1. Human trust in technology and etiquette
John D. Lee & Katrina See
Department of Mechanical and Industrial Engineering
University of Iowa
Sponsored by NSF Grant IIS

2. Beyond theoretical importance
Misues/disuse
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3. Affect, decision making, and reliance
Damasio (1994): Neurological basis for affect as a key element in effective decision making
Norman (2002): Affect and cognition interact with technology to influence behavior
Picard (1997): Affective computing can enhance acceptance and performance
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4. Strange case of Phineus Gage
Left intellectual abilities intact,
but greatly impaired decision making
and emotional response
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5. Affect, decision making, and reliance
Kramer (1999) Trust as an important social decision heuristic in organizations
Nass (1996): People respond to technology as they do people
Zuboff (1987): Operators report role of trust on reliance in working with computerized controllers
Lee & Moray (1992): Trust influences reliance on automation
Trust: a critical social lubricant that mitigates the cognitive complexity of increasingly unstructured relationships
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6. Trust in technology?
Trust: An attitude that reflects a person’s expectation that technology will achieve his or her goals based on:
Performance of the system (What it has done)
Process that governs operation (How it works)
Purpose of the design (Why is was created)
Similar to trust between people?
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7. Belief Attitude Intention Behavior
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8. Calibration and resolution of trust
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9. Calibration of trust in automation
Consider cognitive complexity and social constraints to support trustable behavior (make algorithm understandable)
Reveal behavior to calibrate trust (make behavior understandable)
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10. An experiment with a supervisory control microworld
Evaluate role of sonification in calibrating trust to enhance supervisory control
Investigate individual differences in trusting tendency
“it sounded ‘hollow’ and didn’t feel right so we got out”
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11. Pasteurization plant microworld
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12. (Length indicative of severity of fault)
Day One
Day Two
Day Three
This is what the experiment looked like. The increasing columns indicate an increasing severity in fault. Day one was training. The participants were also randomly assigned order. Some would experience the manual fault first, then the automatic fault. Some otherwise. The first day was for training.
Auto. Fault
Man. Fault
No fault
(Length indicative of severity of fault)
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13. Performance as a function of sound and automatic controller fault
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14. Sonification and reliance during automatic controller faults
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15. Sonification and trust during automatic pump controller faults
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16. Increasingly complex automation and human-automation interactions
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17. Conclusions
Trust influences reliance as an attitude in the context of beliefs, attitudes, intentions, and behavior. Reliance is not a good measure of trust
Designers should focus on calibrating trust not enhancing trust
Trust calibration may depend on the design of the algorithm and feedback
Systems that mimic human characteristics, may lead to inappropriate trust as human characteristics lead to false expectations
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18. Layers of etiquette Pragmatic (communicate, co Role identification
Empathetic, affective
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19. Thoughts? Mapping function to define system etiquette Human Etiquette
Machine Etiquette
System Etiquette
Layers of Etiquette
Pragmatic
Role specification
Empathetic/affective
Level of abstraction in etiquette translation
Literal vs. figurative
Functional vs. physical
Mapping function to define system etiquette
“Please, can I interrupt”
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