In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

The power of feedback.

Статья посвящена вопросам влияния власти на поведение человека. Авторы рассматривают данные различных источников, в которых увеличение власти связывается с напористостью, а ее уменьшение - с подавленностью. Конкретно, власть ассоциируется с: а) позитивным аффектом; б) вниманием к вознаграждению и к свойствам других, удовлетворяющим личные цели; в) автоматической переработкой информации и резкими суждениями; г) расторможенным социальным поведением. Уменьшение власти, напротив, ассоциируется с: а) негативным аффектом; б) вниманием к угрозам и наказаниям, к интересам других и к тем характеристикам я, которые отвечают целям других; в) контролируемой переработкой информации и совещательным типом рассуждений; г) подавленным социальным поведением. Обсуждаются также последствия этих паттернов поведения, связанных с властью, и потенциальные модераторы.

Power, approach, and inhibition. Власть, напористость и подавленность

人教版高中英语新课程教材中,语言运用（Using Language）是每个单元必不可少的部分,提供了围绕单元中心话题的听、说、读、写的综合性练习,是单元中心话题的延续和升华.如何设计Using Language部分的教学,使自己的教学模式既不落俗套,又能真正体现新课程标准所倡导的教学理念,正是广大一线英语教师一直努力探索的问题.

打磨Using Language,倡导新理念

The problem of which cues, internal or external, permit a person to label and identify his own emotional state has been with us since the days that James (1890) first tendered his doctrine that \"the bodily changes follow directly the perception of the exciting fact, and that our feeling of the same changes as they occur is the emotion\" (p. 449). Since we are aware of a variety of feeling and emotion states, it should follow from James' proposition that the various emotions will be accompanied by a variety of differentiable bodily states. Following James' pronouncement, a formidable number of studies were undertaken in search of the physiological differentiators of the emotions. The results, in these early days, were almost uniformly negative. All of the emotional states experi-

"Cognitive, social, and physiological determinants of emotional state": Erratum

The introduction of artificial teammates in the form of autonomous social robots, with fewer social abilities compared to humans, presents new challenges for human–robot team dynamics. A key characteristic of high performing human-only teams is their ability to establish, develop, and calibrate trust over long periods of time, making the establishment of longitudinal human–robot team trust calibration a crucial part of these challenges. This paper presents a novel integrative model that takes a longitudinal perspective on trust development and calibration in human–robot teams. A key new proposed factor in this model is the introduction of the concept relationship equity. Relationship equity is an emotional resource that predicts the degree of goodwill between two actors. Relationship equity can help predict the future health of a long-term relationship. Our model is descriptive of current trust dynamics, predictive of the impact on trust of interactions within a human–robot team, and prescriptive with respect to the types of interventions and transparency methods promoting trust calibration. We describe the interplay between team trust dynamics and the establishment of work agreements that guide and improve human–robot collaboration. Furthermore, we introduce methods for dampening (reducing overtrust) and repairing (reducing undertrust) mis-calibrated trust between team members as well as methods for transparency and explanation. We conclude with a description of the implications of our model and a research agenda to jump-start a new comprehensive research program in this area.

Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams

In this paper we demonstrate that it is possible to help individuals regulate their emotions with mobile interventions that leverage the way we naturally react to our bodily signals. Previous studies demonstrate that the awareness of our bodily signals, such as our heart rate, directly influences the way we feel. By leveraging these findings we designed a wearable device to regulate user's anxiety by providing a false feedback of a slow heart rate. The results of an experiment with 67 participants show that the device kept the anxiety of the individuals in low levels when compared to the control group and the other conditions. We discuss the implications of our findings and present some promising directions for designing and developing this type of intervention for emotion regulation.

https://dl.acm.org/doi/pdf/10.1145/2971648.2971752

EmotionCheck: leveraging bodily signals and false feedback to regulate our emotions

Persuasive technologies aim to influence user's behaviors. In order to be effective, many of the persuasive technologies developed so far relies on user's motivation and ability, which is highly variable and often the reason behind the failure of such technology. In this paper, we present the concept of Mindless Computing, which is a new approach to persuasive technology design. Mindless Computing leverages theories and concepts from psychology and behavioral economics into the design of technologies for behavior change. We show through a systematic review that most of the current persuasive technologies do not utilize the fast and automatic mental processes for behavioral change and there is an opportunity for persuasive technology designers to develop systems that are less reliant on user's motivation and ability. We describe two examples of mindless technologies and present pilot studies with encouraging results. Finally, we discuss design guidelines and considerations for developing this type of persuasive technology.

Mindless computing: designing technologies to subtly influence behavior

Human-robot interaction (HRI) research to date has been dominated by laboratory studies, largely examining a single human interacting with a single robot. This research has helped establish a fundamental understanding about people as they interact with robots, how specific design choices affect interactions with robots, and how novel mechanisms or computational tools can be used to improve HRI. The predominant focus of this growing body of work, however, stands in stark contrast to the complex social contexts in which robots are increasingly placed. Developments in machine learning and tele-robotics, as well as compliant and social robotics, have occasioned more robots in closer proximity and even direct contact with people. Robots, especially mobile autonomous robots, are now deployed across work contexts and “sociable robots” such as Jibo, Cozmo, Kuri, and M.A.X. are increasingly becoming staples of household technology. These robots interact with people in everyday contexts across a wide range of tasks and situations, yet our research reflects a time when studies of HRI were possible almost exclusively only in laboratory settings. As a result, we have a limited understanding of how people will respond to robots in complex social settings and how robots will affect social dynamics in situ. In particular, our theories reflect an oversimplified view of HRI. The time is ripe for studies that tackle HRI in these complex settings and build generalizable theories about what to expect of HRI in the wild. Although there is much to be learned in controlled laboratory settings and they should continue to be a mainstay of HRI studies, we argue that more HRI researchers need to venture into the

https://dl.acm.org/doi/pdf/10.1145/3208975

Robots in the Wild: A Time for More Robust Theories of Human-Robot Interaction

Participating in interaction requires not only coordination on content and process, as previously proposed, but also on affect. The term affective grounding is introduced to refer to the coordination of affect in interaction with the purpose of building shared understanding about what behavior can be exhibited, and how behavior is interpreted emotionally and responded to. Affective Ground is achieved when interactants have reached shared understanding about how behavior should be interpreted emotionally. The paper contributes a review and critique of current perspectives on emotion in HRI. Further it outlines how research on emotion in HRI can benefit from taking an affective grounding perspective and outlines implications for the design of robots capable of participating in the coordination on affect in interaction.

https://dl.acm.org/doi/pdf/10.1145/2909824.3020224

Malte F. Jung

Papers

Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams

EmotionCheck: leveraging bodily signals and false feedback to regulate our emotions

Mindless computing: designing technologies to subtly influence behavior

Robots in the Wild: A Time for More Robust Theories of Human-Robot Interaction

Affective Grounding in Human-Robot Interaction