Sociable Machines

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

2. Human-Robot Relations iRobot Honda’s Asimo Sony’s Aibo Robotic extensions • 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!

3. 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. 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. Three research themes Informed by scientific understanding of humans And animals Evaluate robot compatibility with people SCIENCE HCI ROBOTICS & AI Build robots that do real things In the real world with real people

6. 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. 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. 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. Learning from the way we teach

10. 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. Video of attention system

12. Social skills that support learning • 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

13. Video of communicated affect

14. Social skills that support learning • 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

15. Communication of internal state

16. Social skills that support learning • 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

17. Video of proto-conversations

18. 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. Related, ongoing directions HRI gaze studies Smart Puzzle Fruit SCIENCE HRI & DESIGN Organic Robots ENGINEERING Sensate Silicone Skin Sociable robots

20. Sociable RobotsStan Winston Studios – Media Lab collaboration • Next generation sociable robot • Fully embodied • Organic look and feel • Highly expressive • Socially situated learning

21. Robot Avatars/PerformersStan 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. Organic RobotsWhat 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. 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. 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