| 1. |
- Axell, Cecilia, 1965-, et al.
(författare)
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Artificial Intelligence in Contemporary Children’s Culture : A Case Study
- 2022
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Ingår i: PATT 39. - : Memorial University of Newfoundland. - 9780889015050 ; , s. 376-386
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Konferensbidrag (refereegranskat)abstract
- The overall aim of the school subject technology is to develop pupils’ understanding of technological solutions in everyday life. A starting point for this study is that it is important for teachers in technology to have knowledge of pupils’ prior conceptions of the subject content since these can both support and hinder their learning. In a previous study we found that when pupils (age 7) talk about digital technology and programming, they often refer to out-of-school experiences such as films, television programmes and books. Typically, their descriptions include robots with some form of intelligence. Hence, it seems like children’s culture may have an impact on the conceptions they bring to the technology classroom. In light of this, it is vital that technology teachers have knowledge about how robots and artificial intelligence (AI) are portrayed in children’s culture, and how pupils perceive these portrayals. However, knowledge about these aspects of technology in children’s culture is limited.The purpose of this study is to investigate how artifacts with artificial intelligence are portrayed in television programmes and literature aimed at children. This study is the first step in a larger study aiming to examine younger pupils’ conceptions and ideas about artificial intelligence. A novice conception of artificial intelligence can be described as an understanding of what a programmed device may, or may not, “understand” in relation to a human, which includes discerning th edifferences between the artificial and the human mind. Consequently, as a theoretical framework for investigating how artificial intelligence is portrayed in children’s culture, the concepts of Theoryof Mind (ToM) and Theory of Artificial Mind (ToAM), are used. The empirical material presented in this paper, i.e. four children’s books and a popular children’s television programme, was analysed using a qualitative thematic analysis. The results show that the portrayal of AI is ambiguous. The structure and function of the robot has elements of both human and machine, and the view of the human fictional characters of the robot is sometimes that of a machine, sometimes of a human. In addition, the whole empirical material includes portrayals of AI as a threat as well as a saviour. As regards implications, there is a risk that without real-life experiences of robots, the representations children’s books and other media convey can lead to ambivalent feelings towards real robots.
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| 2. |
- Babel, Franziska, et al.
(författare)
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Cars As Social Agents (CarSA): A Perspective Shift in Human-Vehicle Interaction
- 2023
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Ingår i: PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023. - : ASSOC COMPUTING MACHINERY. - 9798400708244 ; , s. 498-499
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Konferensbidrag (refereegranskat)abstract
- The rapid advancement of autonomous vehicle (AV) technology has opened up new possibilities and challenges in the domain of human-agent interaction. As AVs become increasingly prevalent on our roads, it is crucial to understand how humans perceive and interact with these intelligent systems. This workshop aims to bring together researchers and practitioners to explore the perception of cars as social agents. We explore the shift in user perception and the implications for interactions between autonomous vehicles, human drivers, and vulnerable road users (pedestrians, cyclists, etc.). Additionally, we investigate the communication of goals and intentions between cars and humans, as well as issues related to mixed agency, stakeholder perspectives, in-vehicle avatars, and human-vehicle power dynamics. The workshop aims to uncover the benefits, risks, and design principles associated with this emerging paradigm.
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| 3. |
- Babel, Franziska, et al.
(författare)
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Cyclists' Perception of Automated Shuttle Buses in Shared Spaces
- 2023
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Ingår i: PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023. - : ASSOC COMPUTING MACHINERY. - 9798400708244 ; , s. 467-469
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Konferensbidrag (refereegranskat)abstract
- As automated shuttle buses gradually become a part of urban traffic solutions, their interactions with vulnerable road users need careful consideration. However, the cyclists' perspectives on autonomous shuttle buses have not been explored extensively. This research addresses this gap by surveying 50 cyclists who regularly encounter automated shuttle buses. The results show that, in general, cyclists exhibit a high level of trust in the safety of the buses. Nevertheless, approximately one-third of the cyclists expressed disapproval as the buses tend to drive on the bicycle lane, leading them to wish for infrastructural solutions to avoid forcing cyclists to divert to pedestrian walkways. Identifying potential conflicts like these is vital for the development of effective and acceptable human-agent interactions in road traffic environments.
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| 4. |
- Blomkvist, Johan, 1978-, et al.
(författare)
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Robots in Service Design: Consideringuncertainty in social interaction withrobots
- 2020
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Ingår i: ServDes.2020 Tensions, Paradoxes and Plurality Conference Proceedings. - : Linköping University Electronic Press. - 9789179297794 ; , s. 56-57
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- As robots become more prevalent in society, they will also become part of service systems, and will be among the materials that designers work with. The body of literature on robots in service systems is scarce, in service research as well as in service design research, especially regarding how to understand robots in service, and how design for service is impacted. In this conceptual paper we aim to shed light on how social robots will affect service. We take a look at the current state of robots’ ability to interact socially with people and highlight some of the issues that need to be considered when including social robots as part of service.In navigating the social world, people exhibit an intentional stance, in which they rely on assumptions that social behaviour is governed by underlying mental states, such as beliefs and desires. Due to fundamental differences between humans and robots, people’s attribution of the mental state of robots, such as what a particular robot knows and believes, is often precarious and leads to uncertainty in interactions, partly relating to issues with common ground. Additionally, people might hesitate to initiate interactions with robots, based on considerations of privacy and trust, or due to negative attitudes towards them. Designing for service systems where e.g. a robot is being introduced, requires knowledge and understanding of these issues from a design perspective. Service designers therefore need to consider not only the technical aspects of robots, but the specific issues that arise in interactions because of them.
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| 5. |
- Löfgren, Fredrik, 1992-, et al.
(författare)
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LetterMoose: A Handwriting Tutor Robot
- 2018
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Konferensbidrag (refereegranskat)abstract
- We present a simple robotic tutor designed to help raise handwriting competency in school-aged children. "LetterMoose" shows the steps in how a letter is formed by writing on regular piece of paper. The child is invited to imitate LetterMoose and to scan its own letters using LetterMoose in order to get evaluative feedback (both qualitative and quantitative). We propose that LetterMoose might be particularly useful for helping children with autism attain handwriting competency, as children in this group are more likely to suffer from writing difficulties and may uniquely benefit from interacting with robot technology.
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| 6. |
- Petrovych, Veronika, 1990-, et al.
(författare)
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Human Interpretation of Goal-Directed Autonomous Car Behavior
- 2018
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Ingår i: COGSCI2018 Changing / minds, 40th annual cognitive science society meeting, Madison, Wisconsin, USA, July 25-28. - Victoria, British Columbia : Cognitive Science Society. - 9780991196784 ; , s. 2235-2240
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Konferensbidrag (refereegranskat)abstract
- People increasingly interact with different types of autonomous robotic systems, ranging from humanoid social robots to driverless vehicles. But little is known about how people interpret the behavior of such systems, and in particular if and how they attribute cognitive capacities and mental states to them. In a study concerning people’s interpretations of autonomous car behavior, building on our previous research on human-robot interaction, participants were presented with (1) images of cars – either with or without a driver – exhibiting various goal-directed traffic behaviors, and (2) brief verbal descriptions of that behavior. They were asked to rate the extent to which these behaviors were intentional and judge the plausibility of different types of causal explanations. The results indicate that people (a) view autonomous car behavior as goal-directed, (b) discriminate between intentional and unintentional autonomous car behaviors, and (c) view the causes of autonomous and human traffic behaviors similarly, in terms of both intentionality ascriptions and behavior explanations. However, there was considerably lower agreement in participant ratings of the driverless behaviors, which might indicate an increased difficulty in interpreting goal-directed behavior of autonomous systems.
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| 7. |
- Rueben, Matthew, et al.
(författare)
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Half Day Workshop on Mental Models of Robots
- 2020
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Ingår i: HRI20: COMPANION OF THE 2020 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450370578 ; , s. 658-659
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Konferensbidrag (refereegranskat)abstract
- Robotic systems are becoming increasingly complex, hindering people from understanding the robots inner workings [24]. Simply providing the robots source code may be useful for software and hardware engineers who need to test the system for traceability and verification [3], but not for the non-technical user. Plus, looks can be deceiving: robots that merely resemble humans or animals are perceived differently by users [25]. This workshop aims to provide a forum for researchers from both industry and academia to discuss the users understanding or mental model of a robot: what the robot is, what it does, and how it works. In many cases it will be useful for robots to estimate each users mental model and use this information when deciding how to behave during an interaction. Designing more transparent robot actions will also be important, giving users a window into what the robot is "thinking", "feeling", and "intending". We envision a future in which robots can automatically detect and correct inaccurate mental models held by users. This workshop will develop a multidisciplinary vision for the next few years of research in pursuit of that future.
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| 8. |
- Thellman, Sam, et al.
(författare)
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A Survey of Attributions and Preferences Regarding Higher-Order Mental States in Artificial Agents
- 2023
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Ingår i: PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023. - : ASSOC COMPUTING MACHINERY. - 9798400708244 ; , s. 97-104
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Konferensbidrag (refereegranskat)abstract
- Understanding how people attribute behavior to underlying mental states is crucial to the study of human social interactions. Previous research has established that people rely on attributing mental states to interpret and interact with artificial agents. For example, a pedestrian encountering a driverless vehicle at a crosswalk might view the vehicle as knowing (or not) that there is a pedestrian in front of it. Nevertheless, little attention has been devoted to investigating people's attributions of higher-order mental states, i.e., mental states that are about the mental states of others (e.g., the vehicle's beliefs about the pedestrian's intentions). Addressing this research gap, the present study conducted a survey to explore people's attributions and preferences concerning higher-order mental states in three types of artificial agents (AI chatbot, virtual assistant, and self-driving car), alongside two human agents (participants themselves, referred to as you, and five-year-old child). The survey revealed that: (1) artificial agents, in contrast to humans, may be perceived as more likely to have higher-order mental states than first-order mental states, depending on the purpose or function of the agent; (2) people may prefer some artificial agents to have mental states of a particular order (but not others); (3) attributions and preferences regarding mental states in artificial agents do not always match. The study also contributes insights regarding the methodological challenge of constructing a survey that effectively captures participants' higher-order attributions while minimizing excessive cognitive demands. We posit that human-agent interaction research and design stand to benefit from further exploration of people's attributions and preferences regarding higher-order mental states in artificial agents.
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| 9. |
- Thellman, Sam, et al.
(författare)
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An Implicit, Non-Verbal Measure of Belief Attribution to Robots
- 2020
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Ingår i: HRI20: COMPANION OF THE 2020 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450370578 ; , s. 473-475
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Konferensbidrag (refereegranskat)abstract
- Studies of mental state attribution to robots usually rely on verbal measures. However, verbal measures are sensitive to peoples rationalizations, and the outcomes of such measures are not always reflected in a persons behavior. In light of these limitations, we present the first steps toward developing an alternative, non-verbal measure of belief attribution to robots. We report preliminary findings from a comparative study indicating that the two types of measures (verbal vs. non-verbal) are not always consistent. Notably, the divergence between the two measures was larger when the task of inferring the robots belief was more difficult.
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| 10. |
- Thellman, Sam, et al.
(författare)
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Anthropocentric Attribution Bias in Human Prediction of Robot Behavior
- 2020
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Ingår i: HRI20: COMPANION OF THE 2020 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450370578 ; , s. 476-478
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Konferensbidrag (refereegranskat)abstract
- In many types of human-robot interactions, people must track the beliefs of robots based on uncertain estimates of robots perceptual and cognitive capabilities. Did the robot see what happened and did it understand what it saw? In this paper, we present preliminary experimental evidence that people estimating what a humanoid robot knows or believes about the environment anthropocentrically assume it to have human-like perceptual and cognitive capabilities. However, our results also suggest that people are able to adjust their incorrect assumptions based on observations of the robot.
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| 11. |
- Thellman, Sam, et al.
(författare)
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Do You See what I See? Tracking the Perceptual Beliefs of Robots
- 2020
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Ingår i: iScience. - : CELL PRESS. - 2589-0042. ; 23:10
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Tidskriftsartikel (refereegranskat)abstract
- Keeping track of others perceptual beliefs-what they perceive and know about the current situation-is imperative in many social contexts. In a series of experiments, we set out to investigate peoples ability to keep track of what robots knowor believe about objects and events in the environment. To this end, we subjected 155 experimental participants to an anticipatory-looking false-belief task where they had to reason about a robots perceptual capability in order to predict its behavior. We conclude that (1) it is difficult for people to track the perceptual beliefs of a robot whose perceptual capability potentially differs significantly from human perception, (2) people can gradually "tune in" to the unique perceptual capabilities of a robot over time by observing it interact with the environment, and (3) providing people with verbal information about a robots perceptual capability might not significantly help them predict its behavior.
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| 12. |
- Thellman, Sam, et al.
(författare)
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Does Emotional State Affect How People Perceive Robots?
- 2021
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Ingår i: HRI 21: COMPANION OF THE 2021 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450382908 ; , s. 113-115
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Konferensbidrag (refereegranskat)abstract
- Emotions serve important regulatory roles in social interaction. Although recognition, modeling, and expression of emotion have been extensively researched in human-robot interaction and related fields, the role of human emotion in perceptions of and interactions with robots has so far received considerably less attention. We here report inconclusive results from a pilot study employing an affect induction procedure to investigate the effect of people's emotional state on their perceptions of human-likeness and mind in robots, as well as attitudes toward robots. We propose a new study design based on the findings from this study.
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| 13. |
- Thellman, Sam, et al.
(författare)
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Folk-Psychological Interpretation of Human vs. Humanoid Robot Behavior : Exploring the Intentional Stance toward Robots
- 2017
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Ingår i: Frontiers in Psychology. - : Frontiers Media S.A.. - 1664-1078. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- People rely on shared folk-psychological theories when judging behavior. These theories guide people's social interactions and therefore need to be taken into consideration in the design of robots and other autonomous systems expected to interact socially with people. It is, however, not yet clear to what degree the mechanisms that underlie people's judgments of robot behavior overlap or differ from the case of human or animal behavior. To explore this issue, participants (N = 90) were exposed to images and verbal descriptions of eight different behaviors exhibited either by a person or a humanoid robot. Participants were asked to rate the intentionality, controllability and desirability of the behaviors, and to judge the plausibility of seven different types of explanations derived from a recently proposed psychological model of lay causal explanation of human behavior. Results indicate: substantially similar judgments of human and robot behavior, both in terms of (1a) ascriptions of intentionality/controllability/desirability and in terms of (1b) plausibility judgments of behavior explanations; (2a) high level of agreement in judgments of robot behavior -(2b) slightly lower but still largely similar to agreement over human behaviors; (3) systematic differences in judgments concerning the plausibility of goals and dispositions as explanations of human vs. humanoid behavior. Taken together, these results suggest that people's intentional stance toward the robot was in this case very similar to their stance toward the human.
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| 14. |
- Thellman, Sam, et al.
(författare)
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He is not more persuasive than her: No gender biases toward robots giving speeches
- 2018
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Ingår i: Proceedings of the 18th International Conference on Intelligent Virtual Agents. - New York, NY, USA : ACM Digital Library. - 9781450360135 ; , s. 327-328
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Konferensbidrag (refereegranskat)abstract
- The reported study investigated three gender-related effects on the rated persuasiveness of a speech given by a humanoid robot: (1) the female or male gendered voice and visual appearance of the robot, (2) the female or male gender of the participant, and (3) the interaction between robot gender and participant gender. The study employed a measure of persuasiveness based on the Aristotelian modes of persuasion: ethos, pathos and logos. In contrast to previous studies on gender bias toward intelligent virtual agents and robots, the gender of the robot did not influence the rated persuasiveness of the speech, and female participants rated the speech as more persuasive than men overall.
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| 15. |
- Thellman, Sam, et al.
(författare)
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In the eyes of the beheld: Do people think that self-driving cars see what human drivers see?
- 2023
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Ingår i: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450399708 ; , s. 612-616
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Konferensbidrag (refereegranskat)abstract
- Safe interaction with automated vehicles requires that human road users understand the differences between the capabilities and limitations of human drivers and their artificial counterparts. Here we explore how people judge what self-driving cars versus human drivers can perceive by engaging online study participants in visual perspective taking toward a car pictured in various traffic scenes. The results indicate that people do not expect self-driving cars to differ significantly from human drivers in their capability to perceive objects in the environment. This finding is important because unmet expectations can result in detrimental interaction outcomes, such as traffic accidents. The extent to which people are able to calibrate their expectations remains an open question for future research.
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| 16. |
- Thellman, Sam, et al.
(författare)
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Lay causal explanations of human vs. humanoid behavior
- 2017
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Ingår i: Proceedings of the 17th International Conference on Intelligent Virtual Agents. - Cham : Springer. - 9783319674018 - 9783319674001 ; , s. 433-436
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Konferensbidrag (refereegranskat)abstract
- The present study used a questionnaire-based method for investigating people's interpretations of behavior exhibited by a person and a humanoid robot, respectively. Participants were given images and verbal descriptions of different behaviors and were asked to judge the plausibility of seven causal explanation types. Results indicate that human and robot behavior are explained similarly, but with some significant differences, and with less agreement in the robot case.
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| 17. |
- Thellman, Sam, et al.
(författare)
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Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is a computer < robot < human pattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are apparent contradictions in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation.
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| 18. |
- Thellman, Sam, et al.
(författare)
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Mental State Attribution to Robots: A Systematic Review of Conceptions, Methods, and Findings
- 2022
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Ingår i: ACM Transactions on Human-Robot Interaction. - : ASSOC COMPUTING MACHINERY. - 2573-9522. ; 11:4
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Forskningsöversikt (refereegranskat)abstract
- The topic of mental state attribution to robots has been approached by researchers from a variety of disciplines, including psychology, neuroscience, computer science, and philosophy. As a consequence, the empirical studies that have been conducted so far exhibit considerable diversity in terms of how the phenomenon is described and how it is approached from a theoretical and methodological standpoint. This literature review addresses the need for a shared scientific understanding of mental state attribution to robots by systematically and comprehensively collating conceptions, methods, and findings from 155 empirical studies across multiple disciplines. The findings of the review include that: (1) the terminology used to describe mental state attribution to robots is diverse but largely homogenous in usage; (2) the tendency to attribute mental states to robots is determined by factors such as the age and motivation of the human as well as the behavior, appearance, and identity of the robot; (3) there is a computer < robot < human pattern in the tendency to attribute mental states that appears to be moderated by the presence of socially interactive behavior; (4) there are conflicting findings in the empirical literature that stem from different sources of evidence, including self-report and non-verbal behavioral or neurological data. The review contributes toward more cumulative research on the topic and opens up for a transdisciplinary discussion about the nature of the phenomenon and what types of research methods are appropriate for investigation.
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| 19. |
- Thellman, Sam, et al.
(författare)
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Out of Sight, Out of Mind? Investigating People's Assumptions About Object Permanence in Self-Driving Cars
- 2023
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Ingår i: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction. - New York, NY, USA : ACM Digital Library. - 9781450399708 ; , s. 602-606
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Konferensbidrag (refereegranskat)abstract
- Safe and efficient interaction with autonomous road vehicles requires that human road users, including drivers, cyclists, and pedestrians, understand differences between the capabilities and limitations of self-driving vehicles and those of human drivers. In this study, we explore how people judge the ability of self-driving cars versus human drivers to keep track of out-of-sight objects by engaging online study participants in cognitive perspective taking toward a car in an animated traffic scene. The results indicate that people may expect self-driving cars to have similar object permanence capability as human drivers. This finding is important because unmet expectations on autonomous road vehicles can result in undesirable interaction outcomes, such as traffic accidents.
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| 20. |
- Thellman, Sam, 1989-, et al.
(författare)
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Physical vs. Virtual Agent Embodiment and Effects on Social Interaction
- 2016
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Ingår i: Intelligent Virtual Agents. - Cham : Springer. - 9783319476643 - 9783319476650 ; , s. 412-415
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Konferensbidrag (refereegranskat)abstract
- Previous work indicates that physical robots elicit more favorable social responses than virtual agents. These effects have been attributed to the physical embodiment. However, a recent meta-analysis by Li [1] suggests that the benefits of robots are due to physical presence rather than physical embodiment. To further explore the importance of presence we conducted a pilot study investigating the relationship between physical and social presence. The results suggest that social presence of an artificial agent is important for interaction with people, and that the extent to which it is perceived as socially present might be unaffected by whether it is physically or virtually present.
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| 21. |
- Thellman, Sam, et al.
(författare)
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Social attitudes toward robots are easily manipulated
- 2017
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Ingår i: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. - New York, NY, USA : ACM Digital Library. - 9781450348850 ; , s. 299-300
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Konferensbidrag (refereegranskat)abstract
- Participants in a study concerning social attitudes toward robots were randomly assigned a questionnaire form displaying a non-, semi- or highly anthropomorphic robot as a hidden intervention. Results indicate that asking people about their attitudes toward "robots" in general -- as done in some studies -- is questionable, given that (a) outcomes can vary significantly depending on the type of robot they have in mind, and (b) it is therefore easy to intentionally or unintentionally manipulate results by priming respondents with positive or negative examples.
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| 22. |
- Thellman, Sam, et al.
(författare)
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Social Attitudes Toward Robots are Easily Manipulated
- 2017
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Ingår i: HRI’17. - New York, NY, USA : ACM Digital Library. - 9781450348850 ; , s. 299-300
-
Konferensbidrag (refereegranskat)abstract
- Participants in a study concerning social attitudes toward robots were randomly assigned a questionnaire form displaying a non-, semi- or highly anthropomorphic robot as a hidden intervention. Results indicate that asking people about their attitudes toward "robots" in general -- as done in some studies -- is questionable, given that (a) outcomes can vary significantly depending on the type of robot they have in mind, and (b) it is therefore easy to intentionally or unintentionally manipulate results by priming respondents with positive or negative examples.
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| 23. |
- Thellman, Sam
(författare)
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Social Robots as Intentional Agents
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Social robots are robots that are intended for social interaction with people. Because of the societal benefits that they are expected to bring, social robots are likely to become more common. Notably, social robots may be able to perform tasks that require social skills, such as communicating efficiently, coordinating actions, managing relationships, and building trust and rapport. However, robotic systems currently lack most of the technological preconditions for interacting socially. This means that until the necessary technology is developed, humans will have to do most of the work coordinating social interactions with robots. However, social robots are a phenomenon that might also challenge the human ability to interact socially. In particular, the actions of social robots may be less predictable to the ordinary people who will interact with them than the comparable actions of humans. In anticipating the actions of other people, we commonly employ folk-psychological assumptions about what others are likely to believe, want, and intend to do, given the situation that they are in. Folk psychology allows us to make instantaneous, unconscious judgments about the likely actions of others around us, and therefore, to interact socially. However, the application of folk psychology will be challenged in the context of social interaction with robots because of significant differences between humans and robots.This thesis addresses the scope and limits of people's ability to interact socially with robots by treating them as intentional agents, i.e., agents whose behavior is most appropriately predicted by attributing it to underlying intentional states, such as beliefs and desires. The thesis provides an analysis of the problem(s) of attributing behavior-congruent intentional states to robots, with a particular focus on the perceptual belief problem, i.e., the problem of understanding what robots know (and do not know) about objects and events in the environment based on their perception. The thesis presents evidence that people's understanding of robots as intentional agents is important to their ability to interact socially with them but that it may also be significantly limited by (1) the extendability of the rich folk-psychological understanding that people have gained from sociocultural experiences with humans and other social animals to interactions with robots, and (2) the integrability of new experiences with robots into a usable and reasonable accurate folk psychological understanding of them. Studying the formation and application of folk psychology in interactions with robots should therefore be a central undertaking in social robotics research.
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| 24. |
- Thellman, Sam, et al.
(författare)
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Some Adults Fail the False-Belief Task When the Believer Is a Robot
- 2020
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Ingår i: HRI20: COMPANION OF THE 2020 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION. - New York, NY, USA : ASSOC COMPUTING MACHINERY. - 9781450370578 ; , s. 479-481
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Konferensbidrag (refereegranskat)abstract
- Peoples mental models of robots affect their predictions of robot behavior in interactions. The present study highlights some of the uncertainties that enter specifically into peoples considerations about the minds and behavior of robots by exploring how people fare in the standard "Sally-Anne" false-belief task from developmental psychology when the protagonist is a robot.
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| 25. |
- Thellman, Sam, et al.
(författare)
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The Intentional Stance Toward Robots : Conceptual and Methodological Considerations
- 2019
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Ingår i: CogSci'19. Proceedings of the 41st Annual Conference of the Cognitive Science Society. - : Cognitive Science Society, Inc.. - 0991196775 - 9780991196777 ; , s. 1097-1103
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Konferensbidrag (refereegranskat)abstract
- It is well known that people tend to anthropomorphize in interpretationsand explanations of the behavior of robots and otherinteractive artifacts. Scientific discussions of this phenomenontend to confuse the overlapping notions of folk psychology,theory of mind, and the intentional stance. We provide a clarificationof the terminology, outline different research questions,and propose a methodology for making progress in studyingthe intentional stance toward robots empirically.
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