Mixing It Up: How Mixed Groups of Humans and Machines Modulate Conformity

This study examines to what extent mixed groups of computers and humans are able to produce conformity effects in human interaction partners. Previous studies reveal that nonhuman groups can induce conformity under certain circumstances, but it is unknown to what extent mixed groups of human and nonhuman agents are able to produce similar effects. It is also unknown how varying the number of human agents per group can affect conformity. Participants were assigned to one of five groups varying in their proportion of human to nonhuman agent composition and were asked to complete a social and analytical task with the assigned group. These task types were chosen to represent tasks which humans (i.e., social task) or computers (i.e., analytical task) may be perceived as having greater expertise in, as well as roughly approximating real-world tasks humans may complete. A mixed analysis of variance (ANOVA) revealed higher rates of conformity (i.e., percentage of time participants answered in line with their group on critical trials) with the group opinion for the analytical versus the social task. In addition, there was an impact of the ratio of human to nonhuman agents per group on conformity on the social task, with higher conformity with the group opinion as the number of humans in the group increased. No such effect was observed for the analytical task. The findings suggest that mixed groups produce different levels of conformity depending on group composition and task type. Designers of systems should be aware that group composition and task type may influence compliance and should design systems accordingly.

Under Pressure: Examining Social Conformity With Computer and Robot Groups

Objective: The authors investigate whether nonhuman agents, such as computers or robots, produce a social conformity effect in human operators and examine to what extent potential conformist behavior varies as a function of the human-likeness of the group members and the type of task that has to be performed. Background: People conform due to normative and/or informational motivations in human–human interactions, and conformist behavior is modulated by factors related to the individual as well as factors associated with the group, context, and culture. Studies have yet to examine whether nonhuman agents also induce social conformity. Method: Participants were assigned to a computer, robot, or human group and completed both a social and analytical task with the respective group. Results: Conformity measures (percentage of times participants answered in line with agents on critical trials) subjected to a 3 × 2 mixed ANOVA showed significantly higher conformity rates for the analytical versus the social task as well as a modulation of conformity depending of the perceived agent–task fit. Conclusion: Findings indicate that nonhuman agents were able to exert a social conformity effect, which was modulated further by the perceived match between agent and task type. Participants conformed to comparable degrees with agents during the analytical task but conformed significantly more strongly on the social task as the group’s human-likeness increased. Application: Results suggest that users may react differently to the influence of nonhuman agent groups with the potential for variability in conformity depending on the domain of the task.

Good Advice is Beyond All Price, but What if it Comes from a Machine?

As nonhuman agents become integrated into the workforce, the question becomes whether humans are willing to consider their advice, and to what extent advice-seeking depends on the perceived agent-task fit. To examine this, participants performed social and analytical tasks and received advice from human, robot, and computer agents in two conditions: in the Agent First condition, participants were first asked to choose advisors and were then informed which task to perform; in the Task First condition, they were first informed about the task and then asked to choose advisors. In the Agent First condition, we expected participants to prefer human to non-human advisors, and to subsequently trust their advice more if they were assigned the social as opposed to the analytical task. In the Task First condition, we expected advisor choices to be guided by stereotypical assumptions regarding the agents’ expertise for the tasks, accompanied by higher trust in their suggestions. The findings indicate that in the Agent First condition, the human was chosen significantly more often than the machines, while in the Task First condition advisor choices were calibrated based on perceived agent-task fit. Trust was higher in the social task, but only showed variations with the human partner.

Don Roberto y sus gitanos: El ensalzamiento de Robert Jordan como héroe en For Whom The Bell Tolls

This article tries to analyze the internal mechanisms by which Ernest Hemingway transforms the protagonist of his famous Spanish-war novel For Whom the Bell Tolls in the archetypical literary hero that Robert Jordan represents. My principal thesis consists in the opinion that this heroism has its origin in the difference of delineation that the author carries out upon the American combatant and the Spanish characters that surround him in the novel (by means of a latent contraposition of qualities and abilities from which the outsider will come out always as “better” for the reader). This analytical task will be carried out by approaching the different features (linguistic, physical and psychological) that Hemingway uses for the creation of his characters.Resumen: Este artículo pretende desentrañar los mecanismos internos a través de los cuales Ernest Hemingway convierte al protagonista de su famosa novela sobre la guerra civil española, For Whom the Bell Tolls, en el arquetípico héroe literario que vendrá a encarnar Robert Jordan. Mi argumento principal es que este ensalzamiento heroico tiene su origen en la diferencia delineadora que el autor efectúa sobre el brigadista americano y los personajes españoles que pueblan la novela (a través de una latente contraposición de características y habilidades de la que siempre resultará favorecido el forastero). Esta tarea analítica se llevará a cabo a través del acercamiento a los diferentes rasgos(físicos, psicológicos y lingüísticos) de los que se sirve Hemingway para la creación y modelación de sus personajes.

A Closed Circuit Technological Vision: On Minority Report, event detection, and enabling technologies

In a combined analysis, we investigate how the movie Minority Report can inform and nuance the vision of technological capacities that we identify in event detection literature. The vision in MR of an effective, pre-emptive and preventive techno-politics reflects important areas of event detection research, but it is also a vision for which the movie has become a common cultural reference. While they express similar conceptions of surveillance and technological potentials, MR also becomes a resource for discussing the broader ‘techno’-culture of event detection, showing how surveillance systems are imbued with cultural assumptions and preferences, most notably that technology has strong enabling capacities. By juxtaposing MR and event detection research, we thus demonstrate that it is an important analytical task to understand the assumptions on which such systems are constructed, as well as their social and political implications.