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Grant: Discovery Grants Program - Individual

University of Waterloo

$73,000.00

Understanding human interaction with automated and algorithmic systems

EF 2020-21

Résumé
Autonomous systems, advanced algorithms, and artificial intelligence are emerging technologies. While these technologies aim to reduce human mental workload, if they are not designed with the user in mind these technologies can increase workload and decrease situation awareness. This proposal explores using a method from human factors engineering, Cognitive Work Analysis (CWA), to define the requirements for autonomous, algorithmic or artificially intelligent systems in ways that they assist human operators and improve human decision making. CWA is well-suited for this problem as CWA was developed to help people work better with complex system like the ones proposed here. In particular, CWA takes advantage of a strong reasoning structure and models of human information processing that advance current approaches to human interaction. Dr. Burns, as a world leader in CWA has developed the method in new directions and applied it successfully to many different domains. The research proposed here is novel and innovative, and this is the first time Cognitive Work Analysis will be applied to generate explanations from AI to operators, to directly predict how trust will change with system transparency, to predict how human operator workload will change, and to communicate intention to human operators. Dr. Burns proposes to develop and demonstrate whether CWA can achieve the following in AI, autonomous or algorithmic systems: O1)Provide a framework for improving the explanations provided to operators. O2) Predict how human operator performance changes with system transparency. O3) Improve the recognition of system intent. This research is applied in several different contexts, from financial systems, to defence systems to autonomous vehicles. The application in different contexts increases the ability of the work to have impact to industry and to the methods of human factors engineering. This work is important and will influence all new applications of advanced technology, that use algorithms or AI to make decisions. This work builds on Dr. Burns' world leading program in human factors engineering and advances Canada's position as a leader in highly effective advanced technologies.
Programme
Discovery Grants Program - Individual
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2020-07026
Name nom
Burns, Catherine
Department département
Systems Design Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
73000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
703
Area of application group en
Transportation systems and services
Area of application group fr
Services et systèmes de transport
Area of application en
Aerospace
Area of application fr
Aérospatial
Research subject code
1605
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Human factors engineering
Research subject fr
Génie des facteurs humains
Installment
inst:1-5
Partie
5
Nb partie
5
Application title
Understanding human interaction with automated and algorithmic systems
Keyword
NSERC
Application summary
Autonomous systems, advanced algorithms, and artificial intelligence are emerging technologies. While these technologies aim to reduce human mental workload, if they are not designed with the user in mind these technologies can increase workload and decrease situation awareness. This proposal explores using a method from human factors engineering, Cognitive Work Analysis (CWA), to define the requirements for autonomous, algorithmic or artificially intelligent systems in ways that they assist human operators and improve human decision making. CWA is well-suited for this problem as CWA was developed to help people work better with complex system like the ones proposed here. In particular, CWA takes advantage of a strong reasoning structure and models of human information processing that advance current approaches to human interaction. Dr. Burns, as a world leader in CWA has developed the method in new directions and applied it successfully to many different domains. The research proposed here is novel and innovative, and this is the first time Cognitive Work Analysis will be applied to generate explanations from AI to operators, to directly predict how trust will change with system transparency, to predict how human operator workload will change, and to communicate intention to human operators. Dr. Burns proposes to develop and demonstrate whether CWA can achieve the following in AI, autonomous or algorithmic systems: O1)Provide a framework for improving the explanations provided to operators. O2) Predict how human operator performance changes with system transparency. O3) Improve the recognition of system intent. This research is applied in several different contexts, from financial systems, to defence systems to autonomous vehicles. The application in different contexts increases the ability of the work to have impact to industry and to the methods of human factors engineering. This work is important and will influence all new applications of advanced technology, that use algorithms or AI to make decisions. This work builds on Dr. Burns' world leading program in human factors engineering and advances Canada's position as a leader in highly effective advanced technologies.