>> Great, welcome back, everybody, and welcome anew to those who are joining us for the first time, today. My name is Paul I'm able to discuss this today at the climate change and global security. We've had three sessions so far.
All of this is focused on government perspectives on both climate change threats, government climate change threats, implications of changing global, changing world, but also on, what will the intelligence community, U.S., and a bit less internationally, has unimportant decision-making around climate issues. We have seen recent statements in particular from the deputy director of national intelligence that climate change is at the top of U.S. foreign policy agendas. We also know it's been a key focus of businesses around the world, particularly energy companies, financing, et cetera, thinking about the invocations of climate change, not just from a security perspective, but long-term viability of business models and businesses.
Today, we've got a panel of experts from the private sector of entrepreneurs, analysts, founders of companies, authors, who have thought about this, deeply, and are involved in not just thinking about it, but in working on it and doing things about it. We have Antoine Halff who is the chief founder of Kairos -- one of the founders. He is a senior research scholar at the Center for mobile energy research policy, formerly chief oil analyst at the energy agency, Kairos is a new earth observation for the onset of capabilities.
We have Richard Jenkins who is the CEO of sale drum, it's a company that produces seafaring platforms capabilities to provide measurements data information on what's happening both on and in the oceans with regards to climate change and other issues. Interestingly, the company came out of work he had done designing and running a world land speed when record power with a stunning speed of 146.2 miles per hour for a cell driven craft which is pretty amazing.
I would like to see it out on the lake in front of our house and see what you could get it up to out there on some ice. And we have Mekala Krishnan, with partnered with the McKinsey Global Institute, she is most notably -- in regards to this discussion, the author of an NGO research paper on climate risk and response, physical hazards, and socioeconomic impact. She is a researcher and has also been involved in research on growth, climate risk, gender economics, as well as her work on societal risks of climate change. We are interested, today, in learning what capability the private sector brings to thinking about and acting upon climate driven, national, and transnational threats, and also, what analytical capability -- We also want to look through their eyes about how CEOs are thinking about this as a risk both short-term and long-term, and particularly, how the government might draw upon some of these resources and what private industry might need from government in regard to these sets of questions. With that, let me turn over first two Antoine Halff for some opening comments.
We will go around the table . >> Yes, sure, thank you very much for having me on this panel. I'm very honored to share the stage with co-panelists.
As you said, this is an earth observation platform. Basically, what we do, we use artificial intelligence and machine learning to process data from a great number of differentsix, different satellites , but also local sensors, the social media through natural language processing, adjudication advisors and others. A fairly young company we started about five years ago, and the focus at the time was we needed the energy sector, and the energy industry and the energy markets did not get the data that it needed, the quality of data, the scope, the variety of data, from traditional sources for a variety of reasons, but we found there was an opportunity to tap the huge [ Indiscernible ] from resources and satellites to provide transparency about this traditionally opaque market. So we set out to do this initially by extending data sets that were incomplete or somewhat dubious quality sometimes, for example, could our inventories [ Indiscernible ] emerging economies, that pretty quickly, we set out to generate data that were not set out to track things that had been tracked before.
Particularly, greenhouse a -- Gases, and methane is a concern of ours. We created the first platform to monitor methane, identify them, and attribute [ Indiscernible ] in real time on a [ Indiscernible ] basis. So today, we have a range of products that focus on climate change, it has been the focus of activities and research.
We cater largely to the energy industry, but also other industries including energy intensive industries and government agencies and the financial sector and other users, we had, I would say, a menu that deal with climate change in different ways and would break them down into three categories. [ Indiscernible ] tools measurements that help us recognize the energy system, methane is one example. Before -- until recently, we couldn't really track methane.
Methane was not really visible or could not really be easily detected. You could measure concentrations in the atmosphere, but not really individual sources. Once you do that, you can start eradicating methane and [ Indiscernible ] admissions.
But we monitor [ Indiscernible ], biomass and [ Indiscernible ] for example, through various resources. And we have what I would call climate risk management tools that essentially deal with the risks of catastrophic events of climate disasters such as flooding or fires. We identify areas that are particularly prone to flooding, or if it doesn't flood, we can identify the response and help the insurance industry, for example, deal with the new climate risks and pricing roles to help mitigate them and deal with them when they occur. Then, finally, we have the energy transition management tools.
And those are different from the climate risk tools. Those are risks subject to the transition, itself. The effort to combat climate change, yesterday at the climate summit, really entailed a massive formation [ Indiscernible ] in a short amount of time, and to do this is extremely disruptive in many ways. If you look at the plans of some of the energy companies to increase the renewable energy capacity, for example, this is a massive undertaking in a very compressed period of time.
And this means huge disruptions for the individual companies, for the trading, for the community, a lot of risks are difficult to manage. There are tremendous amounts of information and data, and data capacity. This is what we provide. We provide a platform that tracks a lot of the dimensions on which those changes are playing out, and we have [ Indiscernible ] deal with these changes.
Energy is changing from [ Indiscernible ] , natural gas on one side, [ Indiscernible ], renewables, into a much formal training approach where you have to arbitrage not only different periods and pictures of times, the pictures and people with one another, and we have to do that, and basically, we are really convinced that geospatial observation and new data technologies absolutely essential to the energy transition, to managing the risks associated with climate change, but also to help implement, help achieve the clinic goals that the world has set for itself, including yesterday, and to really bend the curve of admissions. You really can't do it without new data technologies. That's an essential part of the effort. >> Thank you, Antoine Halff, a fascinating set of capabilities, and I love the clarity of approach.
Let's go to Rich Jenkins, over to you. >> Yeah, hi, thank you. So, yeah, the unmanned autonomous services for data collection, [ Indiscernible ] 12 month of information. We collect many types of data with imagery, mapping, to ocean graphing, to weather and climate modeling. Now the oceans are really driving the weather and climate to the rate of absorption and heat and carbon dioxide. [ Indiscernible ], this mitigates the effect of climate change.
Understanding the rates of climate change is the special ability to predict the future and climate. [ Indiscernible ] variables and transmit the data in real time back via satellite. So the oceans continue to absorb carbon at the rate they are, this will delay atmospheric warming.
It will get hotter and more acidic. This has a dramatic effect on the food chain and the sea. But if it would stop absorbing CO2 and an atmosphere carbon spike and axillary atmospheric warming, it has become a bad scenario, but understanding the rate of change is crucial to create meaningful predictions for future which, hopefully, can in turn, create and change policy, and hopefully encourage actions. The threats from climate, I think there are two types of main threat.
There are threats to humans, globally, and a threat to national security, locally. On a global scale, we are -- Likely to displace billions of people. On the national security perspective, one of many applications, but one of the most dwindling fish stocks are pushing to new levels, closer and closer to home, also an economic asset, we need to [ Indiscernible ] to monitor fisheries [ Indiscernible ] illegal fishing boats while simultaneously [ Indiscernible ]. However, I think it is probably the Arctic that will see the most erratic change in the next decade. The rapid reduction in ice coverage allows access to new areas that are previously inaccessible, writing opportunities to naturally -- Access natural resources, gently during the unfrozen summer months for the last six years. We are seeing increased activity in the area.
I think we need to dramatically increase our ocean watering, and specifically, Arctic modeling to protect U.S. interest in climate change. >> Thank you, Richard. Man, my mind is boggling at some of the possibilities at the capability that you described. And I also imagine that not all parties will look at your activities as benignly friendly, if you can imagine folks being quite threatened at others running illegal fishing fleets and stripping resources from other places, it might take issue with your capability and work, so, interesting, interesting set of problems -- complexities you got to deal with, there. are eight, Mekala, let's go to you.
>> Thank you, Paul, thank you for the opportunity to speak at this panel and the fascinating discussion we've had, already. I want to maybe talk about -- Make my remarks from two vantage points. One is part of the McKinsey Global Institute which is McKenzie and companies as an economic research [ Indiscernible ] that is part of McKenzie, and as part of that we have been doing a variety of research on both physical climate risk but also thinking about the social economic impact of the climate transition . I want to talk a little bit about that, and then talk a little bit also about what we are seeing in the private sector landscape so obviously, as McKinsey and Company spend time with companies across the world and some of the developments, as companies think about understanding and managing these risks. So personally, we think about climate risks, we did a big piece of work we launched in January that was trying to understand the nature and magnitude of physical climate risks. Part of what we did this is, if you look at a lot of the discussion in the climate science community and other resources that have been done, it often treats this risk as something that is happening in the second half of the century, something that is all about sea level rise.
What we wanted to try to understand where what were the risk in the system, what was the science, but how does the science interact with human beings -- how does the climate interact with human beings, with the activity, with the wealth we build across the world to try and understand the extensive risks that we experience. And what we found was a few, I think, quite surprising things. The first is when you think about the nature of these risks, what they do is to interact with a range of physical systems, they affect human lives, the ability to live and work outdoors as he conditions rise, like the buildings all of us are in, the infra structure services that I differentiate from physical capital because [ Indiscernible ] economy as a whole, the food systems and they affect capital. In some ways, it's kind of obvious, but if you stop and think about what this list is, these are the factors of production in an economy. As an economist, you think about GDP.
It comes from human capital, physical capital, natural capital, and those are what is changing climate effects. The way it changes our lives and livelihoods, it is a nonstationary former risk meaning risk is not the same as risk in the future, and that matters is you are making long-term decisions as companies are thinking where to put the footprint, as companies are making infrastructure decisions, we need to understand is not in the context of today but also in the context of the future. It's a systemic form of risk. One form of the world can spread to another part of the world as we discover pandemics are a form of systemic risk in the clinic and have much of the same impact whether it is through connected financial system, economic systems or social systems. The reason these are important, nomenclatures start to bring into the climate debate, nonstationary buddies, Anton referred to this as well, we need to refer to these as well which is not typically what one does when they do risk analysis, the systemic nature of the risk, and frankly, that we are underprepared for many of these risks. Risk is here, today.
It will only request -- Increase by 2030. Warm up and build up is guaranteed regardless of what we do because [ Indiscernible ] the system, there are some ways we would have to manage regardless of action we take on mitigation. So that's the context. The good news is, we have a lot of tools, and Antoine Halff and Rich talked about other tools. I think the good news is, we have the capabilities that can help us do this form of risk analyses.
The imperative it creates for stakeholders in my mind is for things. The first is integrating climate risk and all decision-making. So this cannot be something that happens in the silo.
We are seeing this as companies Inc. about responding to risk. These risks are often time not the responsibility of sustainability function, they are the responsibility of a risk function, a finance function, the CEO of a company, this cannot be something that is a side project. You need to think about doing it when you do [ Indiscernible ] and decision-making, that is because it is implicit in every decision we make as we make long-term investments, as we build capital, as I think of a way to grow our food, all these decisions have implicit in them some portion of climatesix. That's number one.
The second is adopted risks that are in the system, like I said, some build up is guaranteed regardless, so we need to think about how we adapt our systems to be able to manage these risks. The third is, of course, the decarbonization imperative that this creates, and finally, managing the transition risks that Antoine Halff mentioned from shifting the current state from energy and land-use to the future state. I say all of this because as we then think about companies, there are two roles that companies play in my mind in managing all these risks. The first is managing their own exposure to these risks. We are starting to see increasingly companies recognizing the need to do this. Sometimes they recognize this because they are in jurisdictions in geographies that have seen increased frequency or severity of events, Inc.
things like wildfires in California, wildfires in Australia, we started to see companies actually get affected as a result of these risks, so there's a recommendation that they need to do something to manage their own exposures. The second reason we are starting to see companies respond is increased attention on the part of regulators and investors were asking companies to understand measures disclosed on these risks. All it's doing is creating increased momentum for companies to both improve their data, improve their analytics, improve their disclosures and risk assessment and risk management. That is one kind of movement in the field.
The second is, of course, the role of the private sector in actually providing these forms of data, forms of analytics, and forms of Mr. -- Risk management tools. As Antoine Halff mentioned, we start to see the private sector reporting their own risks, but also being part of the solution. We can talk more about that as we get through this discussion. I'll pause, now.
>> Thanks, all three of you. It is an evocative and fascinating set of issues. I've got a bunch of questions. I will ask the audience to start questioning in the Q&A box.
I will start off with one about markets, you know? All of your companies were founded to respond to a market. In some ways, I suspect you are also probably creating a market. I think it was Antoine Halff who said, we are producing and discovering data that didn't exist before, and I suspect that data, once it's revealed, in turn, drives its own set of questions.
Can you give us a little bit about how -- what is the market for the various types of climate change intelligence, whether there is hard data driven pieces that Richard and Antoine Halff are producing, or more analytically produced pieces that Mekala is talking about? Is it a robust dynamic market, you know, is it niche, small, yeah, can you characterize a little bit? >> I can talk about my perspective. Ocean is like space 10 years ago. It is something to get to that traditionally, the government what had only afforded to do it, space X gave us access, and the ocean is the same way up until now, you only have government research ships in the Navy and the Coast Guard could only afford a $2 billion ship to go get that data. Because of that, the data market is a government centric market.
It is rapidly changing as commercial applications like other systems get data from the ocean. So I think it's a rapidly changing data plate. I know lots of folks are doing these incredibly clever industries of data, risk analysis, data merging to give us new insight. I think very much on the data-gathering side, it's a difficult thing to do to get precise quality data out of the oceans, I think we are seeing a dramatic change in the bias in the data [ Indiscernible ]. >> The customers for the data, are they primarily commercial, private sector or -- [ Indiscernible - overlapping speakers ] >> It is changing from government or private sector. It has traditionally been a private industry.
As it traditions to lower-cost technologies, it makes data more affordable to private companies. I think like space X, you think -- you have seen it bloom, as it would, likewise, you will see a lot more whether intelligence and limited intelligence spring up as we reduce the cost of access to the oceans. >> What are some of the uses of data that companies haven't thought about, or are just now weakening to? I suspect you have a whole spectrum of customers anticipating something cool, then what do I do with it? >> Absolutely. Our customers range from core products, we can get [ Indiscernible ], we got a core product, we can deliver, and then data products, then Intel products. It's what folks used to analyze to use modeling, and there is energy pricing [ Indiscernible ] -- you want to know the accurate ability of the sun and wind commodities, risk analysis, we are sending six vehicles into the hurricane season this year, we will really trying get more intelligence into the intensity of those storms and where they're going to land, obviously, the insurance industry, and also for human safety, being able to give an adequate warning before a land falls storm, it is crucial.
This translates into really valuable knowledge. >> Did it transmit the photo and video -- [ Indiscernible - overlapping speakers ] >> We have cameras and learning which actually spots things autonomously, but yes, everything is transmitted in real-time by satellite. >> I suspect there is really cool images that come back from that. I'm waiting for the one that shows a huge set of teeth coming up, you know, to devour your craft. >> We see a lot of animals like whales, dolphins and seals. >> What has been the biggest surprise from your standpoint in terms of what you haven't thought about, but which your crafting capability or revealing? >> That's a good question.
I guess it's the rates of change. We manage carbon dioxide, which we need for accurate measures of trends, and it's been going up, you know, about five bpm for year since we started. The ice is thrown from the north.
Temperatures are warmer. The fish we are measuring are more dispersed because of the warm waters. I think, from a science perspective, it's the rates of change in these regions like the Arctic that is most surprising to me, because as a scientist, [ Indiscernible ], understanding changes very significant.
>> Thank you, Richard. Antoine Halff and Mekala, same question. >> Go ahead, Antoine Halff. >> Okay. Will what Richard was saying, when we think about omissions, greenhouse gas emission, the lack of progress we've made so far, I think, was driven by two groups of factors, lack of knowledge, lack of transparency, understanding of transmission and also [ Indiscernible ]. Once you start to have transparency, you also have a possibility to create positive incentives and move carbon abatement from cost center to profit center.
This is something that companies can boost of doing. We can certify the content of the methane omissions with companies, oil field, the gas field, [ Indiscernible ], the volume of [ Indiscernible ]. The ability to do this, this lets companies extract a premium for goods performance. So this is a nuisance market, it's not a virtual market, it's emerging as we speak.
You've seen reports of transactions done for companies for kind of a neutral crude green energy removing -- we would be able to have multilateral transactions with point discovery in open voluntary markets. So this is changing the conversation, completely. It is not all doom and gloom.
You know, the volume of omissions we can see particularly attributed to the oil and gas industry is just massive, even larger than we thought, but the capacity to remove these omissions is here. Once they are visible, they can be removed, and they can be removed sometimes at zero cost or at a profit. So it's kind of a good story waiting to happen. >> Thank you, and fun. I think the discussion -- both the points you made about transparency, you know, knowledge drives action, but it also offers -- it opens up opportunity, then your point on incentives and building incentives is a piece of discussion that feels extraordinarily important and extraordinarily important to weave into the government discussions and taking place -- you know, at the summit's, but this is not going to be a top-down government driven set of actions to be successful, it has to incorporate the private security, incorporate incentives and real-world opportunities you talk about. >> Yeah, yeah.
And [ Indiscernible ] we picked up 9 million [ Indiscernible ] from large events in just one year. So if you can see the gloaming warble -- Global warming potential -- >> And that monitoring piece, by itself, feels like an important good or public potential good in terms of a modest broker that can find out sources of omission, and then, just the knowledge of it that will help drive action whether it's regulatory or enforcement or just reputational, oops, we need to move on this. Mekala, same question over to you on markets. >> If I take what Rich talked about, it was really about measuring the impact of climate change, so that's one form of data.
Antoine Halff, what you talked about was measuring contribution to climate change through omissions, right? And there were really excellent points about understanding the data, and also, the measurements and forms of admission measurements that allows us to do trade on carbon, allows us to certify carbon abatement, understand impacts, et cetera, is a third type of data of course that is also risk data, allowing us to understand our exposures to these risks, and I think about the final risk assessment, what that typically entails is some form of climate science data that allows us to understand in a probabilistic manner what I would call climate hazards would evolve. What is the likelihood of extreme rainfall, today, how does that go into the future -- you know, what are the [ Indiscernible ] that same temperature in the future -- so that is the data, then there is the analytics on the hazard data that is approaching, and some form of geospatial analytics involves maps -- what I would call hazard maps, flood maps, heat maps, that one could put over the company's footprint, you know, real estate footprints on to understand exposures of these assets or people to these hazards, so there is an emerging group of companies that are thinking about doing that form of risk analytics who understand how hazards can impact different communities, different stakeholders, not just direct impacts, and also ecosystem impacts, of COVID, we saw the supply chain risks play a huge part in some of the experiences in countries during COVID, so similarly, it is important not to understand -- To understand your distributors and customers, so there's a lot of heavy analytics on the geospatial side of things but also on the ecosystem, and the third form of analysis [ Indiscernible ] when you take about physical climate risks is intelligence over and about that data and analytics, right? So once you look at the data, you look at the analysis using that to change decision-making and understanding how to do that effectively, so we are starting to see, you know, various providers love hazard data. We start to see providers of analytics data, but the analytics step, that's a step I mentioned, through there, a lot of the assessments tend to be what I would call, quote, first-order assessments and not looking at the ecosystem -- and the finally piece of actually using the data and analytics intelligently is still very much an emerging arena. >> Yeah, I think you put your finger right on a really important point.
What the intelligence is, if it doesn't get to the right decision-maker at the right time in the right form, it is not helpful. I think that's a really strong point. And there's a couple -- go ahead, Richard. >> Yeah, a great point on risk.
I see it as when you are assessing risk and also when you are trying to influence policy change an action, the reason there is argument is because there is not agreement, even among scientists, the models do agree. The errors are too large. My goal would be to make the models agree through more data. You can remeasure that in real time.
What is actually happening, [ Indiscernible ] there's very little uncertainty, that is my best suggestion to enforce policy change at the government level, and also, like yourself, it would significantly reduce the risk error of marginal risk [ Indiscernible ]. So yes for measuring the effects, but is crucial to measure those effects at a spatial resolution and timely resolution, and you get enough data to make precise models to try to get the disagreement to go away. >> Thanks, Richard. We had a couple questions from the audience. A couple of them converge around the issue of transparent miss, openness and accessibility of the data. How conflict affected countries facing climate change -- and you could substitute an energy transition challenges, draw some tools being offered by the private sector, what kind of infrastructure needs to be in place, how is the private sector cooperating with such countries to ensure no one is left behind? Anyone want to jump on that? >> Yeah, maybe I can start.
I think the two points I would make, you know, on the one hand, we have talked a lot about private-sector tools and data, and I'm speaking now more on the physical risk assessment which is the area I know best. There is, I think, a little debate about should this data be public goods of some kind or at least some form of this data become public goods, if you think about a climate map, if you think about a heat map, drop maps, should these -- all too many of these rely on climate models which are free, publicly available, something that not an everyday person can access and understand, but I think we will see how the next few years play out, but I think there is a question about the raw data, itself, the raw hazard inputs into risk assessment, should they be public things that everyone can access, right? I think some form of these various platforms do try to provide data around, but they are not typically across a range of hazards, they typically don't do things like a multitude of scenarios. They don't allow you to overlay your footprint onto them. There are some emerging sector platforms or public platforms that are trying to do that.
So we will see how that debate shapes out in the coming years -- then, there is the question of capability building, capacity building around using the data effectively. I think there is some emerging work we are starting to see around private-sector consortia coming together, you know, to develop best practice guides, develop tools, techniques, protocols, standards to do things effectively and well, and I think that will be really important as we think about doing risk analysis to take into consideration [ Indiscernible ] -- there's a new toolkit that needs to be built around risk analysis, and we are starting to see groups come together to form -- it is happening industry by industry, for example, trying to come together to establish the standards and the techniques and make that topically available, there is, of course, a similar wave of effort with the decarbonization side, like how you measure your bank, how you measure zero omissions, how you account for admissions, how do you reduce expressions effectively -- [ Indiscernible ] certifications provided around robust analysis or robust measurements that are, again, public goods and publicly available, so we will see how well the shapes out in terms of development, but I think that's an emerging area that is -- that will come to maturity in a few years. >> I think you make a good point. But I think we are entering a period of very interesting partnership, [ Indiscernible ] generation, you know, the private sector has a key role to play. And I think the private sector is best placed in general innovation we need to create data, and the input to our data in our company really comes largely from the data from the European space agency, from NASA, the raw data is available, we don't have any assets, our contribution is purely on the algorithmic asset. It is machine learning.
We created, you know, we generated innovations that extracted from existing [ Indiscernible ] account of information that a company is upgrading and could use the satellite did not expect -- there is an interest we have in sharing our data with the public as well. We have publishers. We have noncommercial executions, academic centers, multilateral agencies where we provide to share the data, and I think even from our perspective, it's not the [ Indiscernible ], there's a shared interest in having a common understanding of what numbers are, what the climate impacts are around the world, and to go back to your question, Paul, about less advanced economy areas of the world, I think the data from nontraditional sources is pretty much [ Indiscernible ]. So we don't physically need to be there to provide [ Indiscernible ] and so on. In the cost of data is pretty cost-effective, cost-efficient, so we can actually [ Indiscernible ] and other new technologies, create transparency at the active market which would otherwise [ Indiscernible ] by any other means. >> [ Indiscernible - overlapping speakers ] >> Antoine Halff's point on partnerships is key.
We developed a great amount of money to a solution which is an order of magnitude cheaper than a previous solution on a ship, for example, so using private funds, private equity to enable the service of the government as a service-based product, which is of extreme value to the taxpayer, [ Indiscernible ] there are great public and private partnerships, there, [ Indiscernible ] great organization, they collect mandates to share, publicly and openly, which is great for data. People need to know the difference between who is confusing open data and free data. Data is very expensive to collect if you want high quality climate quality data. So someone still has to pay for it. Whoever's paying for the data can choose whether they wanted themselves, or whether they want to to share it and that is my role in government.
Now at -- These technologies exist, they can get information across the planet at a low cost. Let's get the data and share it with everyone including poor countries as well. Yeah, we have open data, there still high-technology products adding a tough environment with what your experience costs. >> It's a great, you know -- when you say it, it feels, you know, obvious -- it's a great point that folks forget.
Open doesn't mean free. There is a great amount of both investment and technology and effort that goes into building the platforms for the systems that have to collect the data. Let's pose an anonymous question back to the government.
Colleagues, you know, if the intelligence community is using its collection mechanisms to gather all this data, is it only used or should it only be used to inform a government audience or a select set of decision-makers within the U.S. government? We talk about sharing across allies and adversaries, what opportunities and obligations there are for that, but you can also think about a whole set of states and some state actors private and public, you know, that will be among the most affected by energy transition and climate change, but also, and are most in need of the analysis capability that the data will drive -- the intelligence will drive, but also in the least position to collect it themselves or use it themselves, and you've come up with example after example. And it feels like there's a lot of room for some creative thinking on the part of both public-sector and private-sector and private public partnerships which will be [ Indiscernible ] in some way shape or form, you know, to drive it there, so, you know, you don't have skewed structures of, you know, the data or intelligence privileged versus those not. And, so we've got just a couple of minutes left, and I will ask one last question for you each, then we will close out in advance.
Again, I want to thank you all for being here, today, thank you for being involved. It's such an interesting and important field, driving such great work. I really commend folks to take a look at the report that Mekala talked about , produced in January 2020 -- what was the name of it -- Mekala? >> It was called climate risk and response, [ Indiscernible ] -- quite a mouthful. >> It's a great report and a great international perspective to it as well, so I thought it was important. So the last question being, here, what do you think governments can learn from private sector in tying analytics to intelligence to allow more accurate use for decision-making? His closer collaboration warranted, and are there any examples you know of of this happening? >> Yeah, maybe I can start. I think, if I were to describe at least two things that are happening in the private sector where there's an opportunity for the government to do more, one is an organizational point that I alluded to earlier, where we are seeing some companies very thoughtfully think about who owns this function, right? This risk analysis, risk integration function within an organization, where should it sit? And how much weight should it have? Should it sit in risk, finance, crosscutting function, and there is an analogy in government function about who owns the responsibility of doing these risk analytics giving the cross-dresser nature of some of the -- Crosscutting nature, I think that is maybe an opportunity for some selection on the types of organizational structures or private sectors putting in place and potential opportunities for learning from that -- I think the second is the nature of risk assessments that are recurring in many parts of the private sector, not all, typically, we are seeing industries that have large physical aspects, industries that have long-lived aspects, ones that have global supply chains, others that are at the forefront of this, but as they do these forms of risk analysis, there is a systematic process they are understanding the science, not becoming climate scientist, but [ Indiscernible ] recognizing the limitations of the data as Rich said, there are uncertainties.
You need to know what our true uncertainties, water uncertainties and your [ Indiscernible ] et cetera, but there's a systematic process of understanding the science, understanding the data, building the tools and techniques and capabilities to use the data effectively, and then thinking about shifting processes so end to end chain, I think, there is a battle with other types of intelligence that the government gathers, I'm sure, but maybe there's the opportunity to think about the processes, the tools, the techniques that are being put at risk and what opportunities are able to integrate that into government decision-making as well. >> Thank you, Mekala. Antoine Halff? >> Yeah, I would agree with that statement.
I think there's a lot that the intelligence community can learn from technologies and practices developed in the private sector. What strikes me at the same time is that the new technologies are kind of commoditizing the intelligence -- the content of intelligence, leveling the access to information, and I see it particularly in the private sector. If you take the oil and gas industry, for example, you used to have large players with big footprints in the value chain and small operators with much less access to information because most of the information was privileged and came from within the system, the bigger footprint you had, the more intelligence you had in house. The new technologies are really bridging the gap between the information haves and information have-nots.
And that's in the private sector as well as in other areas as well, I think. It is also changing the governance of the private sector, because it is not just about the kind of information it can get and what it can see, it's how you access it and how it transforms you and how it exposes you to public scrutiny. So the energy system is changing, dramatically, and the role of investigations, for example, is changing completely because the information companies performance is no longer dependent on [ Indiscernible ] of companies, but is accessible from third parties, sometimes, faster than it is in house. >> Thanks, and a great point on the democratization of intelligence in the field, and the private sector, and what that might mean. And Rich, over to you, final word. >> I know I've got a few minutes left, here, I'll keep it short.
Coming from the middle, the way things government does traditionally, people own hardware and keep it to themselves, I think, as the private sector accelerates its learning curve and it is ready to deliver new solutions both in hardware and in cloud compute, I think it needs to be nimble and open, you know, to testing those solutions across the board, I think it will need a bit of reform of nimble contract vehicles and ways to test new hardware , low risk, low cost solutions to getting things in the field to really looking at data quality without having to embark on a five-year project which may be the wrong path, and maybe a high expense to the taxpayer. I think it needs to catch up with the private sector, and open-mindedness to try new platforms, new systems, and then facilitate that in a short period of time. >> Thanks, Richard. You managed to go from a really hard problem to a really, really hard problem, making the government nimble.
[ Laughter ] the first one is better -- [ Indiscernible - overlapping speakers ] look, thank you very much, Mekala, Antoine Halff, and Richard Jenkins,
2021-05-01