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Cover Page
Title: Teach Our Robot To Dance
Investigators: Brian Scassellati, faculty; Dan Leyzberg, graduate student; Eleanor Avrunin, undergraduate student, class of 2011
Department: Computer Science
Address: 51 Prospect St., New Haven, CT 06511
Phone: 732 642 8550
Email: [email protected]
Project Period: 1 year
Research Site: Yale University, Social Robots Lab, Watson Hall, Room 400. (All investigators are affiliated with this site.)
Certifications are attached separately.
Project Description Introduction We intend to conduct a psychological experiment about human-robot interaction. We will examine whether people are better teachers/trainers (i.e. more giving of their time and more invested in the act of teaching) when they are asked to teach an emotionally-intelligent robot than when they are asked to teach an emotionally-less-sophisticated robot.
The robot we'll use is called Keepon: it's yellow, a foot tall, and shaped like two stacked tennis balls with dots for eyes and a dot for a nose. See picture to the right. It is capable of rotating side to side, leaning side to side, leaning forward and back, and squishing up and down. It can also speak (i.e. can play audio), hear (i.e. has a microphone), and see (i.e. has a camera).
We will ask our participants to teach Keepon five short dances and we will measure how many times they elect to teach each dance. There will be two experimental groups: one will see the emotionally-sophisticated robot (the treatment group), the other will see an emotionally-less-sophisticated version (the control group) but in both cases, the robot will learn at the same rate, and, in fact, no matter how well or poorly any individual participant teaches, the robot will perform the dances with the same sequence of accuracies for each participant.
Purpose
The purpose of the experiment is to find out whether people teach differently when teaching an emotionally-intelligent robot than with an emotionally-lesssophisticated one. We hypothesize that people will be better teachers in the case of the more emotionally-sophisticated robot.
Background Last year, our lab studied how people talk when they teach a robot. [1] We found that people approach robots like they do pets or other people: they talk a lot to the robot in the form of guidance, encouragement, and feedback all throughout the robot's actions. Humans-teaching-robots is a much studied field at the intersection of psychology and computer science: this research anticipates the need for robot-builders to know how people will want to teach and use the machines they build. [2-5] As artificial intelligence becomes more powerful, robots become more useful; and as robots become more useful, those that build them need to know how people can more easily control, train, and teach them.
In this experiment, we're studying whether the robot's emotional-intelligence will incentivize people to be better teachers. Throughout this document, when we refer to an "emotionally-intelligent" (or "emotionally-sophisticated") robot... we're referring specifically to this property:
Significance Knowing how people behave when they teach our robot to dance will let us generalize about better ways to build robotic assistants, teammates, and therapeutic agents of many sorts. Robots are used now to help rehabilitate stroke victims [6], help people stick to their diets [7], help elderly people cope with depression [8], and many more applications are currently in development in our lab and elsewhere. Our research will inform whether emotional-intelligence (of the sort we're implementing) ought to be part of these sorts of robot therapies.
Test Procedures Participants will be asked to teach Keepon a series of five short dances, displayed on a screen behind the robot. They will stand on a Nintendo Wii Fit Balance Board,
a white scale-like device that measures how a person is standing (i.e. whether he/she is tilting, leaning, rotating, scrunching) as a means of conducting the robot's movements. The participants will be asked to follow the dance moves on the screen in order to help the robot learn the moves. As they dance, the robot will seem like its imitating their movements. The dance moves are a series of body poses (tilting left or right, leaning forward or back, rotating left or right, or scrunching up or down). A song will last between 30 and 60 seconds, after which a score will be displayed on the screen measuring the robot's performance on that trial. Then the participant will be asked to choose whether to they want to teach that song again or move on to the next song.
Throughout this process, the robot will remark about how it feels about its learning. In the case of the emotionally-sophisticated robot, it will deliver a sequence of emotional-intelligent coping strategies to deal with its mistakes: "At least I'm getting some exercise!" (i.e. finding a silver lining), "I'll pay more attention next time, I promise." (i.e. planning to improve), "I'm so sorry!" (i.e. making amends). The less-sophisticated version will deliver these same lines, but in random order.
The experiment ends when the participant has played all five songs.
Deception The experiment requires some deception: we will tell the participants that the robot is learning from their actions, whereas, in reality the robot's behavior will be scripted and identical for all participants. In addition, during the non-dancing portions of the interaction, we will be controlling the speech of the robot from another room, secretly, in order to respond to any comments or questions that the participant may make or ask the robot. These workarounds simulate what will one day be possible with artificial intelligence.
Possible Risks To Participants We don't anticipate significant emotional or physical risks for participants in this experiment.
The physical component of this experiment has participants standing on a large platform and leaning or rotating or scrunching their bodies slightly. We don't anticipate any increased risk of bodily harm than experienced while walking or dancing.
The emotional component of this experiment has participants convinced the robot is somewhat intelligent, being that it speaks in English and can understand and respond to their questions. We don't anticipate significant emotional risk or disturbance when informing our participants that the robot was, in reality, being remotely controlled throughout the experiment.
Benefits To Participants We don't anticipate any direct benefits to participants in this experiment. This experiment is designed to discover generalizable human inclinations and preferences.
References [1] Kim, E. S., Leyzberg, D., Tsui, K. M., and Scassellati, B. 2009. How people talk when teaching a robot. In Proceedings of the 4th ACM/IEEE international Conference on Human Robot interaction (La Jolla, California, USA, March 09 - 13, 2009). HRI '09. ACM, New York, NY, 23-30. [2] Thomaz, A. L. and Breazeal, C. 2008. Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artif. Intell. 172, 6-7 (Apr. 2008), 716-737. [3] Otero, N., Saunders, J., Dautenhahn, K., and Nehaniv, C. L. 2008. Teaching robot companions: the role of scaffolding and event structuring. Connect. Sci 20, 2-3 (Jun. 2008), 111-134. [4] Chatila, R. 2008. Toward cognitive robot companions. In Proceedings of the 3rd ACM/IEEE international Conference on Human Robot interaction (Amsterdam, The Netherlands, March 12 15, 2008). HRI '08. ACM, New York, NY, 391-392. [5] Argall, B., Browning, B., and Veloso, M. 2007. Learning by demonstration with critique from a human teacher. In Proceedings of the ACM/IEEE international Conference on Human-Robot interaction (Arlington, Virginia, USA, March 10 - 12, 2007). HRI '07. ACM, New York, NY, 57-64.
[6] Mahoney, R. M., Van Der Loos, H. F., Lum, P. S., and Burgar, C. 2003. Robotic stroke therapy assistant. Robotica 21, 1 (Jan. 2003), 33-44. [7] Kidd, C. D. 2008 Designing for Long-Term Human-Robot Interaction and Application to Weight Loss. Doctoral Thesis. UMI Order Number: AAI0819995., Massachusetts Institute of Technology. [8] Heerink, M., Kröse, B., Wielinga, B., and Evers, V. 2008. Enjoyment intention to use and actual use of a conversational robot by elderly people. In Proceedings of the 3rd ACM/IEEE international Conference on Human Robot interaction. HRI '08. ACM, New York, NY, 113-120.
Subject Population
Treatment Of Data
Title: Teach Our Robot To Dance
Investigators: Brian Scassellati, faculty; Dan Leyzberg, graduate student; Eleanor Avrunin, undergraduate student, class of 2011
Department: Computer Science
Address: 51 Prospect St., New Haven, CT 06511
Phone: 732 642 8550
Email: [email protected]
Project Period: 1 year
Research Site: Yale University, Social Robots Lab, Watson Hall, Room 400. (All investigators are affiliated with this site.)
Certifications are attached separately.
Project Description Introduction We intend to conduct a psychological experiment about human-robot interaction. We will examine whether people are better teachers/trainers (i.e. more giving of their time and more invested in the act of teaching) when they are asked to teach an emotionally-intelligent robot than when they are asked to teach an emotionally-less-sophisticated robot.
The robot we'll use is called Keepon: it's yellow, a foot tall, and shaped like two stacked tennis balls with dots for eyes and a dot for a nose. See picture to the right. It is capable of rotating side to side, leaning side to side, leaning forward and back, and squishing up and down. It can also speak (i.e. can play audio), hear (i.e. has a microphone), and see (i.e. has a camera).
We will ask our participants to teach Keepon five short dances and we will measure how many times they elect to teach each dance. There will be two experimental groups: one will see the emotionally-sophisticated robot (the treatment group), the other will see an emotionally-less-sophisticated version (the control group) but in both cases, the robot will learn at the same rate, and, in fact, no matter how well or poorly any individual participant teaches, the robot will perform the dances with the same sequence of accuracies for each participant.
Purpose
The purpose of the experiment is to find out whether people teach differently when teaching an emotionally-intelligent robot than with an emotionally-lesssophisticated one. We hypothesize that people will be better teachers in the case of the more emotionally-sophisticated robot.
Background Last year, our lab studied how people talk when they teach a robot. [1] We found that people approach robots like they do pets or other people: they talk a lot to the robot in the form of guidance, encouragement, and feedback all throughout the robot's actions. Humans-teaching-robots is a much studied field at the intersection of psychology and computer science: this research anticipates the need for robot-builders to know how people will want to teach and use the machines they build. [2-5] As artificial intelligence becomes more powerful, robots become more useful; and as robots become more useful, those that build them need to know how people can more easily control, train, and teach them.
In this experiment, we're studying whether the robot's emotional-intelligence will incentivize people to be better teachers. Throughout this document, when we refer to an "emotionally-intelligent" (or "emotionally-sophisticated") robot... we're referring specifically to this property:
Significance Knowing how people behave when they teach our robot to dance will let us generalize about better ways to build robotic assistants, teammates, and therapeutic agents of many sorts. Robots are used now to help rehabilitate stroke victims [6], help people stick to their diets [7], help elderly people cope with depression [8], and many more applications are currently in development in our lab and elsewhere. Our research will inform whether emotional-intelligence (of the sort we're implementing) ought to be part of these sorts of robot therapies.
Test Procedures Participants will be asked to teach Keepon a series of five short dances, displayed on a screen behind the robot. They will stand on a Nintendo Wii Fit Balance Board,
a white scale-like device that measures how a person is standing (i.e. whether he/she is tilting, leaning, rotating, scrunching) as a means of conducting the robot's movements. The participants will be asked to follow the dance moves on the screen in order to help the robot learn the moves. As they dance, the robot will seem like its imitating their movements. The dance moves are a series of body poses (tilting left or right, leaning forward or back, rotating left or right, or scrunching up or down). A song will last between 30 and 60 seconds, after which a score will be displayed on the screen measuring the robot's performance on that trial. Then the participant will be asked to choose whether to they want to teach that song again or move on to the next song.
Throughout this process, the robot will remark about how it feels about its learning. In the case of the emotionally-sophisticated robot, it will deliver a sequence of emotional-intelligent coping strategies to deal with its mistakes: "At least I'm getting some exercise!" (i.e. finding a silver lining), "I'll pay more attention next time, I promise." (i.e. planning to improve), "I'm so sorry!" (i.e. making amends). The less-sophisticated version will deliver these same lines, but in random order.
The experiment ends when the participant has played all five songs.
Deception The experiment requires some deception: we will tell the participants that the robot is learning from their actions, whereas, in reality the robot's behavior will be scripted and identical for all participants. In addition, during the non-dancing portions of the interaction, we will be controlling the speech of the robot from another room, secretly, in order to respond to any comments or questions that the participant may make or ask the robot. These workarounds simulate what will one day be possible with artificial intelligence.
Possible Risks To Participants We don't anticipate significant emotional or physical risks for participants in this experiment.
The physical component of this experiment has participants standing on a large platform and leaning or rotating or scrunching their bodies slightly. We don't anticipate any increased risk of bodily harm than experienced while walking or dancing.
The emotional component of this experiment has participants convinced the robot is somewhat intelligent, being that it speaks in English and can understand and respond to their questions. We don't anticipate significant emotional risk or disturbance when informing our participants that the robot was, in reality, being remotely controlled throughout the experiment.
Benefits To Participants We don't anticipate any direct benefits to participants in this experiment. This experiment is designed to discover generalizable human inclinations and preferences.
References [1] Kim, E. S., Leyzberg, D., Tsui, K. M., and Scassellati, B. 2009. How people talk when teaching a robot. In Proceedings of the 4th ACM/IEEE international Conference on Human Robot interaction (La Jolla, California, USA, March 09 - 13, 2009). HRI '09. ACM, New York, NY, 23-30. [2] Thomaz, A. L. and Breazeal, C. 2008. Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artif. Intell. 172, 6-7 (Apr. 2008), 716-737. [3] Otero, N., Saunders, J., Dautenhahn, K., and Nehaniv, C. L. 2008. Teaching robot companions: the role of scaffolding and event structuring. Connect. Sci 20, 2-3 (Jun. 2008), 111-134. [4] Chatila, R. 2008. Toward cognitive robot companions. In Proceedings of the 3rd ACM/IEEE international Conference on Human Robot interaction (Amsterdam, The Netherlands, March 12 15, 2008). HRI '08. ACM, New York, NY, 391-392. [5] Argall, B., Browning, B., and Veloso, M. 2007. Learning by demonstration with critique from a human teacher. In Proceedings of the ACM/IEEE international Conference on Human-Robot interaction (Arlington, Virginia, USA, March 10 - 12, 2007). HRI '07. ACM, New York, NY, 57-64.
[6] Mahoney, R. M., Van Der Loos, H. F., Lum, P. S., and Burgar, C. 2003. Robotic stroke therapy assistant. Robotica 21, 1 (Jan. 2003), 33-44. [7] Kidd, C. D. 2008 Designing for Long-Term Human-Robot Interaction and Application to Weight Loss. Doctoral Thesis. UMI Order Number: AAI0819995., Massachusetts Institute of Technology. [8] Heerink, M., Kröse, B., Wielinga, B., and Evers, V. 2008. Enjoyment intention to use and actual use of a conversational robot by elderly people. In Proceedings of the 3rd ACM/IEEE international Conference on Human Robot interaction. HRI '08. ACM, New York, NY, 113-120.
Subject Population
Treatment Of Data
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