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Modern Applied Statistics With S

The measurement of meaning

The Social Psychology of Groups. J. W Thibaut & H. H. Kelley. New York: alley, 1959. The team of Thibaut and Kelley goes back to 1946 when, after serving in different units of the armed services psychology program, the authors joined the Research Center for Group Dynamics, first at M.LT and then at the University of Michigan. Their continued association eventuated in appointments as fellows at the Center for Advanced Study in the Behavioral Sciences, 19561957. It is during these years that their collaboration resulted in the publication of The Social Psychology of Groups. The book was designed to "bring order and coherence to present-day research in interpersonal relations and group functioning." To accomplish this aim, the authors introduced, defined, and illustrated basic concepts in an effort to explain the simplest of social phenomena, the two-person relationship. These basic principles and concepts were then employed to illuminate larger problems and more complex social relationships and to examine the significance of such concepts as roles, norm, power, group cohesiveness, and status. The lasting legacy of this book is derived from the fact that the concepts and principles discussed therein serve as a foundation for one of the dominant conceptual frameworks in the field of family studies today-the social exchange framework. Specifically, much of our contemporary thinking about the process of interpersonal attraction and about how individuals evaluate their close relationships has been influenced by the theory and concepts introduced in The Social Psychology of Groups. Today, as a result of Thibaut and Kelley, we think of interpersonal attraction as resulting from the unique valence of driving and restraining forces, rewards and costs, subjectively thought to be available from a specific relationship and its competing alternatives. We understand, as well, that relationships are evaluated through complex and subjectively based comparative processes. As a result, when we think about assessing the degree to which individuals are satisfied with their relationships, we take into consideration the fact that individuals differ in terms of the importance they attribute to different aspects of a relationship (e.g., financial security, sexual fulfillment, companionship). We also take into consideration the fact that individuals differ in terms of the levels of rewards and costs that they believe are realistically obtainable and deserved from a relationship. In addition, as a result of Thibaut and Kelley's theoretical focus on the concept of dependence and the interrelationship between attraction and dependence, there has evolved within the field of family studies a deeper appreciation for the complexities and variability found within relationships. Individuals are dependent on their relationships, according to Thibaut and Kelley, when the outcomes derived from the existing relationship exceed those perceived to be available in competing alternatives. Individuals who are highly dependent on their relationships are less likely to act to end their relationships. This dependence and the stability it engenders may or may not be voluntary, depending on the degree to which individuals are attracted to and satisfied with their relationships. When individuals are both attracted to and dependent on their relationships, they can be thought of as voluntarily participating in their relationship. That is, they are likely to commit themselves to the partner and relationship and actively work for its continuance. Thibaut and Kelley termed those relationships characterized by low levels of satisfaction and high levels of dependence "nonvoluntary relationships. …

The Social Psychology of Groups

In this paper, we question the simplicity of the common prescription that more thinking leads to better 26 moral choices In three studies, we discover that the relationship between how complexly one reasons 27 before making a decision with moral consequences is related to the outcome of that decision in a curvi

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Organizational Behavior and Human Decision Processes

Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given the exceptional dependence of humans on communication and their vulnerability to misinformation. A wide range of evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis. Poor performance in standard reasoning tasks is explained by the lack of argumentative context. When the same problems are placed in a proper argumentative setting, people turn out to be skilled arguers. Skilled arguers, however, are not after the truth but after arguments supporting their views. This explains the notorious confirmation bias. This bias is apparent not only when people are actually arguing, but also when they are reasoning proactively from the perspective of having to defend their opinions. Reasoning so motivated can distort evaluations and attitudes and allow erroneous beliefs to persist. Proactively used reasoning also favors decisions that are easy to justify but not necessarily better. In all these instances traditionally described as failures or flaws, reasoning does exactly what can be expected of an argumentative device: Look for arguments that support a given conclusion, and, ceteris paribus, favor conclusions for which arguments can be found.

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Why Do Humans Reason? Arguments for an Argumentative Theory

OBJECTIVE: We examine whether trust in smart systems is generated analogously to trust in humans and whether the automation level of smart systems affects trustworthiness and acceptability of those systems. BACKGROUND: Trust is an important factor when considering acceptability of automation technology. As shared goals lead to social trust, and intelligent machines tend to be treated like humans, the authors expected that shared driving goals would also lead to increased trustworthiness and acceptability of adaptive cruise control (ACC) systems. METHOD: In an experiment, participants (N = 57) were presented with descriptions of three ACCs with different automation levels that were described as systems that either shared their driving goals or did not. Trustworthiness and acceptability of all the ACCs were measured. RESULTS: ACCs sharing the driving goals of the user were more trustworthy and acceptable than were ACCs not sharing the driving goals of the user. Furthermore, ACCs that took over driving tasks while providing information were more trustworthy and acceptable than were ACCs that took over driving tasks without providing information. Trustworthiness mediated the effects of both driving goals and automation level on acceptability of ACCs. CONCLUSION: As when trusting other humans, trusting smart systems depends on those systems sharing the user's goals. Furthermore, based on their description, smart systems that take over tasks are judged more trustworthy and acceptable when they also provide information. APPLICATION: For optimal acceptability of smart systems, goals of the user should be shared by the smart systems, and smart systems should provide information to their user. Language: en

Trust in smart systems: sharing driving goals and giving information to increase trustworthiness and acceptability of smart systems in cars.

This research views dispositional inference as a process whereby perceivers integrate multiple inferences about a target person's motives and traits. The findings suggest that although perceived motives may stimulate extra attributional processing (S. Fein, 1996), the content of the inferred motive is important as well. Perceivers learned about situational forces implying that a target person had free choice, no choice, or an ulterior motive for helpful behavior. Inferences about the target's helpfulness differed depending on whether the target's behavior was attributed to an obedience motive (no-choice condition) or to a selfish motive (ulterior-motive condition). In general, inferences about motives were more predictive of dispositional inferences than were global causal attributions (to situational vs. dispositional forces) or base rate assumptions.

Dispositional attribution: multiple inferences about motive-related traits.

Earlier theorizing suggested that an (artificial) agent that combines persuasive strategies will be more persuasive. Therefore, the current research investigated whether a robot that uses two persuasive strategies is more persuasive than a robot that uses only one. Two crucial persuasive strategies that humans use in face-to-face persuasion are gazing and gestures, and therefore we studied the combined and individual contribution of these two persuasive strategies (gestures and gazing) on the persuasiveness of a storytelling robot. A robot told a classical persuasive story about the consequences of lying to forty-eight participants, and was programmed to use (persuasive) gestures (or not) and gazing (or not). Next, we asked participants to evaluate the character in the story thereby assessing the robot’s persuasiveness. Results presented evidence a robot’s persuasiveness is increased when gazing is used. When the robot used gestures, its persuasiveness only increased when it also used gazing. When the robot did not use gazing, using gestures diminished the robot’s persuasiveness. We discuss the implications for theory and design of robots that are more persuasive.

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Combining Robotic Persuasive Strategies: The Persuasive Power of a Storytelling Robot that Uses Gazing and Gestures

Social agency theory suggests that when an (artificial) agent combines persuasive strategies, its persuasive power increases. Therefore, we investigated whether a robot that uses two persuasive strategies is more persuasive than a robot that uses only one. Because in human face-to-face persuasion two crucial persuasive strategies are gazing and gestures, the current research investigated the combined and individual contribution of gestures and gazing on the persuasiveness of a storytelling robot. A robot told a persuasive story about the aversive consequences of lying to 48 participants. The robot used persuasive gestures (or not) and gazing (or not) to accompany this persuasive story. We assessed persuasiveness by asking participants to evaluate the lying individual in the story told by the robot. Results indicated that only gazing independently led to increased persuasiveness. Using persuasive gestures only led to increased persuasiveness when the robot combined it with (the persuasive strategy of) gazing. Without gazing, using persuasive gestures diminished robot persuasiveness. The implications of the current findings for theory and design of persuasive robots are discussed.

Making robots persuasive: the influence of combining persuasive strategies (gazing and gestures) by a storytelling robot on its persuasive power

In this paper we explore the persuasive effects of social feedback, as provided by an embodied agent, on behavioral change. In a lab setting, two experiments were conducted in which participants had the opportunity to conserve energy while carrying out washing tasks with a simulated washing machine. The experiments tested the effect of positive and negative social feedback and compared these effects to more widely used factual feedback. Results of both studies indicate that social feedback has stronger persuasive effects than factual feedback (Experiment 1) and factual-evaluative feedback (Experiment 2). In addition, an effect of feedback valence was found, demonstrating more conservation actions following negative feedback (social or factual) as compared to positive feedback. Interestingly, especially negative social feedback had the strongest persuasive effects. The predicted perceived agency effect could not be demonstrated. These findings have several implications for theory and design of persuasive robotic agents.

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Jaap Ham

Papers

Trust in smart systems: sharing driving goals and giving information to increase trustworthiness and acceptability of smart systems in cars.

Dispositional attribution: multiple inferences about motive-related traits.

Combining Robotic Persuasive Strategies: The Persuasive Power of a Storytelling Robot that Uses Gazing and Gestures

Making robots persuasive: the influence of combining persuasive strategies (gazing and gestures) by a storytelling robot on its persuasive power

Using negative and positive social feedback from a robotic agent to save energy