1. Sociable Machines Cynthia Breazeal MIT Media Lab Robotic Presence Group

2. Cynthia Breazeal, MIT Media Lab Human-Robot Relations Honda’s AsimoSony’s Aibo iRobot  Types of relationships  Face to face with a robot creature  Embodied, distal interactions through a robot avatar  Augmented physicality through robotic extensions  Capable machines, untrained users, human environment  Balance human strengths with machine capabilities  Useful and enjoyable! Robotic extensions

3. Cynthia Breazeal, MIT Media Lab Robots in your everyday life Competence in: Human engineered environment Human social environment Untrained users of different Age, gender, culture, etc. Human centered design Appropriate mental model Supports what comes naturally On the job learning Easy to teach Long-term relationships Acceptance, trust

4. Cynthia Breazeal, MIT Media Lab Sociable anthropomorphic robots Very complex technology Social interface is (Reeves&Nass) Intuitive, natural Untrained users Humanoid robots are well suited to this hypothesis Same morphology, sensing Share social, communication cues HRI meets HCI Study how people want to and do interact with them. Informs design Evaluation methods

5. Cynthia Breazeal, MIT Media Lab Three research themes HCISCIENCE ROBOTICS & AI Evaluate robot compatibility with people Informed by scientific understanding of humans And animals Build robots that do real things In the real world with real people

6. Cynthia Breazeal, MIT Media Lab Issues for sociable robots today The real-world is Complex Ever-changing Robots have limited abilities compared to people Motor skills Perceptual abilities Mental abilities Imbalance in social sophistication Yet, social interaction is Tightly coupled Mutually regulated

7. Cynthia Breazeal, MIT Media Lab Early exploration into sociable humanoids Set appropriate expectations Not human Robo-baby Use of expressive feedback to regulate interaction Emotive expressions Communicative displays Paralinguistic cues Use science of natural behavior as a guide Start “simple” and learn, develop Kismet, MIT AI Lab

8. Cynthia Breazeal, MIT Media Lab Socially situated learning: A path to more capable machines? Issues for learning systems (robots or otherwise) Knowing what matters Knowing what action to try Evaluating actions Correcting errors Recognize success Structuring learning If task is pre-specified, then can do at design-time If not the case, then what? Address issues through structured social interactions Robots in a benevolent learning environment

9. Cynthia Breazeal, MIT Media Lab Learning from the way we teach

10. Cynthia Breazeal, MIT Media Lab Social skills that support learning Direct visual attention Indicates saliency (i.e.what matters) Match to human – find similar things interesting Robot responds to attention directing cues of people Robot sends feedback to person for focus of attention

11. Cynthia Breazeal, MIT Media Lab Video of attention system

12. Cynthia Breazeal, MIT Media Lab Recognize communicated reinforcement Serves as progress estimator Serves as signal for goal attainment Robot should recognize affective feedback from human Robot signal to human that intent was properly understood Social skills that support learning

13. Cynthia Breazeal, MIT Media Lab Video of communicated affect

14. Cynthia Breazeal, MIT Media Lab Communicate internal state to human Allows human to: Predict and understand robot’s behavior Tune own behavior to robot Improves quality of interaction Robot conveys internal state to human in an intuitive manner Can be used by both to establish better quality instruction Social skills that support learning

15. Cynthia Breazeal, MIT Media Lab Communication of internal state

16. Cynthia Breazeal, MIT Media Lab Regulating the interaction Provides structure to the interaction Interactive games Variations on a theme Avoid being overwhelmed or under-stimulated Turn-taking as cornerstone Human interaction Human instruction Social skills that support learning

17. Cynthia Breazeal, MIT Media Lab Video of proto-conversations

18. Cynthia Breazeal, MIT Media Lab Lessons from Kismet Face to face In human terms Human drive to animate, anthropomorphize Importance of gaze Social qualities Emotive qualities Physical interaction Being and Feeling in communication Expressive feedback is vital Entrainment and accommodation Mutual regulation Being engaged vs. interacting

19. Cynthia Breazeal, MIT Media Lab Related, ongoing directions HRI & DESIGN SCIENCE ENGINEERING Smart Puzzle Fruit HRI gaze studies Sensate Silicone Skin Organic Robots Sociable robots

20. Cynthia Breazeal, MIT Media Lab Sociable Robots Stan Winston Studios – Media Lab collaboration Next generation sociable robot Fully embodied Organic look and feel Highly expressive Socially situated learning

21. Cynthia Breazeal, MIT Media Lab Robot Avatars/Performers Stan Winston Studios – Media Lab collaboration Symbiotic control Puppeteer and “single-mind” performance Human provides content, new interfaces Robot local intelligence to perform content Physical medium for embodied interactions Visual, auditory, tactile Mobile Shared environment, reference frame Physical interactions with world and others

22. Cynthia Breazeal, MIT Media Lab Organic Robots What gives a machine a living presence? Organic qualities to make them familiar yet distinct  Intriguing blend between plant and animal  Silicone skin instead of plastic shells  Natural and expressive movement, serpentine  Visual perception of people (faces, movement, color)

23. Cynthia Breazeal, MIT Media Lab Sensate Synthetic Skin “…Perhaps next to the brain, the skin is the most important of all our organ systems.” Ashley Montagu, Touching: The Human Significance of the Skin, 1986, p.4  Sensate skin for environmental interactions  Active perception of material characteristics (hard, soft)  Development of novel conductive silicone sensor  Neuro-physiological representations

24. Cynthia Breazeal, MIT Media Lab Human-Robot Interaction Studies Controlled studies to better understand the human side of human-robot interaction  A series of studies to understand the human  Focus on the important of gaze in interaction  Compare physical (robot) verses virtual (animation)  Examine arousal and engagement through autonomic responses  To better understand the advantages and limitations of physical vs. animated media