Modeling uncertainty in neural networks with TensorFlow Probability | by Aleksander Molak | Nov, 2021. Hands-on Tutorials Part 2: Aleatoric uncertainty This series is a brief introduction to modeling uncertainty using TensorFlow Probability library. I wrote it as a supplementary material to my PyData Global 2021 talk on uncertainty estimation in neural networks. Part 1 can be found here. Introduction In the first part of the series we talked about motivations behind modeling uncertainty and introduced the basics of TensorFlow Probability (TFP). What is aleatoric uncertainty?
Aleatoric uncertainty represents unpredictable differences in outcomes when we repeat the same experiment with exactly the same settings many times. The word aleatoric comes from Latin alea /ˈaː.le.a/ originally meaning “joint-bone” or “pivot-bone”. Perhaps the most important fact about aleatoric uncertainty is that it cannot be reduced by adding more data⁰. Let’s see an example. Imagine two robots. We said that aleatoric uncertainty represents differences in outcomes when we repeat the same experiment many times.
Summary. Hazard and Risk. The meaning of the word hazard can be confusing. Often dictionaries do not give specific definitions or combine it with the term "risk". For example, one dictionary defines hazard as "a danger or risk" which helps explain why many people use the terms interchangeably. There are many definitions for hazard but the most common definition when talking about workplace health and safety is: A hazard is any source of potential damage, harm or adverse health effects on something or someone. Basically, a hazard is the potential for harm or an adverse effect (for example, to people as health effects, to organizations as property or equipment losses, or to the environment). Sometimes the resulting harm is referred to as the hazard instead of the actual source of the hazard.
Risk Management Is Project Management for Adults - Henrico Dolfing. The title of this article is a quote from Tim Lister, and is a universal principle for the success of any project in the presence of uncertainty. All software development projects are subject to risk and uncertainty because they are unique, constrained, based on assumptions, performed by people and subject to external influences. Risks can affect the outcome of projects either positively or negatively. “If There’s No Risk On Your Next Project, Don’t Do It” Greater risk brings greater reward, especially in software development. Positive Risk Risk includes both opportunities and threats. There are many examples of positive risks in projects: you could deliver the project early; you could discover that the problem is easier to solve as expected; you could re-use your solution for other problems; you could acquire more customers than you accounted for; you could imagine how a delay in shipping might open up a potential window for better marketing opportunities, etc.
Risk or Uncertainty? Risk management: Uncertainty, tradeoffs and decision-making. Home - CGE Risk Management Solutions. Free courseware on risk engineering and safety management. The Uncertainty Created by the Risk Management Definition - Paladin Risk Management Services | Providing extensive risk management consultancy and training services. Okay –this might be controversial – but as a risk management professional – I truly dislike the risk management definition. There I said it!!!!!!! I believe the effect of uncertainty of objectives has actually created uncertainty within the risk management fraternity since its release in 2009.
Let me take you back to the good old days of AS/NZS 4360:2004 which defined a risk as a chance of something happening that will have an impact on objectives. This definition had it all – something happening (an event), a chance (Likelihood) and an impact (Consequence). I am afraid, however, the current definition does not give us the same clarity. Let’s break it down: The effect of uncertainty on objectives. Effect is defined as “a change which is a result or consequence of an action or other cause”. So what does this mean? A little known ISO document also released in 2009 is ISO Guide 73:2009. This is where it gets really funky………… So what do we have now? Cox’s risk matrix theorem and its implications for project risk management. Introduction One of the standard ways of characterising risk on projects is to use matrices which categorise risks by impact and probability of occurrence.
These matrices provide a qualitative risk ranking in categories such as high, medium and low (or colour: red, yellow and green). Such rankings are often used to prioritise and allocate resources to manage risks. There is a widespread belief that the qualitative ranking provided by matrices reflects an underlying quantitative ranking. In a paper entitled, What’s wrong with risk matrices? , Tony Cox shows that the qualitative risk ranking provided by a risk matrix will agree with the quantitative risk ranking only if the matrix is constructed according to certain general principles. Since the content of this post may seem overly academic to some of my readers, I think it is worth clarifying why I believe an understanding of Cox’s principles is important for project managers.
Background and preliminaries Figure 1: A 3x3 Risk Matrix. Keys To Success In Managing A Black Swan Event. Root Cause Identification & Role of Risk Management - Learnaboutgmp: Accredited Online Life Science Training Courses. Risk Monitoring: 6 Considerations for Understanding this Make or Break Moment for ERM - Carol Williams. Epistemic, ontological and aleatory risk « Critical Uncertainties. What do an eighteenth century mathematician and a twentieth century US Secretary of Defence have to do with engineering and risk? The answer is that both thought about uncertainty and risk, and the differing definitions that they arrived at neatly illustrate that there is more to the concept of risk than just likelihood multiplied by consequence.
Which in turn has significant implications for engineering risk management. Editorial note. I’ve pretty much completely revised this post since the original, hope you like it The concept of risk allows us to make decisions in an uncertain world where we cannot perfectly predict future outcomes. Which leads us to the point that Secretary Rumsfeld was making, that uncertainty is a continuum that ranges from that which we are certain of at one end through to that which we are completely ignorant of at the other.
Aleatory uncertainty At one end of the spectrum of knowing we have those things that we know and are confident we know. Notes 1. 2. 3. 4. What are the 12 Key Elements of a Project Risk Register Template? Your Project Risk Register Template is a handy tool to add structure and consistency to your project risk management process. Using this template framework puts you in the lead to quickly and easily carry out a complete risk management process. You identify, assess and treat risks, and bring your project team and stakeholders along on the journey.
Here are the 12 key elements of a Project Risk Register template together with some examples to help you understand how the process works. Elements 1 to 3 record the results of the Risk Identification phase. 1. Risk Category – This is where you categorize your risk. Elements 4 to 6 record the results of the Risk Analysis phase. 4.
Elements 7 and 8 record the outcomes of the Risk Evaluation phase. 7. These last four elements record the outcomes of the Risk Treatment phase. 9. It makes sense to belong to the group that uses smart tools to quickly undertake a comprehensive risk management process that covers all the necessary steps. ITIL Risk Management | ITIL Tutorial | ITSM - CertGuidance. What is ITIL Risk Management Process? Risk Management is NOT an officially defined process under ITIL Service Design, and ITIL V3 official documentation doesn’t describe any deep detail about this process. But this process/framework is used throughout the ITIL lifecycle.
As per the idea we get from ITIL books, ITIL Risk Management is the process of identifying, assessing, and prioritizing of potential business risks. It also defines the economical application of resources to minimize, monitor, and control the probability or impact of the threat, or to maximize the realization of opportunities. In case any risk is identified, an entry for that is the created in the ITIL Risk Register. ITIL Risk Management Scope: The Risk Management, in ITIL, is shown as an integral part throughout the entire ITIL Service Management Lifecycle. It also coordinates with Information Security Management to identify and assess security threats before they can actually occur. What is wrong with a typical risk register? | Norman Marks on Governance, Risk Management, and Audit. I recently presented at a Zoom meeting of IIA Qatar on the topic of “Risk Management for Success”. At one point, I shared an example of a risk register I had found on the web.
I explained how it was removed from the context of achieving objectives (i.e., risk to what?) And that periodically managing a list of risks is not sufficient. Far more is needed for effective risk management as I see it (enabling an acceptable likelihood of achieving objectives). In the Q&A session, somebody asked how the risk register could be improved. xx There are multiple problems that need to be overcome, including: As mentioned above, it is a static list of risks, updated occasionally. There are more problems, but I want to talk about one that seems to confound many risk practitioners: that risks (and opportunities) are not a point; there is a range of potential effects or consequences and each point in that range has its own likelihood. Are they wrong? In all likelihood (pun intended) they are all right.
29 Biases and Traps that Prevent Good Decision-Making - Carol Williams. It seems like bias is everywhere in our world… Some bias is healthy and normal. We may have a bias for or against a certain sports team or those of us who are parents will naturally be biased toward our children. But when it comes to decision-making in our organizations, bias can lead to putting out fires, missed goals, financial losses, regulatory headaches, instead of taking action to prevent the fires and achieve the goals.
Over the last few decades, psychologists and other behavioral scientists have identified over 200 different types of biases with more added each year. While there has been much research on identifying these biases, very few have categorized them. When it comes to decision-making, there are close to 30 specific biases and traps that can be broken down into six categories according to the book Decision Quality: Value Creation from Better Business Decisions. Below are these categories and relevant biases that can be directly linked to decision-making in organizations. 1.
Safety-Critical Systems Development. Black Swans in Risk: Myth, Reality and Bad Metaphors. The term “Black Swan event” has been part of the risk management lexicon since its coinage in 2007 by Nassim Taleb in his eponymous book titled The Black Swan: The Impact of the Highly Improbable. Taleb uses the metaphor of the black swan to describe extreme outlier events that come as a surprise to the observer, and in hindsight, the observer rationalizes that they should have predicted it.
The metaphor is based on the old European assumption that all swans are white, until black swans were discovered in 1697 in Australia. Russell Thomas recently spoke at SIRACon 2018 on this very subject in his presentation, “Think You Know Black Swans – Think Again.” In the talk, and associated blog post, Thomas deconstructs the metaphor and Taleb’s argument and expounds on the use and misuse of the term in modern risk management.
From a purely practitioner point of view, it’s worth examining why the term Black Swan is used so often in risk management. Black Swan Definition and Misuse Conclusion. Risk Register Definition | How to use a Risk Register with sample Template. Strictly necessary Performance Targeting Functionality Unclassified Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies. Performance cookies are used to see how visitors use the website, eg. analytics cookies. Targeting cookies are used to identify visitors between different websites, eg. content partners, banner networks.