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9/29/01Human-Robot Interaction Ecce Homo: Why It’s Great to be Labeled a “Person” Clifford Nass Stanford University.

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Presentation on theme: "9/29/01Human-Robot Interaction Ecce Homo: Why It’s Great to be Labeled a “Person” Clifford Nass Stanford University."— Presentation transcript:

1 9/29/01Human-Robot Interaction Ecce Homo: Why It’s Great to be Labeled a “Person” Clifford Nass Stanford University

2 9/29/01Human-Robot Interaction Three Stories Robot best friend Shylock –Bleed –Tickle –Poison –Eyes, hands, organs, dimensions, senses, affections, passions Dred Scott case

3 9/29/01Human-Robot Interaction Lessons to be Learned “Human” is nothing more than a label “Human”: not ontological “Human”: psychological and social

4 9/29/01Human-Robot Interaction Does the Label Matter? Not philosophical question Is experimental question

5 9/29/01Human-Robot Interaction Humor — Findings –Funny people are: Smarter More likable More friendly Does not harm performance –Even applies in task situations

6 9/29/01Human-Robot Interaction Humor — Variables –Independent variables Successful humor vs. no humor HCI vs. CMC –Dependent variables Perception of interactant Behavior Smiling responses

7 9/29/01Human-Robot Interaction Likable

8 9/29/01Human-Robot Interaction Cooperation

9 9/29/01Human-Robot Interaction Actual Task Time

10 9/29/01Human-Robot Interaction Joking

11 9/29/01Human-Robot Interaction Smiling

12 9/29/01Human-Robot Interaction Humor — Implications Profoundly human behaviors are acceptable on computers People will be verbally friendly to computers CMC is basically the same, but –More jokes –More smiles! Cognitive construction of person

13 9/29/01Human-Robot Interaction Adaptation: Findings Humans: Adaptation is universal Computers: Adaptation is uncommon –Hard problem –Focus on Technology Precision of measurement

14 9/29/01Human-Robot Interaction Possible processes Social facilitation –Confident people do better when observed –Non-confident people do worse Stress –Opposite of social facilitation Which explanation applies to: –human-computer interaction? –Human-human interaction?

15 9/29/01Human-Robot Interaction Method Computer-based GRE (same for everyone) IVs –Confidence in prior GRE performance High Low –Adaptation No adaptation Ostensibly adapts based on previous questions

16 9/29/01Human-Robot Interaction Performance on the GRE CMC

17 9/29/01Human-Robot Interaction Performance on the GRE HCI

18 9/29/01Human-Robot Interaction Performance on the GRE

19 9/29/01Human-Robot Interaction Implications Human label influences response to adaptation –Social facilitation in CMC –Choking in HCI Rarity effects?

20 9/29/01Human-Robot Interaction Animated Representations Conformity pressure is powerful –Informative –Normative Appearance is powerful

21 9/29/01Human-Robot Interaction Method Choice-dilemma questionnaire Representation –Text box –Stick figure –Rich animated figure (Ostensible) Interactant –HCI –CMC

22 9/29/01Human-Robot Interaction Traditional CMC

23 9/29/01Human-Robot Interaction Animated “People”

24 9/29/01Human-Robot Interaction Intelligence of Agent

25 9/29/01Human-Robot Interaction Public Conformity

26 9/29/01Human-Robot Interaction Implications Representation matters in HCI Representation matters in CMC! –Was that the mental construction? TTS evidence –Can’t draw general conclusions about faces, characters, etc. CMC exerts great social influence

27 9/29/01Human-Robot Interaction Visible Agents What happens when agents are indistinguishable from humans? –Distinction disappears or –Label makes a difference Expectancy Theory: Everything should match its label

28 9/29/01Human-Robot Interaction Labeling: Findings Expectation of consistency with label –Better than expected: Great! –Worse than expected: Awful!

29 9/29/01Human-Robot Interaction Demo Human Slide51.human.movSlide51.human.mov or Synthetic Slide51.synthetic.movSlide51.synthetic.mov

30 9/29/01Human-Robot Interaction Context Auction Site Human-looking or agent-looking “Human” or “Agent”

31 9/29/01Human-Robot Interaction Bidding Behavior

32 9/29/01Human-Robot Interaction Implications Labels matter Appearance matters Humans are held to higher standard

33 9/29/01Human-Robot Interaction Summary – Part I Turning Turing Test on its head –“Human” is not ontological –Not “Is it human” but “if it’s human, now what?” HCI does NOT equal social interaction But what about “Media Equation”? –Cognitive construction may be at the critical determinant

34 9/29/01Human-Robot Interaction Final Question Will robots ever be labeled “human”?


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