Responsibility in AI
Frameworks for human-AI collaboration and responsibility allocation across various sectors.
Innovating Responsibility in AI Collaboration
We clarify responsibility allocation in human-AI collaboration through multi-dimensional analysis and technical tool development, ensuring ethical and effective frameworks across various industries.
Case Studies
Our case studies validate the framework's effectiveness in healthcare, finance, and transportation sectors.
Multi-Dimensional Analysis
Analyzing legal, ethical, and technical factors influencing responsibility attribution in human-AI collaboration.
Technical Tools
Developing AI-driven tools to enhance decision-making and responsibility tracking in various sectors.
ClarifyResponsibilityAttribution:Throughascientificandfairresponsibility
allocationframework,reducetheuncertaintyofresponsibilityattributioninhuman-AI
collaborationandenhancesocialtrust.
PromoteResponsibleTechnologyApplication:Provideabasisforresponsibility
allocationintheapplicationofAItechnologyinvariousfields,promotingits
responsibledevelopment.
Cross-DomainApplicability:Throughmulti-domaincasevalidation,ensurethe
applicabilityandoperabilityoftheframeworkindifferentscenarios.
SocialImpactandPromotion:Promotetheresearchresultstorelatedfields,enhancing
society'sattentionandabilitytoaddressresponsibilityissuesinhuman-AI
collaboration.
InterdisciplinaryCollaboration:PromoteinterdisciplinarycollaborationbetweenAI
technology,law,ethics,andotherfields,drivingthedeepintegrationoftechnology
andsociety.