[MUSIC] Welcome to the second lesson of this week, where we will tackle post-normal science. And then, we would use insight from post normal science, in this case, what one should do with quantification and that's done using mathematical modeling, and then we also say something about sensitivity to other things. In this first section, we introduced both post-normal science and NUSAP, which is a system to, in a sense, attach a pedigree to some kind of quantitative information. In post-normal science, for those of you who haven't heard about that, is said to apply when facts are uncertain, stakes high, that is in dispute and decision urgent. And we will see in a moment what this means. When it was born in the early 90s, post-normal science was especially a reaction to a style of quantification of environmental issue, for instance, which heavily relied on risk-benefit analysis and cost-benefit analysis. Even in cases where the application of those technique would appear highly problematic. In fact, one of the first paper, post-normal science was a deconstruction of a an attempt to made [INAUDIBLE] cost to the effect of climate change. And I must say that this is a discussion which is still going on today. That there are a couple of references you can look at. The main idea of being, can you put in dollars things like the natural capital? And in this case, can you put in dollars, in the case of the paper of Funtowicz and Ravetz. Can you put in dollars the value of a songbird? But in fact, post-normal science was not the first intellectual movement to take issue with this type of quantification. The ecological tradition from Schumacher and Winner and other, had already noticed that there was some kind of technology associated to get them to quantify environmental damage. Here, I have, out of many, one quote from the beautiful book of EF Schumacher, Small is Beautiful which described the distinction between qualitative and quantitative. And if you read through this slide, you will see that it says that qualitative is normally more difficult to appreciate than quantitative. Because it's more subtle when compared to the freeze evidence of a number, but also makes the point that when you compress a complex issue into a number, you achieve precision and apparent simplicity by suppressing vital difference in quality. Before post-normal science came about, there had been several books anticipating its arrival. One which I already mentioned in the previous lesson is a book of published in 1971, the one containing a diagnosis of the oncoming crisis of the scientific method. And toward the end of this book, Robert said, well, you have to reflect that one thing is to have a science to master, dominate and domesticate nature, as in the dream of Bacon. Another science is perhaps needed when what you need to do is to remedy the damage than to nature by the same men which is technology. And in this book published in 90, in 1990 by together with from [INAUDIBLE] where the [INAUDIBLE] had [INAUDIBLE] which I'm about to describe. They make the point that uncertainty has been mostly the victim of this kind of pontification suppressed. And so, one of the points made in the book is that ignorance and error interact with knowledge and power more intimately than was ever conceived. This idea that knowledge interacts with power we have discussed already. But the interaction with ignorance is also an important aspect. So I said already that the PNS mantra is you need PNS when facts are uncertain, stakes high, value in dispute, and decision urgent. But there is also a very famous diagram of post-normal science which plot a system of uncertainty versus decision stake. And in this diagram, when you are in a system where you have small uncertainty, and small stakes like in a normal study, I don't know the chemical mechanism of a particular reaction. You may need applied science but when you are in context where much depends on decision made, maybe, in a short time on a lack of information, as for instance, on a military battlefield or in a operating theater, a surgeon with his patients, then, you need something different, which maybe put professional consultancy. But when you are tackling issue where the uncertainty is truly very high, and the stakes are also very high, and here we could mention several things which we are confronting today, from climate change, to the use of genetically modified foods and substances, then, you are in the domain of post-normal science. Something important which was immediately realized is that those two axis which are here plotted independently are in fact not independent, something which will typically happen in that when the stakes are very high, some of the actors who'd had a high interest in either suppress or inflate uncertainties. We will discuss this in a moment. When you adopt post-normal science, you, in a sense, abandon the positivity model of science informing power, by a truth, and for a model which we may define as working deliberatively with an imperfection. So this means that this is a participatory approach, you want to do it with stakeholders involved in the issue, whatever the issue is. But these stakeholders are not just being consulted, they can deliberate. And so, other important ingredient of post-normal science is a communication of uncertainty, the assessment of quality. So because the process of production of the evident, and the evident itself is imperfect, it's very important that we at least ensure that the process we generate is evident, is of a good quality. Then, the justifications and practices of the extended peer communities. Extended peer community is an important concept in post-normal science. Perhaps the most important concept. What is an extended peer community? Well, first of all, it says that when you have to look at an issue, could even be an issue of, an environmental issue, but not necessarily, could also be a social issue, you have to look at it using different disciplines, because each discipline looks at problems with their own lenses. So when you enrich the spectrum of discipline which are brought to bear on a given problem, you normally get more than one framing of the issue. That also, the extension has to be across community, including both practitioner experts and stakeholders. These are both issues of fairness because it is fair that the framing of the stakeholders be retained and of quality because something one immediately relies, one adult tense is that normally stakeholders can bring additional quality of the process. Here, we have the words of Peter Gluckman, who is a science advisor to the government of New Zealand, who uses post-normal science in his daily work. And he makes a list of those which are in his opinion issues where post-normal science can be applied and here you see that we no longer have only general and climate but edification of exogenous pests. Pests offshore oil prospecting, legalization of recreational psychotropic drugs, water quality, family violence, obesity, teenage morbidity, and suicide, the aging of population, the prioritization of early childhood education, reduction of agricultural greenhouse gases, balancing economic growth and environmental sustainability. I read it all, because it's interesting to see here how this can apply to both social issues and environmental issues. Although the discipline which are brought to bear in the different issues, actually different. Post-normal science can also be applied because it's not a disciplinary field is an approach to the way those signs should be used. If you wish is a kind of epistemology. The main part of this book of notational values is to say, given the numbers arranged in a very suspicious manner, I want to make sure that we have a system to qualify number, we call it NUSAP. And with this system, we shall be able to communicate the uncertainty in science for policy. One person who has spent a good part of his life on NUSAP is Jeroen van der Sluijs, he is not at the University of Jeroen Van in Norway and he has also many papers of this tracking example of the application of NUSAP and one is given below. So what is it this main suggestion of NUSAP, NUSAP says, you normally give a number with an error, and the unit of course, so we called this number or numero, unit and spread. So these are the three information which nowadays we use give a number, 1 plus minus 2 kilogram is a very uncertain quantity or 1 plus minus 0.1 kilogram. We want to compliment this assessment with two more categories, two more qualifiers, and we call them assessment and pedigree. Assessment is an idea of how reliable is my assessment of the number and of the spread. If you look at the history of physics, you will see that very often, the value of fundamental constant had been revised many times. And those revision where above the [INAUDIBLE] range even in the previous determination. So it is important to know how good are the number and the spread. While the unit, we hope, that one knows what he's talking about. Beyond assessment, we have a last category, fifth category called pedigree, which is the deeper, mostly multi-criteria assessment of the quality of the process and of the team leading to determination of this quantity. So how was this number produced? Which team worked on it? Which interests were behind this team? And so on and so forth. And because these qualifications of the quality of the process leading to the number is very complex, you normally do it using here we have the pedigree matrix. And this pedigree matrix, which is for instance, one used for statistical information, we tell you how good that is according to, in this case, four different categories. They even proposed numbers. Now, it's not important to go into the detail of the categories, because when you do an assessment using pedigree, the first thing you have to do is to put together, and to agree on the categories, which should be part of a pedigree. Because this is a pedigree for statistical information. So that, for instance, data collection and analysis it has a task force, direct survey, indirect survey, guess, fiat and unknown as the quality indication. But we could have totally different category for different assessment. For instance, if this is instead of being for statistical information, these were for what recorded you, to make an example. I said that to extend the participation, a key idea of normal science, here we have a paper where this approach was in a sense taken. Was a problem in the UK are flooding. We get are references there. And what happened in this case is that the measure to offset remedy, there's nothing were discussed with the stakeholders. So with the villagers affected by this flooding, and is an image of this flood. And what's happening is that the discussion of the remedy is to be taken and moved [INAUDIBLE] by the expert provided by the regional and regular authority and by the citizens of this particular village. And it was discovered that in fact there was among the citizens, a deep understanding of the causes of the flooding and of the possible remedial actions which should be taken. And what is interesting that the citizen even remembered the previous times that the regulators had been there to discuss the flooding and how, in their opinion, was retained, or not retained. In fact, what happened in the end, the stakeholders suggested the most effective remedy which was to use up stream storage of flood waters. And the reason why the regulators and their mathematical model had not considered this option is that the mathematical model was set as not to include [LAUGH] this particular option in this modeling of the process. Well, this finished this first segment of the second lesson.