I have been away from writing on the blog, even my personal opinions on current research topics (OK, that's what almost all of this writing is) due to travel, deadlines, and other obligations. I do want to take an opportunity to announce that a new paper from the SEED research group co-authored by Dr. Francis and Behailu Bekera has just been accepted for publication in the journal Reliability Engineering and System Safety. I am very excited about this, because I enjoy reading articles from this journal, and have found this research community engaging and interesting in person, as well as on paper. I'll write a more "reflective" entry about this sometime later, but if you'd like to take a look at the paper, please find it here. We will be presenting an earlier version of this work as a thought piece at ESREL 2013. More on the conference paper closer to the date of the conference in October.
Tag: risk analysis
Robust Decision Making for Confronting Deep Uncertainties in Risk Analysis
In this post, Behailu Bekera, a 2nd-year PhD student in the SEED group discusses the role of robust decision making under deep uncertainties. This post was inspired by a reading of Louis Anthony Cox's "Confronting Deep Uncertainties in Risk Analysis" in a recent issue of Risk Analysis.
There is no one good model that can be used to assess deep uncertainties. Hence our decisions about complex systems or decision contexts are typically made based on insufficient knowledge about the situation. Deep uncertainties are characterized by multiplicity of future events and an unknown future. So, being able to precisely anticipate undesired events in the future and conducting the necessary preparations would be an example of a decision context with deep uncertainty. In this article, Tony offers recognition to ideas from robust optimization, adaptive control and machine learning that seem promising for dealing with deep uncertainties in risk analysis.
Using multiple models and relevant data to improve decisions, average forecasting, resampling data that allows robust statistical inferences despite model uncertainty, adaptive sampling and modeling, and Bayesian model averaging for statistical are some of the tools that can assist in robust risk analysis involving deep uncertainties.
The robust risk analysis techniques shift the focus of risk analysis from addressing passive aspects of it, such as identifying likelihood events (disruptions) and their associated [estimated] consequences to more action-oriented questions. Active questions such as how we should act now to effectively mitigate the occurrence or consequences of events with highly undesirable effects in the future.
Robust decision making, for instance, is used by developing countries to identify potential large-scale infrastructure development projects and investigate possible vulnerabilities that require profound attention of all stakeholders. Additionally, adaptive risk management may be used to maintain reliable network structure to ensure service continuity despite failures. This sort of techniques can be considerably important in the areas of critical infrastructure protection and resilience.
Through these emerging methods, Dr. Cox, makes important suggestions for making robust decisions in the face of extreme uncertainty in spite of our incomplete or inadequate knowledge. This will be an important paper for those looking to advance the science of robust decision-making and risk analysis.
Revisiting Stan Kaplan’s “The Words of Risk Analysis”
Recently in a SEED group paper discussion, we re-visited the words of Stan Kaplan in his 1997 "The Words of Risk Analysis." This is a transcript of a plenary lecture delivered to an Annual Meeting of the Society for Risk Analysis. SEED Ph.D. student Vikram Rao presents some highlights from this article that I'm sure you'll enjoy as well.
I enjoyed the Kaplan article. I liked how it was written in an informal style which helped the article flow well and was easy to understand. It was a good introduction to risk analysis. It asked the three questions needed for a risk assessment – What can happen?, How likely is it?, and What are the consequences? These constitute the risk triplet. The diagrams were helpful, especially the dose response curve and the evidenced based approach. And the diagrams that explained the decision making process with QRA were especially useful to get an overview of the whole process.
We need to recognize that risk assessments are going to be a bigger part of our decision making process considering the complexity of systems today. Systems such as aircraft, cars, and microprocessors have so many parts that the complexity is even bigger than before. Mitigating risks is a key to having successful complex systems. We need to be able to identify risks and have strategies for overcoming them. We can do this by eliciting expert opinions, doing simulations, and increasing our knowledge base.
We also see the rise in risks that have consequences on a national and global scale, such as global warming and climate change. By recognizing that effective risk mitigating strategies have vast importance today we can prepare ourselves well for the challenges of the future.
Short Report from #SRA2011
The SEED group is actively involved in the Society for Risk Analysis, and we take this opportunity to list a few brief highlights from this year’s meeting:
- A paper by Dr. Francis and collaborators was presented in the preference elicitation and benefits assessment symposium. The abstract is provided below.
- Dr. Francis began serving as the Chair of the Engineering and Infrastructure Specialty Group of the SRA. EISG will be emphasizing linkages with other specialty groups, while also increasing our presence in the Risk Analysis journal.
- Expert elicitation and evidence synthesis were big topics this year, and Drs. Francis and Gray will be hoping to build on this interest within the SRA by applying innovative evidence synthesis techniques to chemical risk assessment problems.
- The plenary sessions this year were excellent, including a discussion of the Deepwater Horizon oil spill by Admiral Thad Allen, and a tribute to Carnegie Mellon’s Lester Lave. Look out for class material from both of these knowledge bases to appear in Dr. Francis’s future courses