The influence of Cultural Factors on Trust in Automation
(FA9550-13-1-0129)
The influence of Cultural Factors on Trust in
Automation(FA9550-13-1-0129)PI: Katia Sycara (Carnegie Mellon
University, USA)Co-PI: Michael Lewis (University of Pittsburgh,
USA)Co-PI: Asiye Kumru (Ozyegin University, Turkey)Co-PI: Jyi-Shane
Liu (National Chengchi University, Taiwan)
AFOSR Program Review: Trust and Influence (May 11, 2015,
Colorado Springs, CO)Research MotivationAdvantages of automation
(e.g. delivering more accurate information, lowering workload,
allowing for more rapid decisions) may not be realized due to
maladaptive use of the automation (Parasuraman and Riley 1997;
Parasuraman and Manzey 2010; Lyons and Stokes
2012)Disuse/under-reliance: the human may fail to use the
automation when it would be advantageous (e.g. ignoring or turning
off alarms)Misuse/over-reliance/complacency: human accepts
automations recommendations and/or actions when it is inappropriate
(e.g. fail to monitor automation)Abuse: inappropriate application
of automation by managers or designers.
Need for ways to ensure appropriate use of
automationTrustMultiple studies have shown that trust mediates
automation use and reliance, and in particular is involved in
automation misuse and disuse (Lee and See 1994; Lee and Moray 1992;
Muir 1988; Lewandowsky et al 2000; Merritt and Ilgen 2008)
Trust (Lee and See 2004) is an attitude that an agent
(automation or another person) will help achieve an individuals
goals in a situation characterized by uncertainty and
vulnerability.Trust has been considered to consist of a set of
attributional assumptions (trust dimensions) that range from
trustees competence to its intentionsTrust is dynamicTrust
establishmentTrust dissolution after occurrence of faultsTrust
restoration
Factors that Affect TrustCharacteristics of the
automationReliabilityNature of system
faultsPredictabilityIntelligibility and TransparencyLevel of
AutomationProperties of the OperatorPropensity to trustSelf
ConfidenceCultureEnvironmental FactorsRisk
Current LimitationsDearth of studies on the influence of culture
on trust in automation Current standardized measures for trust in
automation are lacking (ad hoc measures, conceptualizations by
analogy to interpersonal trust)Dearth of studies on the dynamics of
trust in automation
Research GoalsDevelop a fundamental understanding of general
principles and factors pertaining to dynamic trust in automation
How trust mediates reliance on automation across cultures
Research StrategyReliable psychometric instrument that captures
the nature and antecedents of trust in automation across
culturesInitial pooling of items from 3 current measures
Empirically Derived, Human-Computer Trust and SHAPE Automation
Trust IndexTrust-Sensitive Task (TST) and associated computational
and simulation infrastructure to enable replication studies of
known effects so as to allow valid cross cultural
comparisonsMulti-UAV control simulationTheoretically guided
experimental studies to determine how cultural factors affect
various aspects of trust and reliance on automationUse Hofstedes
cultural dimensions plus cultural syndromes (Dignity, Honor, Face)
(Triandis 1994;96, Cohen and Leung 2009; Leung and Cohen
2011)US-DignityTurkey-HonorTaiwan-Face
Cultural Dimensions and SyndromesDignity CulturesFound in
Western Europe and North AmericaIndependent individuals focusing on
personal goalsEgalitarian system backed up be effective system of
lawTend to make swift trust assumption, i.e. trust until proven
otherwiseHonor CulturesMiddle East, Latin America, Southern
USExternally driven self-worthEmphasis on protecting self and
family, not allowing to be taken advantage ofUnstable social
hierarchiesLow interpersonal and institutional trustFace
CulturesFar EastSelf worth extrinsically derived (what is important
is view others have of you)Power and status is relatively
hierarchical and stableSociety governed by norms, monitored and
sanctions are imposedThus little need for interpersonal trust in
general, high in-group trust
Comparison in Hofstede Cultural Dimensions
Power distance & Uncertainty avoidanceTurkey scores the
highest PD (66) and UA (85) dimensionsUnited States scores PD (40)
and UA (46)Taiwan falling in between, PD (58) and UA (69)Example
Hypotheses Process TransparencyHypothesesFace culture operators
will trust and more likely accept recommendations, even if the
underlying process is unclearDignity and Honor culture operators
will be relatively less likely to trust or accept recommendations
if the process or purpose is not well understood Honor cultures
will require greater support of trust from knowledge of process
and/or purpose than Dignity and will be prone to disuseResearch
ProductsReliable psychometric instrument that can be used across
cultures to measure trust and its antecedents. This will be made
widely available.Trust-Sensitive Task (TST) and associated
computational and simulation infrastructure will become available
to the scientific communityRecommendations and implications for
interventions and training to enable proper trust calibration of
human operators across culturesBasic Framework for Studying Trust
in Automation
Automation/environmentTrustDecisionOBSERVEMEASUREMANIPULATEFramework
for Measuring Cross-cultural Effects of TrustDisposition to
TrustIndividual/Cultural
DifferencesTrustingBeliefsTrustingIntentionsTrust
relatedBehaviorsTask variablesReliabilityRiskLOATask
contextWorkloadSubjective
measuresExperimentalmanipulationsObservedBehaviorsCross cultural
samples, Hofstedes CVS, Big 5Distinguishing Predisposition to Trust
from Trust of a Particular SystemItem pool contained items
characterizing:General attitudes towards automationItems involving
predisposition to trustI am confident in automationAttitudes across
cultural-technological contexts E.g., uncertainty avoidance or
subjective normsI feel okay using automation because it is backed
by vendor protectionsAttitudes invoked after cueing to think about
particular instances of automationThe advice GPS provided is as
good as that which a highly competent person could produce
Cross-cultures validationDemographicsJune 16, 2014AFOSR Trust
and Influence Program Review15SourcesUnited States(Army War
College)Taiwan (Chengchi Univ.)Turkey(Ozyegin Univ.)Num of
participants10012091GenderMale892946Female119145EducationHigh
school0125Undergraduate57751Graduate954215Age<
200201221~300677631~40212141~506812051~602770> 6032215The Mturk
info are shown on slide 26 15Cross-culture scale
validationReliability Test (Cronbach's alpha)June 16, 2014AFOSR
Trust and Influence Program Review16General AutoUnited States(War
College)Taiwan (Chengchi Univ.)Turkey(Ozyegin Univ.)Performance
/Ability.888.862.878Process/Integrity.869.856.855Purpose
/Benevolence.844.777.850Task contexts .704.743.800Specific
AutoUnited States(War College)Taiwan (Chengchi Univ.)Turkey(Ozyegin
Univ.)Performance
/Ability.847.859.903Process/Integrity.813.824.886Purpose
/Benevolence.809.840.887All the Cronbach's alpha values exceed the
threshold value of 0.7The Mturk reliability test are shown on slide
28
16Specific AutoMturkUnited StatesTaiwan TurkeyGermanCronbachs
AVEAVEAVEAVEAVEPerformance
0.9870.7380.8470.5870.8590.5940.9030.6750.8540.585Process
0.9620.7180.8130.5310.8240.5390.8860.6390.8830.637Purpose
0.9790.6640.8090.5160.8400.5600.8870.6420.8710.614Cross Culture
Specific Scale ValidationSuggestive threshold value- Reliability:
Cronbachs > 0.7, Validity: AVE > 0.5Cultural Differences in
Fullscale Means from SurveyAFOSR Trust and Influence Program
Review18Mean
ValuePerformProcessPurposeMturk3.824.003.83Army3.893.753.78TW3.373.463.40Turkey3.553.493.55Performance
Process Purpose MANOVA shows cultural differences
All differences Significant exceptThose circled
Additional analysescontinuingMTurk ArmyTurkey TwFramework for
Measuring Cross-cultural Effects of TrustDisposition to
TrustIndividual/Cultural
DifferencesTrustingBeliefsTrustingIntentionsTrust
relatedBehaviorsTask variablesReliabilityRiskLOATask
contextWorkloadSubjective
measuresExperimentalmanipulationsObservedBehaviorsCross cultural
samples, Hofstedes CVS, Big 5Trust Sensitive TaskStandard task(s)
for evaluating effects of trust in automation across culturesNeeds
to provide multiple tasks to produce effects such as
complacencyNeeds to accommodate manipulations known to affect
trust/trust-mediated behaviorsNeeds to be inclusive of types of
tasks used in prior research
LOW 1 The computer offers no assistance, human must take all
decisions and actions 2 The computer offers a complete set of
decision/ action alternatives, or 3 Narrows the selection down to a
few, or 4 Suggests one alternative, and 5 Executes that suggestion
if the human approves, or 6 Allows the human a restricted veto time
before automatic execution 7 Executes automatically, then
necessarily informs the human, and 8 Informs the human only if
asked, or Informs the human only if it, the computer, decides toThe
computer decides everything, acts autonomously, ignores the
humanHIGH Types of AutomationWho does it?What gets
automated?Sheridan & Verplanck 1978 10 levels of automation
(LOA)Parasuraman, Sheridan, & Wickens 2000Four stages of
processing
LOW 1 The computer offers no assistance, human must take all
decisions and actions 2 The computer offers a complete set of
decision/ action alternatives, or 3 Narrows the selection down to a
few, or 4 Suggests one alternative, and 5 Executes that suggestion
if the human approves, or 6 Allows the human a restricted veto time
before automatic execution 7 Executes automatically, then
necessarily informs the human, and 8 Informs the human only if
asked, or Informs the human only if it, the computer, decides toThe
computer decides everything, acts autonomously, ignores the
humanHIGH Levels of automation of Decision and Action Selection
(Sheridan & Verplanck, 1978) Types and Levels of Automation
(Parasuraman, Sheridan and Wickens, 2000) ClassifiersWho does
it?What gets automated?Classifier?53% reviewed papersTypical
Experiment:Parasuraman, Molloy, & Singh (1993)Monitoring gauges
with reliable/unreliablealarm for out of range readings
LOW 1 The computer offers no assistance, human must take all
decisions and actions 2 The computer offers a complete set of
decision/ action alternatives, or 3 Narrows the selection down to a
few, or 4 Suggests one alternative, and 5 Executes that suggestion
if the human approves, or 6 Allows the human a restricted veto time
before automatic execution 7 Executes automatically, then
necessarily informs the human, and 8 Informs the human only if
asked, or Informs the human only if it, the computer, decides toThe
computer decides everything, acts autonomously, ignores the
humanHIGH Levels of automation of Decision and Action Selection
(Sheridan & Verplanck, 1978) Types and Levels of Automation
(Parasuraman, Sheridan and Wickens, 2000) AdvisorWho does it?What
gets automated?Expert system/advisor?26%, some classify
&advise
Typical Experiment:Mosier, Skitka, Heers, & Burdick
(1998)Altitude, heading, & radio frequencyChanges suggested by
decision aid
LOW 1 The computer offers no assistance, human must take all
decisions and actions 2 The computer offers a complete set of
decision/ action alternatives, or 3 Narrows the selection down to a
few, or 4 Suggests one alternative, and 5 Executes that suggestion
if the human approves, or 6 Allows the human a restricted veto time
before automatic execution 7 Executes automatically, then
necessarily informs the human, and 8 Informs the human only if
asked, or Informs the human only if it, the computer, decides toThe
computer decides everything, acts autonomously, ignores the
humanHIGH Levels of automation of Decision and Action Selection
(Sheridan & Verplanck, 1978) Types and Levels of Automation
(Parasuraman, Sheridan and Wickens, 2000) ControllerWho does
it?What gets automated?Closed loop controller?17%, 5 of 7 involved
single failureTypical Experiment:Chen & Barnes 2012Path
planner- detect & replanTrust Sensitive Task for exploring
culture x manipulation interactionModifying
Cummings/Nehmeslight-weight RESCHU simulator to provide
manipulations for task variables reported to affect trust,
reliance, misuse, & disuse behaviorsTypes of
interaction:Monitoring- ComplacencyClassifying- likelihood alarm
systemNon-alerts (Miss-prone) ComplianceAlarms (FA-prone)Reliance
Warnings (FA-prone)Uncertainty avoidanceDecision Aid- path
planningautomation bias (FA-prone)Construct-focused
manipulationsPlanning transparencyTask characteristics:Workload
& Auto reliabilitySystem Feedback
25Trust Sensitive TaskPayload TaskclassifierNavigation
Taskclosed-loop oradvisorTrust SensitiveTaskReliability
workload forNavigation TaskReliabilityLOATransparency
workload forPayload TaskExperimental DesignBetween
VariablesControlIndication OnlyRe-routing OnlyIndication &
Re-routingHigh ReliabilityLow ReliabilityNavigation TaskPayload
Tasks - ClassificationCHECK: after clicking CHECK receiving a
picture with better resolution for further identifying the
existence of the target HIT: after adding a box on the suspected
target, the operator will be able to attack the targetSAFE: if the
operator believes the assigned hostile target does not exist in the
image, click SAFE to proceed with other tasks
28Payload Tasks Decision AidTarget Finder is used but the
reliability is less than perfect Based on the automated diagnosis,
the payload window will be highlighted in different colors and a
square will be added on the suspected target Red: alarm condition,
high likelihood to truly indicate the assigned targetYellow:
warning condition, higher level of uncertainty, informing the
operator that there might be the assigned targetGreen: non-alert
condition, low possibility the assigned target is included in the
image
29Payload Tasks
Indication without Re-routing
Conflict Detection is used to detect the UAV conflicts but with
imperfect reliabilityOnce conflicts are detected the area on the
map in which the conflict is predicted to occur is highlighted and
alerting messages are displayed in the status panel.Operator must
manually add waypoints to direct UAV(s) away from the conflict
Highlight the conflict spots without re-planning paths, the
operator must manually add waypoints to avoid the conflicts
31Indication Only
Re-routing without Indication
Conflict Detection is used to detect UAV conflicts and generate
new paths to resolve the conflicts. Paths follow Dubins curves
which do not match expectations for straight trajectories.
Reliability in conflict detection is imperfect.
Once a conflict is detected, new paths are automatically
generated for the UAVs and the AUTO button in the status panel
becomes available
Re-generate paths with no further auto information 33Re-routing
Only
Re-routing with Indication
Conflict detection is used to detect the UAV conflicts and
generate new paths for UAVs to avoid the conflictsTwo ways to apply
the re-plan paths:Click the Red square shown on the map and then
select Yes to apply the new pathsClick the AUTO button in the
status panel to apply the new paths
Highlight the conflict spots and re-generate paths for UAVs to
avoid the conflict 35Re-routing with Indication
Plans for Next YearStudies in US, Turkey and Taiwan, using the
TST to determine differences in disposition of trust, trust
formation, effects of trust on behavior
Publications Chien, S., Semnani-Azad, Z., Lewis, M.,&
Sycara, K. (2014). An Empirical Model of Cultural Factors on Trust
in Automation. Proceedings of the 58th Annual Meeting of the Human
Factors and Ergonomics Society, Chicago, IL., October 27-31,
2014.
Chien, S., Semnani-Azad, Z., Lewis, M.,& Sycara, K. (2014).
Towards the Development of an Inter-Cultural Scale to Measure Trust
in Automation. Proceedings of the 2014 HCI International, Crete,
Greece, June 22-27, 2014 (Best paper award)
Chien, S., Hergeth, S., Semnani-Azad, Z., Lewis, M.,&
Sycara, K. (accepted). Cross-Country Validation of a Cultural Scale
in Measuring Trust in Automation, 59th Annual Meeting of the Human
Factors and Ergonomics Society
38