TY - JOUR
T1 - For nanotechnology decisions, use decision analysis
AU - Linkov, Igor
AU - Bates, Matthew E.
AU - Trump, Benjamin D.
AU - Seager, Thomas
AU - Chappell, Mark A.
AU - Keisler, Jeffrey M.
N1 - Funding Information:
Dr. Thomas P. Seager's research interests are related to environmental decision analysis, and the life-cycle environmental impacts of alternative energy technologies. He is currently leading a project funded by the National Science Foundation that applies game theory to develop new strategies for teaching ethical reasoning skills relevant to sustainability to science and engineering graduate students. He joined the School of Sustainable Engineering and the Built Environment at Arizona State University in 2010. His formal education is in Civil and Environmental Engineering, in which he earned his Ph.D. from Clarkson University in 2001.
PY - 2013/2
Y1 - 2013/2
N2 - Management of nanotechnology is rife with complicated, contentious, and risky decisions. These decisions involve significant uncertainty, multiple stakeholder groups, competing objectives, and dynamic, non-linear interdependencies which test the limits of unaided human judgment. In the past, formal methods of risk analysis have been used to evaluate new technologies, but these methods ignore decision-relevant qualitative information and rely on a volume of quantitative engineering and scientific data that simply does not exist for many nanomaterials. Yet, we know that robust production decisions need to be holistic and based on all available information if we are to minimize negative externalities to society, human health, and the environment. We discuss how the use of decision analytical methods such as Multi-Criteria Decision Analysis and value of information analysis can help to fill existing gaps in nanomaterial risk management to make the best use of all available qualitative and quantitative information and prioritize future research based on expected decision relevance. This will help nanoparticle scientists and manufacturers to better develop and identify optimal materials and production methods in the midst of high uncertainty.
AB - Management of nanotechnology is rife with complicated, contentious, and risky decisions. These decisions involve significant uncertainty, multiple stakeholder groups, competing objectives, and dynamic, non-linear interdependencies which test the limits of unaided human judgment. In the past, formal methods of risk analysis have been used to evaluate new technologies, but these methods ignore decision-relevant qualitative information and rely on a volume of quantitative engineering and scientific data that simply does not exist for many nanomaterials. Yet, we know that robust production decisions need to be holistic and based on all available information if we are to minimize negative externalities to society, human health, and the environment. We discuss how the use of decision analytical methods such as Multi-Criteria Decision Analysis and value of information analysis can help to fill existing gaps in nanomaterial risk management to make the best use of all available qualitative and quantitative information and prioritize future research based on expected decision relevance. This will help nanoparticle scientists and manufacturers to better develop and identify optimal materials and production methods in the midst of high uncertainty.
KW - Decision analysis
KW - Green nano manufacturing
KW - Health and safety
KW - Risk
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U2 - 10.1016/j.nantod.2012.10.002
DO - 10.1016/j.nantod.2012.10.002
M3 - Article
AN - SCOPUS:84874513396
SN - 1748-0132
VL - 8
SP - 5
EP - 10
JO - Nano Today
JF - Nano Today
IS - 1
ER -