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Adaptive Dialog Robots: Expertise Impact and Human Perceptions

Investigating how expertise influences human responses to adaptive dialog capabilities of robots, exploring adaptation in volume, intonation, word choice, and sentence structure. The research delves into user interactions with adaptive dialog systems and the implications for robot-provided information. The study aims to understand the outcomes of robot adaptation and its effect on human perceptions.

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Adaptive Dialog Robots: Expertise Impact and Human Perceptions

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  1. The Effect of Expertise on Perceptions of a Directive Robot:The Case for Adaptive Dialog Cristen Torrey Dialog on Dialogs August 25, 2005

  2. Opportunities for Adaptation • Multiple users with varying levels of expertise or a single user over some period of time • Possibilities for adaptation • Volume • Intonation • Word Choice • Sentence Structure

  3. Research Question • What are the outcomes of adaptation (or a lack of adaptation) by robots? • (Do humans respond to robot adaptation in ways similar to human adaptation?) • Constrained problem • Robot is providing information • Adaptation is manipulating amount of detail (Semantic Elaboration)

  4. Related Work (Suggestions?) • Adaptive dialog systems • Johanna Moore • Diane Litman • Sharon Oviatt • Robotics • Cynthia Breazeal

  5. Predictions • If one needs more information and does not receive it • less successful • task is perceived to be more difficult • If one does not need more information but does receive it • performance is unaffected • speaker is perceived to be less intelligent, less responsive, less effective, etc.

  6. Experiment Design • Pre-test for expertise • 2 X 2 between-subjects design • (expertise X dialog style) • NamesOnly • Description • Task • Selection task requires subjects to choose correct object from set of 6 possible

  7. Measures • Performance measures • Time on task • Accuracy (out of 10 possible) • Number of turns • Questionnaire measures • Patronizing • Content appropriateness • Communication effectiveness • Responsiveness • Authority • Conversational control • Task ease • Task Difficulty

  8. Results: Number of Questions

  9. Results: Items Correct

  10. Experiment Two • Recalibrated the dialog • Addition of a visible timer • Monetary incentives for accuracy/speed

  11. Results: Number of Questions

  12. Results: Patronization Example: “My partner’s explanations can be condescending.” Cronbach’s alpha = .90 (4 items)

  13. Results: Conversational Effectiveness Example: “I found the conversation to be very useful and helpful.” Cronbach’s alpha = .90

  14. Results: Authority Example: Expert/Inexpert, Reliable/Unreliable Cronbach’s alpha = .72 (4 items)

  15. Marginal Effects • Task enjoyability (3 items) (p=.12) • “I enjoyed participating in this task” • Responsiveness (5 items) (p=.08) • “My partner can adapt to changing situations” • Content appropriateness (3 items) (p=.10) • “My partner’s explanations were just right for someone like me”

  16. Summary: Impact of Time • Expected results only exist under time pressure • Under pressure, people may revert to expectations they have for people

  17. Future Work • Repeated exposure (novelty effect) • Different devices, agents, etc. • New population • Older adults and negative outcomes of being “talked down to” • Lots of variability in the population

  18. Older Adults & Adaptation

  19. Tools Correct: Study Two

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