TY - GEN
T1 - Understanding formal aggregation of expert assessments in safety decision making
AU - Stephen, Cynthia
AU - Salado, Alejandro
AU - Kannan, Hanumanthrao
N1 - Publisher Copyright:
Copyright, American Society for Engineering Management, 2020.
PY - 2020
Y1 - 2020
N2 - Expert assessment is critical to safety decision making. Expert assessment is used to interpret, qualify, or complement historical data when characterizing uncertainties related to safety. When historical records are not available, uncertainty characterization relies solely on the experts’ assessment. Because safety of engineered systems is a multidisciplinary problem, decision makers need to reason through the information provided by several experts. Past work on expert aggregation in engineering management has focused on using multiple behavioral and mathematical aggregation techniques that are subjective in nature and lack the rigor to reason about the individual assessments in a mathematically consistent manner. In this paper, we leverage work from the fields of business management, economics, and cybernetics to present different techniques to mathematically aggregate expert assessment. We differentiate between expertise provided through three different information mechanisms: belief distributions, opinions, and judgements. We show that these three forms of expert information inherently require different aggregation. In fact, we demonstrate that most of the existing techniques for expert aggregation can actually lead to misusing expertise.
AB - Expert assessment is critical to safety decision making. Expert assessment is used to interpret, qualify, or complement historical data when characterizing uncertainties related to safety. When historical records are not available, uncertainty characterization relies solely on the experts’ assessment. Because safety of engineered systems is a multidisciplinary problem, decision makers need to reason through the information provided by several experts. Past work on expert aggregation in engineering management has focused on using multiple behavioral and mathematical aggregation techniques that are subjective in nature and lack the rigor to reason about the individual assessments in a mathematically consistent manner. In this paper, we leverage work from the fields of business management, economics, and cybernetics to present different techniques to mathematically aggregate expert assessment. We differentiate between expertise provided through three different information mechanisms: belief distributions, opinions, and judgements. We show that these three forms of expert information inherently require different aggregation. In fact, we demonstrate that most of the existing techniques for expert aggregation can actually lead to misusing expertise.
KW - Belief aggregation
KW - Discursive dilemma
KW - Expert aggregation
KW - Judgement aggregation
KW - Safety risk assessment
UR - http://www.scopus.com/inward/record.url?scp=85101633890&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101633890&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85101633890
T3 - ASEM 41st International Annual Conference Proceedings "Leading Organizations through Uncertain Times"
BT - ASEM 41st International Annual Conference Proceedings "Leading Organizations through Uncertain Times"
A2 - Keathley, H.
A2 - Enos, J.
A2 - Parrish, M.
PB - American Society for Engineering Management
T2 - 41st International Annual Conference of the American Society for Engineering Management: Leading Organizations through Uncertain Times
Y2 - 28 October 2020 through 30 October 2020
ER -