consuming and require a lot of processing resources. That is why expectations can save processing time in many situations (Roese & Sherman, 2007); for example, people expect that the action of pushing the light switch turns on the light and do not have to think about this over and over again. However, other expectations are not quite as accurate (see, for example, Neuberg, 1996). This is not surprising when we think about the sources of expectations: stereotypes and prejudices, third-party hearsay, observations of others behaviors that have been constrained without us being aware of the constraints. Because expectations guide attention and how the person perceives information, false expectations can lead to misinterpreted data and can, therefore, negatively influence SA (Endsley, Bolté, & Jones 2003, see Section 2.1.1.2).

To conclude, in order to accelerate mental processing, expectations have to deliver information accurately and efficiently, i.e., fast and with little processing effort (Roese & Sherman, 2007).

Thus, the expectations have to support the mental construction process (see Section 2.1.1.2). An expectation-driven construction process is described in Darley and Fazio (1980) with respect to a social interaction sequence between two people (see Figure 2-4).

The figure shows that the authors differentiate between perceiver and target person. However, they stress that both interlocutors can take both roles at any time and the process does not have to be symmetric. The central aspect of this sequence is the construction of the situation. In the construction process, expectations are important because they guide information gathering top-down and, thus, influence event processing. Moreover, they provide structure and meaning for the interpretation of the gained information.

Figure 2-4. Expectation-driven construction process (Darley & Fazio, 1980)

Based on this idea of constructivism, Ross and Conway (1986) developed a model of personal recall. The model emphasizes the role that response-expectancies play in the reconstruction of past events. It highlights that personal recall only depends on construction processes. However, the model ignores the fact that sometimes recall of the past is highly accurate and not always biased by inaccurate expectancies (Neuberg, 1996). To overcome this shortcoming, the model of expectancy-guided retrieval was developed (see Hirt, 1990; Hirt, Lynn, Payne, Krackow, &

McCrea, 1999). This model describes retrieval from memory as based on several sources, i.e., information about the present, expectancy regarding stability and change between past and present, and episodic memory trace of the original information. In other words:

[…], the proposed retrieval process involves retrieval of the original information anchored at the outcome (the benchmark) and guided by one’s expectancy.” (Hirt, 1990, p.949)

The weighting of the episodic memory trace, on the one hand, and the expectancy, on the other hand, determines the accuracy of the recall. It depends on the accessibility and the strength of the original memory trace, the motivation at retrieval, and on the assumptions on how the mind works (lay people usually assume that memories are correct and that their attitudes and beliefs do not change over time) (Hirt, 1990). If expectations and not episodic memory traces are the main source of recall, they can lead to inaccurate inferences if being incorrect, biasing information collection, or overruling consideration of information altogether (Sears, Peplau, Freedman, & Taylor, 1988).

The theory that has been presented on function and processing of expectations so far leads to the following implications for the model presented below. The function of expectations is to save time and processing resources. However, the price might be that our perceptions are not accurate, even though expectations can change and improve over time because they are part of the construction process. In other words, the users could form inaccurate expectations about the robot at first but might adapt them over time.

In fact, expectations change whenever they are retrieved from memory. They are an inherent part of our dynamic memory and strongly reflect our experiences. In other words, expectations are case based (Schank, 1999). Looking at it that way, the dynamic memory is a learning system. According to Schank (1999), learning means to alter the memory in response to experiences. Noticing and recalling mismatches to generalizations enables learning because it helps to improve outcome predictions. Having better predictions helps people to better cope with the environment. If someone encounters a deviation from an expectation he or she will most probably be reminded of episodes that are relevant for this deviation if these are stored and labeled properly. Schank (1999) calls high-level structures under which memories are stored TOPs (thematic organization packets). Within TOPs, three kinds of information are stored:

expectational information, static information (knowledge of the state of the world that describes what is happening when a TOP is active), and relational information (links of TOPs to other structures in memory). Once a TOP has been selected, we begin to generate expectations.

Expectations are generated by using appropriate indices to find episodes organized by that TOP.

In most cases, many memories are stored within one TOP. That is why indices are needed to find a particular memory.

More than one TOP can be active at a given time, which is reasonable because people want to be able to apply memories that are about the kind of goal they are pursuing as well as others that have nothing to do with the particular goal. Cross-contextual learning is enabled by breaking apart experiences and then decomposing them with the help of TOPs when remembering. For this process, memory structures have to be linked in the brain. According to Schank (1999), information about how memory structures are ordinarily linked in frequently occurring combinations is held in MOPs (memory organization patterns). MOPs are both memory and processing structures.

“The primary job of a MOP in processing new inputs is to provide relevant memory structures that will in turn provide expectations necessary to understanding what is being received. Thus MOPs are responsible for filling in implicit information about what events must have happened but were not explicitly remembered.” (Schank, 1999, p.113)

TOPs and MOPs are the structural basis of memories and information in memory (Schank, 1999). All these structures need to have the following basic content:

• a prototype

• a set of expectations organized in terms of the prototype

• a set of memories organized in terms of the previously failed expectations of the prototype

• a characteristic goal

If a situation deviates from the prototype, expectations are failed. As was mentioned above, this enables learning because with the help of TOPs it supports to improve outcome predictions.

This idea is central in the model presented below because the aim of the user studies that it will be applied to is to find differences between the prototype of the designed interaction and the mental representations of the users and to identify behaviors that are connected to (dis-) confirmation of their expectations. What happens in the case of expectation disconfirmation will be discussed in the following section.