Optimus Primed: Media Cultivation of Robot Mental Models and Social Judgments

Mental Models of Smart Implant Technology: A Topic Modeling Approach to the Role of Initial Information and Labeling

Public understanding of medical innovations such as smart technology is decisive for its acceptance and implementation. Thus, it is important to understand what visions people develop of a technology based on initial information such as the label. We chose smart implants as an example and conducted qualitative interviews with 47 former implant patients to record their mental models after exposing them to the idea of smart implants through a vignette. Their answers were analyzed using LDA topic modeling. We derived five topics describing people's mental models considering the technology's functionalities, (dis)advantages as well as potential benefits and risks. The topics revealed that our respondents have often associated the idea of smart implants with artificial intelligence, which is a misconception regarding the introduced conceptualization. Thus, special attention has to be paid to the technology's labeling in communication efforts to ensure adequate understanding.

Robots are both anthropomorphized and dehumanized when harmed intentionally

The harm-made mind phenomenon implies that witnessing intentional harm towards agents with ambiguous minds, such as robots, leads to augmented mind perception in these agents. We conducted two replications of previous work on this effect and extended it by testing if robots that detect and simulate emotions elicit a stronger harm-made mind effect than robots that do not. Additionally, we explored if someone is perceived as less prosocial when harming a robot compared to treating it kindly. The harm made mind-effect was replicated: participants attributed a higher capacity to experience pain to the robot when it was harmed, compared to when it was not harmed. We did not find evidence that this effect was influenced by the robot's ability to detect and simulate emotions. There were significant but conflicting direct and indirect effects of harm on the perception of mind in the robot: while harm had a positive indirect effect on mind perception in the robot through the perceived capacity for pain, the direct effect of harm on mind perception was negative. This suggests that robots are both anthropomorphized and dehumanized when harmed intentionally. Additionally, the results showed that someone is perceived as less prosocial when harming a robot compared to treating it kindly.

Bias in the trauma bay: A multicenter qualitative study on team communication

BACKGROUND

Team communication and bias in and out of the operating room have been shown to impact patient outcomes. Limited data exist regarding the impact of communication bias during trauma resuscitation and multidisciplinary team performance on patient outcomes. We sought to characterize bias in communication among health care clinicians during trauma resuscitations.

METHODS

Participation from multidisciplinary trauma team members (emergency medicine and surgery faculty, residents, nurses, medical students, emergency medical services personnel) was solicited from verified level 1 trauma centers. Comprehensive semistructured interviews were conducted and recorded for analysis; sample size was determined by saturation. Interviews were led by a team of doctorate communications experts. Central themes regarding bias were identified using Leximancer analytic software (Leximancer Pty Ltd., Brisbane, Australia).

RESULTS

Interviews with 40 team members (54% female, 82% White) from 5 geographically diverse Level 1 trauma centers were conducted. More than 14,000 words were analyzed. Statements regarding bias were analyzed and revealed a consensus that multiple forms of communication bias are present in the trauma bay. The presence of bias is primarily related to sex but was also influenced by race, experience, and occasionally the leader's age, weight, and height. The most commonly described targets of bias were females and non-White providers unfamiliar to the rest of the trauma team. Most common sources of bias were White male surgeons, female nurses, and nonhospital staff. Participants perceived bias being unconscious but affecting patient care.

CONCLUSION

Bias in the trauma bay is a barrier to effective team communication. Identification of common targets and sources of biases may lead to more effective communication and workflow in the trauma bay.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

Design Metaphors for Understanding User Expectations of Socially Interactive Robot Embodiments

The physical design of a robot suggests expectations of that robot’s functionality for human users and collaborators. When those expectations align with the robot’s true capabilities, users are more likely to adopt the technologies for their intended use. However, the relationship between expectations and socially interactive robot design is not well understood. This paper applies the concept of design metaphors to robot design and contributes the Metaphors for Understanding Functional and Social Anticipated Affordances (MUFaSAA) dataset of 165 extant robots and the expectations users place on them. We used Mechanical Turk to crowd-source user expectation over three user studies. The first study (N=382) associated crowd-sourced design metaphors to different robot embodiments. The second study (N=803) assessed initial social expectations of robot embodiments. The final study (N=805) addressed the degree of abstraction of the design metaphors and the functional expectations projected on robot embodiments. We performed analyses to gain insights into how design metaphors can be used to understand social and functional expectations of robots and how these data can be visualized to be useful for study designers and robot designers. Together, these results can serve to guide robot designers toward aligning user expectations with true robot capabilities, facilitating positive human-robot interaction.

Some Assembly Required: Player Mental Models of Videogame Avatars

In playing videogames, players often create avatars as extensions of agency into those spaces, where the player-avatar relationship (PAR) both shapes gameplay and is the product of gameplay experiences. Avatars are generally understood as singular bodies; however, we argue they are functional and phenomenological assemblages-networks of social and technological components that are internalized by players as networks of knowledge about the avatar. Different PARs are based on different internalizations (i.e., mental models) for what an avatar is and why it matters. Toward illuminating nuances in PARs, we examine the content and structure of players' internalizations of avatars as evidenced by descriptions of those digital bodies. Secondary analysis of N = 1,201 avatar descriptions parceled them by PAR type (avatars as asocial Objects, psychologically merged extensions of Me, hybrid me/other Symbiotes, and authentically social Other). Aggregated descriptions for each PAR type were subjected to semantic network analysis to identify patterns in salient avatar components, and then qualitatively compared across the four PARs. Results indicate component clusters that are universal to PARs (demographics and body features), common to three of four PARs (time, appearance, clothing, and player agency), and idiosyncratic to specific PARs (significance, character narratives, game dynamics, liminality, and gratifications). Findings signal the importance of theoretically engaging avatars as assemblages both (a) influenced by player-avatar sociality and (b) that contribute (in part and whole) to antecedents, processes, and effects of gameplay.

Framing Effects on Judgments of Social Robots' (Im)Moral Behaviors

Frames—discursive structures that make dimensions of a situation more or less salient—are understood to influence how people understand novel technologies. As technological agents are increasingly integrated into society, it becomes important to discover how native understandings (i.e., individual frames) of social robots are associated with how they are characterized by media, technology developers, and even the agents themselves (i.e., produced frames). Moreover, these individual and produced frames may influence the ways in which people see social robots as legitimate and trustworthy agents—especially in the face of (im)moral behavior. This three-study investigation begins to address this knowledge gap by 1) identifying individually held frames for explaining an android’s (im)moral behavior, and experimentally testing how produced frames prime judgments about an android’s morally ambiguous behavior in 2) mediated representations and 3) face-to-face exposures. Results indicate that people rely on discernible ground rules to explain social robot behaviors; these frames induced only limited effects on responsibility judgments of that robot’s morally ambiguous behavior. Evidence also suggests that technophobia-induced reactance may move people to reject a produced frame in favor of a divergent individual frame.

From Warranty Voids to Uprising Advocacy: Human Action and the Perceived Moral Patiency of Social Robots

Moral status can be understood along two dimensions: moral agency [capacities to be and do good (or bad)] and moral patiency (extents to which entities are objects of moral concern), where the latter especially has implications for how humans accept or reject machine agents into human social spheres. As there is currently limited understanding of how people innately understand and imagine the moral patiency of social robots, this study inductively explores key themes in how robots may be subject to humans’ (im)moral action across 12 valenced foundations in the moral matrix: care/harm, fairness/unfairness, loyalty/betrayal, authority/subversion, purity/degradation, liberty/oppression. Findings indicate that people can imagine clear dynamics by which anthropomorphic, zoomorphic, and mechanomorphic robots may benefit and suffer at the hands of humans (e.g., affirmations of personhood, compromising bodily integrity, veneration as gods, corruption by physical or information interventions). Patterns across the matrix are interpreted to suggest that moral patiency may be a function of whether people diminish or uphold the ontological boundary between humans and machines, though even moral upholdings bare notes of utilitarianism.