Revisiting Timeliness for Strategic Foresight and Warning and Risk Management

timeliness, the Red (Team) Analysis Society, risk management, strategic foresight, strategic warning, anticipation, scenario, peak oil, climate change Bin Laden, Obama

[Fully rewritten version v3] To exist, risk and foresight products as well as warnings must be delivered to those who must act upon them, the customers, clients or users. These anticipation analyses must also be actionable, which means that they need to include the right information necessary to see action taken.

Yet, if you deliver your anticipation when there is no time anymore to do anything, then your work will be wasted.

Yet, even if you deliver your impeccable strategic foresight or risk analysis, or your crucial actionable warning to your clients in time to see a response implemented, but at a moment when your customers, decision-makers or policy-makers cannot hear you, then your anticipation effort will again be wasted. Let me give you an example. If you look at the picture used as featured image, what you see is the Obama government in a situation room as it awaits updates on the 2011 Operation Neptune’s Spear, the mission against Osama bin Laden. Imagine now that you have another warning to deliver (and the authorisation to do so) on any other issue, one with high impact but meant to happen in, say, 2 years time. Do you seriously believe that anyone in that room would – or rather could – listen to you? If ever you nonetheless delivered your warning, you would not be heard. Obviously, as a result, decisions would not be taken. Your customer would be upset, while the necessary response would not be implemented. Finally, endless problems, including crises, would emerge and propagate.

Delivering an anticipation analysis or product must thus obey a critical rule: it must be done in a timely fashion. Timeliness is a fundamental criterion for good anticipation, risk management and strategic foresight and warning.

In this article, we shall look, first, at timeliness as a criterion that enables the coordination of response. We shall explain it with the example of the controversial “Peak Oil”. Second, timeliness means that customers or users will not only have enough time to decide and then implement any necessary course of action as warranted by your strategic foresight and warning or risk analysis, but also be able to hear you. This is the problem of fostering credibility and overcoming other biases. We shall explain this part using again the examples of Peak Oil and taking as second example Climate Change. Finally, we shall point out a synthetic approach to understand timeliness and ways forward to achieve it.

Timeliness: enabling the coordination of response

Most often, the challenge of timeliness is understood as stemming from the need to conciliate, on the one hand, the dynamics which are specific to the issue, object of anticipation, and, on the other, the related decisions and the coordination of the response.

Let us take the example of Peak Oil, i.e. the date when “world oil production will reach a maximum – a peak – after which production will decline” (Hirsch, 2005, 11), which implies the end of a widespread availability of cheap (conventional crude) oil. Hirsch underlined that the problem of timing, i.e. identifying when oil will peak is complex

“When world oil peaking will occur is not known with certainty. A fundamental problem in predicting oil peaking is the poor quality of and possible political biases in world oil reserves data. Some experts believe peaking may occur soon. This study indicates that “soon” is within 20 years. ” (Hirsch, 2005, 5)

Thus, according to Hirsch, oil should peak before 2025.

In 2018, the idea of Peak Oil may be thought as being outdated or plainly false, grounded in mistaken false science as exemplified by Michael Lynch, “What Ever Happened To Peak Oil?“, Forbes, 29 June 2018. Note that these arguments were already used prior to a phase of relatively wide recognition of the Peak Oil phenomenon around 2010, from scientists’ reports, associations, institutions and books (see, for example, the creation of the Association for the Study of Peak Oil & Gas in 2000 , Robert Hirsch report (2005), the Institut Français du Pétrole (IFP), Thomas Homer Dixon in 2006, Michael Klare or Jeff Rubin in 2010), to web resources such as the now defunct The Oil Drum and Energy Bulletin to finally the International Energy Agency (IEA – it recognised the peaking of Peak Oil in 2010, e.g. Staniford, 2010), despite still some resistance by then a shrinking number of actors. Since then, notably, the shale revolution took place, while climate change allowed an easier access to northern oil and gas fields (e.g Jean-Michel Valantin, “The Russian Arctic Oil: a New Economic and Strategic Paradigm?”, The Red Team Analysis Society, October 12, 2016).

Peak oil is thus not very much on the agenda, although some still argue that it will happen, as, exemplified by the websites Peak Oil Barrel or Crude Oil Peak, which suggests that the oil will peak when the U.S. shale will peak (“What happened to crude oil production after the first peak in 2005?“, Sept 2018.) The peak in U.S. shales thus becomes a significant issue (e.g. Robert Rapier, “Peak Tight Oil By 2022? EIA Thinks It’s Possible, Without Even Accounting For This Risk“. Forbes, 20 February 2018; Tsvetana Paraskova, “Peak U.S. Shale Could Be 4 Years Away“, OilPrice, 25 Feb 2018).

If the remaining proponents of peak oil are right and if some of the hypotheses of the EIA are correct, then Peak Oil could take place around 2022. This is not that far away from Hirsch estimates according to which Peak Oil could occur by 2025.

We should nonetheless allow for the considerable evolutions that took place over the last 13 years, notably in terms of technology, including Artificial Intelligence, consuming behaviour, global consumption, and climate change. We should also allow for coming revolutions such as Quantum technologies which could completely upset many estimates. As long as all these developments with their complex feedbacks have not been considered, without forgetting that Hirsch addressed availability of cheap oil, not availability of expensive oil, then we must remain conservative and treat 2025 as only a possibility (a probability of 50%) for Peak Oil.

Notwithstanding other impacts, Hirsch estimates that 20 years of a “mitigation crash program before peaking” would have allowed avoiding “a world liquid fuels shortfall” (Hirsch, 2005, 65).

Thus, assuming that oil peaks in 2025, if we want to have an energy mix of replacement for the soon gone cheap oil, then we should have decided implementing and then coordinating a response… back in 2005. Note that, interestingly, this corresponds to the time when Hirsch published his report, and the time when the world started being worried about Peak Oil. We can thus wonder if, in specific countries, as well as collectively, SF&W on this issue was not actually delivered.

To answer more precisely this question, further research, when archives are declassified, will need to be done. Meanwhile, it will be useful to follow precisely the delivery process, notably, according to countries and actors, to know where exactly the warning was delivered and to whom.

If we now assume that Hirsch estimates of the time needed to develop mitigation and a new energy mix is correct, then we may consider that Hirsch, as well as the “peak oil” interest of the second part of the first decade of the 21st century, delivered a timely waning, as far as the time needed to implement answers is concerned.

If and where the right decisions were taken and the right responses implemented would need to be evaluated on a case by case basis.

Let us turn now to other criteria that condition the timeliness of the delivery of a risk or foresight analysis or of a warning.

Timeliness, credibility and biases

Jack Davis, writing on strategic warning in the case of U.S. national security, hints at the importance of another criterion linked to timeliness, credibility:

“Analysts must issue a strategic warning far enough in advance of the feared event for US officials to have an opportunity to take protective action, yet with the credibility to motivate them to do so. No mean feat. Waiting for evidence the enemy is at the gate usually fails the timeliness test; prediction of potential crises without hard evidence can fail the credibility test. When analysts are too cautious in estimative judgments on threats, they brook blame for failure to warn. When too aggressive in issuing warnings, they brook criticism for “crying wolf.”
Davis, Jack, “Improving CIA Analytic Performance: Strategic Warning,” The Sherman Kent Center for Intelligence Analysis Occasional Papers: Volume 1, Number 1, accessed September 12, 2011.

For Davis, credibility is the provision of “hard evidence” to back up strategic foresight, or actually any anticipation analysis. Of course, as we deal with the future, hard evidence will consist in understanding of processes and their dynamics (the model used, preferably an explicit model) added to facts indicating that events are more or less likely to unfold according to this understanding. This is why, building an excellent model (see our online course), grounded in science is so important, as this will be key in achieving the credibility criterion.

Credibility is, however, also something more than hard evidence. To obtain credibility, people must believe you. Hence, the biases of the customers, clients or users must be overcome. Thus, whatever the validity of the hard evidence in the eyes of the analyst, it must also be seen as such by others. The various biases that can be an obstacle to this credibility have started being largely documented (e.g. Heuer). Actually, explaining the model used and providing indications, or describing plausible scenarios are ways to overcome some of the biases, notably out-dated cognitive models. Yet, relying only on this scientific logic is insufficient, as shown by Craig Anderson, Mark Lepper, and Lee Ross in their paper “Perseverance of Social Theories: The Role of Explanation in the Persistence of Discredited Information.” Thus, other ways to minimize biases must be imagined and included. The possibility to deliver the SF&W or risk product will be accordingly delayed.

Credibility and, more broadly, overcoming biases are so important that I would go further than Davis and incorporate them within the very idea of timeliness. This would be much closer to the definition of timely, according to which something is “done or occurring at a favourable or useful time; opportune” (Google dictionary result for timely). Indeed, there cannot be timely SF&W or risk management if those who must act cannot hear the warning or analysis we seek to deliver.

If the SF&W product or the risk analysis is delivered at the wrong time, then it will be neither heard nor considered, decisions will not be taken, nor actions implemented.

More difficult, biases also affect the very capability of analysts to think the world and thus to even start analysing issues. We are there faced with cases of partial or full collective blindness, when timeliness cannot be achieved because SF&W or risk analysis cannot even start in the specific sectors of society where this analysis needs to be done.

If we use again our example of Peak Oil, the 2005 warning could have lost part of its timeliness, because of debate regarding its credibility, which remains nowadays and is exemplified in the Forbes article above mentioned. On the other hand, the decision by the International Energy Agency (IEA) to finally recognise the peaking of Peak Oil in 2010 (e.g. Staniford, 2010) lent an official character to the phenomenon, that was very likely extremely important in finally allowing for the credibility of the warning.

We face very similar stakes and challenges with Climate Change, as shown once more by the latest debates presiding to the October 2018 IPCC report (Matt McGrath, “IPCC: Climate scientists consider ‘life changing’ report“, BBC News, 1 October 2018). Tragically, in that case, the ongoing attacks on the credibility of the various warnings regarding climate change over years, has also finally most probably endangered the timely possibility of response to remain below a 1.5C warming:

“For some scientists, there is not enough time left to take the actions that would keep the world within the desired limit.
‘If you really look seriously at the feasibility, it looks like it will be very hard to reach the 1.5C,’ said Prof Arthur Petersen, from University College London and a former IPCC member.
‘I am relatively sceptical that we can meet 1.5C, even with an overshoot. Scientists can dream up that is feasible, but it’s a pipedream.'” (MacGrath, “IPCC: Climate scientists …)

This shows how the credibility issue is absolutely crucial for a warning to respect the timeliness criterion.

Timeliness as the intersection of three dynamics

To summarise, timeliness is best seen as the intersection of three dynamics:

The dynamics and time of the issue or problem at hand, knowing that, especially when they are about nature, those dynamics will tend to prevail (Elias, 1992)
The dynamics of the coordination of the response (including decision)
The dynamics of cognition (or evolution of beliefs and awareness, including biases resulting from interests) – at collective and individual level – of the actors involved.

To understand each dynamic is, in itself, a challenge. Even more difficult, each dynamic acts upon the others, making it impossible to truly hope to achieve timeliness if the impact of one dynamic on the others is ignored.

For example, if we continue with the case of climate change, having been unable to truly even properly think collectively the possibility of climate change in its dire reality and with a more accurate timeline before the turn of the century – despite multiple efforts in this direction (e.g. Richard Wiles, “It’s 50 years since climate change was first seen. Now time is running out“, The Guardian, 15 March 2018), has dramatically changed the current possible dynamics of the response, while both the cognitive delay and the absence of previous decisions and actions have orientated the dynamics of the issue towards some paths, while others are definitely closed. Any SF&W or risk assessment delivered on this issue now, as shown by the October 2018 IPCC Panel discussions (Ibid.), is quite different from what was delivered previously.

To acknowledge the difficulty of finding the timely moment, and the impossibility to ever practice an ideal SF&W in an imagined world where everyone – at individual and collective level – would have perfect cognition, is not to negate SF&W or risk management. Answering the “timeliness challenge” with a “what is the point to do it now as we did not do it when things were easy/easier” is at best childish, at worst suicidal.

On the contrary, fully acknowledging hurdles is to have a more mature attitude regarding who we are as human beings, accepting our shortcomings but also trusting in our creativity and capacity to work to overcome the most difficult challenges. It is to open the door to the possibility to develop strategies and related policies with adequate tools to improve the timeliness of SF&W and risk management, thus making it more actionable and efficient:

Creating evolving products that will be adapted to the moment of delivery;
Using the publication of groups, communities, scholarly or other work on new dangers, threats and opportunities as potential weak signals that are still unthinkable by the majority;
Developing and furthering our understanding of the dynamics of cognition and finding ways to act on them or, to the least, to accompany them;
Keeping permanently in mind this crucial issue in anticipation to seek and implement adequate strategies to overcome it, according to the ideas, moods, science and technologies available at the time of delivery.

——–

This is the 3rd edition of this article, considerably revised from the 1st edition, 14 Sept 2011.

Featured image: Situation Room, Pete Souza [Public domain], via Wikimedia Commons

About the author: Dr Helene Lavoix, PhD Lond (International Relations), is the Director of The Red (Team) Analysis Society. She is specialised in strategic foresight and warning for national and international security issues. Her current focus is on Artificial Intelligence and Security.

References

Anderson, Craig A., Mark R. Lepper, and Lee Ross, “Perseverance of Social Theories: The Role of Explanation in the Persistence of Discredited Information,” Journal of Personality and Social Psychology 1980, Vol. 39, No.6, 1037-1049.

Campbell, Colin J. and Jean H. Laherrere, “The end of cheap oil,”  Scientific American, March 1998.

Davis, Jack, “Improving CIA Analytic Performance: Strategic Warning,” The Sherman Kent Center for Intelligence Analysis Occasional Papers: Volume 1, Number 1, accessed September 12, 2011.

Dixon, Thomas Homer, The Upside of Down: Catastrophe, Creativity and the Renewal of civilization, (Knopf, 2006).

Elias, Norbert, Time: An Essay, (Oxford: Blackwell, 1992)

Hirsch, Robert L., SAIC, Project Leader, Roger Bezdek, MISI, Robert Wendling, MISI Peaking of World Oil Production: Impacts, Mitigation & Risk Management, For the U.S. DOE, February 2005.

International Energy Agency (IEA), World Energy Outlook 2010.

Klare, Michael, Blood and Oil: The Dangers and Consequences of America’s Growing Dependency on Imported Petroleum, (New York: Metropolitan Books, 2004; paperback, Owl Books, 2005).

Klare, Michael, Rising Powers, Shrinking Planet: The New Geopolitics of Energy (Henry Holt & Company, Incorporated, 2008).

Rubin, Jeff, Why Your World is About to Get a Whole Lot Smaller: Oil and the End of Globalization, Random House, 2009.

Staniford, Stuart, “IEA acknowledges peak oil,” Published Nov 10 2010, Energy Bulletin.

Winning the Race to Exascale Computing – AI, Computing Power and Geopolitics (4)

artificial intelligence, geopolitics, exascale, great power competition, strategic foresight, strategic warning, The Red (Team) Analysis Society, drivers, stakes, risk

This article focuses on the race to exascale computing and its multi-dimensional political and geopolitical impacts, a crucial response major actors are implementing in terms of High Performance Computing (HPC) power, notably for the development of their artificial intelligence (AI) systems. It thus ends for now our series on HPC as driver of and stake for AI, among the five we identified in Artificial Intelligence – Forces, Drivers and Stakes: the classical big data, HPC and the race to quantum supremacy as related critical uncertainty, algorithms, “sensors and expressors”, and finally needs and usages.

Related
Artificial Intelligence, Computing Power and Geopolitics (1): the connection between AI and HPC
Artificial Intelligence, Computing Power and Geopolitics (2): what could happen to actors with insufficient HPC in an AI-world, a world where the distribution of power now also results from AI, while a threat to the Westphalian order emerges
High Performance Computing Race and Power – Artificial Intelligence, Computing Power and Geopolitics (3): The complex framework within which the responses available to actors in terms of HPC, considering its crucial significance need to be located.

This final piece builds on the first part, where we explained and detailed the connection between AI and HPC, and on the second part, where we looked at the related political and geopolitical impacts: what could happen to actors with insufficient HPC in an AI-world, a world where the distribution of power now also results from AI, while a threat to the Westphalian order emerges. The responses available to actors in terms of HPC, considering its crucial significance need to be located within the complex framework we explained in part three. Accordingly, first, decisions regarding which HPC capability to develop must be taken in relative terms, i.e. considering others’ HPC and AIs. Second, each actor engaged in the race must consider how fast other actors will develop stronger HPC capabilities. Finally, the longer the lead time investing actors have over the next revolutionary advance in HPC, the longer they delay the loss of value of their investment, and the more performing the AI-systems they can create, which gives them a window of opportunity to take full advantage of their superior AI.

In this dynamical framework we look at the obvious policy response actors designed: having more and better HPC, earlier, than the others. This is translated as the ongoing race to exascale computing, i.e. bringing online a computer with as capability a thousand petaflops or 10¹⁸ floating point operations per second, knowing that, currently, the most powerful computer in the world, U.S. Summit, shows a performance of 122.3 petaflops (TopList 500 June 2018). We start with a state of play on the ongoing “race to exascale”, which involves chronologically Japan, the U.S., France, China and the EU. We notably includes latest information on the indigenous European Processor Initiative (4-6 Sept 2018). The table summarizing the State of Play below is open access/free.

We then point out linkages between this race and economic, business, political, geopolitical and global dynamics, focusing notably on the likely disappearance of American supremacy in terms of processors.

Subscribe for new articles

Finally, strategically, if this race means going quicker than others developing better machines, it may also imply, logically, slowing down as much as possible, by all means, one’s competitors. Disrupting the very race would be an ideal way to slow down others, while completely upsetting the AI and HPC field, relativising the race to exascale and thus changing the whole related technological, commercial, political and geopolitical landscape. Thus, we underline two major possible disruptive evolutions and factors that could take place, namely quantum computing and a third generation AI. We shall detail both in forthcoming articles as quantum computing is a driver and stake for AI in its own right, while a third generation AI can best be seen as belonging to the driver and stake constituted by algorithms (“Artificial Intelligence – Forces, Drivers and Stakes”, ibid).

The Race to Exascale

Access for non-members is limited to the table summarising the state of play of the race to exascale. The complete text is a premium article. To access this article, you must become one of our members. Log in if you are a member.
A pdf version of the complete article (EN and FR) is available for members
ARTICLE 3951 WORDS – pdf 17 pages

State of Play

As of September 2018, the state of play for the race to exascale is as follows:

The Race to Exascale – Full State of Play – 24 September 2018
	Japan	U.S.	China	EU	France
Pre-ES and prototype		2013-2020	June 2018 Sunway exascale computer prototype July 2018 Tianhe-3 prototype	2021	2015, 2018 Tera1000
Peak-ES and Sustained-ES	2021 Post-K	2021 Aurora – Argonne National Laboratory (ANL) 2021 Frontier -Oak Ridge National Laboratory (ORNL) 2022 El Capitan – Lawrence Livermore National Laboratory (LLNL) 2022-2023 Aurora upgrades	2020 – Tianhe-3 2d half 2020 or first half 2021 – Sunway Exascale	2023-2024 (EPI) (Initially 2022-2023 -Official)	2020-2021 BullSequana X
Energy Efficiency Goal		20-30 MW	20-32MW	20-40 MW	20 MW by 2020
Initiative	Flagship 2020 Project	ECP	13th 5 Year Plan	EuroHCP	CEA
Budget	$0.8 to 1 billion***	$ 1.8 billion for the 2 ORNL and LLNL machines	?	€ 1billion+ by 2020**	?
Vendors	Japan	U.S.	Chinese	Europe	France
Processor, Accelerator, Integrator	Japan Fujitsu-designed Arm	U.S.	Chinese ARM based, Sugon: x86	European Processor Initiative (EPI) (Arm, RISC-V) RHEA, First generation processor for pres Exascale – CRONOS for Exascale Bull integrator BXI	Intel, ARM, Bull Exascale Interconnect (BXI)
Cost per System		Aurora:$300 to $600 million. Frontier and El Capitan: $400 to 600 million	$350 to 500 million***	$350 million***	?
Research by The Red (Team) Analysis Society – Detailed sources in the text.

Feedbacks and impacts

To continue reading, become a member . If you are already a member, please login (don’t forget to refresh the page).

Notes and Additional Bibliography

*”does not manufacture the silicon wafers, or chips, used in its products; instead, it outsources the work to a manufacturing plant, or foundry. Many of these foundries are located in Taiwan and China…” (Investopedia)

**€486 million matched by a similar amount from the participating countries plus in kind contributions from private actors (“Commission proposes to invest EUR 1 billion in world-class European supercomputers“, European Commission – Press release, 11 January 2018)

***Hyperion Research, “Exascale Update“, 5 Sept 2018.

CEA, Atos et le CEA placent TERA 1000, le supercalculateur le plus puissant d’Europe, dans le Top 15 mondial, 25 June 2018

CEA, TERA 1000 : 1er défi relevé par le CEA pour l’Exascale, 12 Nov 2015

Collins, Jim, “Call for Proposals: Aurora Early Science Program expands to include data and learning projects“, Argonne National Laboratory, 18 January 2018

e-IRG, “Interview of EPI’s project coordinator Philippe Notton from Atos“, 10 April 2018

ECP, “SECRETARY OF ENERGY RICK PERRY ANNOUNCES $1.8 BILLION INITIATIVE FOR NEW SUPERCOMPUTERS“, 9 April 2018

Lobet, Mathieu, Matthieu Haefele, Vineet Soni, Patrick Tamain, Julien Derouillat, et al.. High Performance Computing at Exascale: challenges and benefits. 15ème congrés de la Société Française de Physique division Plasma, Jun 2018, Bordeaux, France.

Thielen, Sean, “Europe’s advantage in the race to exascale“, The NextPlatform, 5 September 2018

Valero, Mateo, European Processor Initiative & RISC-V, 9 May 2018

Featured image: Computational Science, Argonne National Laboratory, Public Domain.

Intelligence, Strategic Foresight and Warning, Risk Management, Forecasting or Futurism?

Intelligence, Strategic Foresight and Warning, Risk Management, Forecasting, Futurism

The focus of this website is anticipation for all issues that are relevant to political and geopolitical risks and uncertainties, national and international security, traditional and non-traditional security issues, or, to use a military approach, conventional and unconventional security[1]. In other terms we shall deal with all uncertainties, risks, threats, but also opportunities, which impact governance, and international relations, from pandemics to artificial intelligence through disruptive technology, from energy to climate change through water to wars. This activity may be called more specifically strategic foresight and warning (SF&W) or risk management, even though there are slight differences between both. The definition we use builds upon the practice and research of long time experts and practitioners Fingar, Davis, Grabo and Knight.

Definition of Strategic Foresight and Warning – Risk management for strategic uncertainties

“Strategic Foresight and Warning (risk management for strategic uncertainties) is an organized and systematic process to reduce uncertainty regarding the future that aims at allowing policy-makers and decision-makers to take decisions with sufficient lead time to see those decisions implemented at best.” (Fingar, Davis, Grabo and Knight)

Broadly speaking, it is part of the field of anticipation – or approaches to the future, which also includes other perspectives and practices centred on other themes.

SF&W can and does borrow ideas and methodologies from those approaches, while adapting them to its specific focus. For example, a country like Singapore with its Risk Assessment and Horizon Scanning – RAHS Programme Office, part of the National Security Coordination Secretariat at the Prime Minister’s Office, uses a mix of most of those perspectives, reworks and combines them for its own needs, while creating and designing original tools, methodologies and processes. Furthermore, various actors also use different names for SF&W, or very similar approaches. It is thus important to clarify what various labels and names mean, even if borders between categories are often fuzzy.

We find, by alphabetical order (the “Early Warning System” item is under the “Warning” section):

Futures Studies (also futurology)

Futures Studies (also futurology), practiced by futurists, have been developed since the 1960s. It has, initially, as main market for-profit organisations, i.e. companies and businesses, although it also increasingly tends to provide services to territorial collectivities and state agencies, generally in fields unrelated to security (e.g. urbanism, education, the future of work etc.). Considering the outlook of its founding fathers and related texts, it tends to be characterised by a pro-peace utopian outlook, an emphasis on human intent, a specific multi-disciplinarity focusing on economy and business, technology, some parts of sociology and anthropology, literary criticism, and philosophy. It also tends to have been influenced by post-modernism. It is most often taught in business schools or part of business programs, such as the Wharton School, Turku’s Finland Futures Research Centre, or the University of Houston. Hawaii Research Center for Futures Studies seems to be an exception to the rule as it is part of the department of political studies. It tends to be heavily grounded in a post-modern approach.

Forecasting

Forecasting usually refers to the use of quantitative techniques, notably statistics, to approach the future. This is however not always the case and, for example, Glenn and Gordon in their exhaustive review, Futures research methodology, tend to use indifferently forecasting, futures methods and foresight. Understanding forecasting as quantitative techniques seems, nevertheless, to be the most generalized and clearer meaning. It is a tool that is or may be used in any discipline, for example demographics. It is also sometimes considered as the only proper way to anticipate the future. It then tends to ignore what has been developed in other fields and the reasons for this evolution such as the complexity of the world. Many approaches to forecasting are mostly business and economics oriented, although some parts of political science – notably those dealing with elections – or more rarely parts of international relations also use forecasting. Here, we may notably refer to the work of Philip Schrodt, or of the Political Instability Task Force – PITF (funded by the CIA).

Foresight

Foresight, notably in Europe, tends to be used for approaches to the future focused almost exclusively on science and technology, innovations and research and development e.g. the European Foresight Platform which replaces the European Foresight Monitoring Network (EFMN), but also elsewhere in the world. If foresight is meant to be used for other issues, then it is spelled out: e.g. Security Foresight.

Horizon Scanning

Horizon Scanning is used mainly in the U.K. and in Singapore – see the post “Horizon Scanning and Monitoring for Anticipation” for more details.

Intelligence

For the CIA, “Reduced to its simplest terms, intelligence is knowledge and foreknowledge of the world around us—the prelude to decision and action by U.S. policymakers.” (CIA, 1999: vii). Note that Michael Warner (2002) references eighteen different definitions of “intelligence.” It is thus broader than SF&W and should ideally include it, although the SF&W function may or not be part of the intelligence system. A major difference that may be underlined between intelligence on the one hand, SF&W on the other, is that the first starts with and depends upon decision-makers or policy-makers’ requirements while the second does not (see the SF&W cycle).

National Intelligence Estimate

In the US, “National Intelligence Estimates or NIEs “represent a coordinated and integrated analytic effort among the [US] intelligence enterprise, and are the [Intelligence Community] IC’s most authoritative written judgments concerning national security issues and estimates about the course of future events” (ODNI, 2011: 7). NIEs are produced by the National Intelligence Council (NIC). The NIC is heir to the Board of National Estimates created in 1950, that was morphed into National Intelligence Officers in 1973 and finally became the National Intelligence Council, reporting to the Director of Central Intelligence, in 1979. It is part of the ODNI, Mission Integration (MI) led by the Deputy Director of National Intelligence for Mission Integration, Edward Gistaro. They, however, result from a collective effort and process. “The NIEs are typically requested by senior civilian and military policymakers, Congressional leaders and at times are initiated by the National Intelligence Council (NIC)” (National Intelligence Estimate – Iran: Nuclear Intentions and Capabilities, November 2007 – pdf). They may use or not Strategic Foresight & Warning methodologies, and usually are concerned with a medium term (up to ten years) timeframe. Most of the time NIEs are classified, however some are public and can be found in the NIC (public) collection. For more details on the NIEs process, read, for example, Rosenbach and Peritz, “National Intelligence Estimates,” 2009.

National Intelligence Assessment

National Intelligence Assessments or NIAs are products such as the US Intelligence Community Assessment on Global Water Security (Feb 2012), or the 2008 National Intelligence Assessment on the National Security Implications of Global Climate Change to 2030. In the words of Tom Fingar, former chairman of the NIC, “The short explanation of the difference between an NIA and the better-known National Intelligence Estimate or NIE is that an NIA addresses subjects that are so far in the future or on which there is so little intelligence that they are more like extended think pieces than estimative analysis. NIAs rely more on carefully articulated assumptions than on established fact.” (Fingar, 2009: 8). Both the NIEs and NIAs emphasize and rate the confidence they have in their own judgements and assessments, which is rarely done elsewhere and should be widely adopted.

La Prospective

La Prospective is the French equivalent, broadly speaking, for both futures studies approaches and strategic foresight (or Strategic Futures). We can notably refer to the work done by Futuribles, which is focusing on futurism for businesses, as well as teaching done at the CNAM, notably focused on innovation.

Risk Management

Risk Management (initially known as risk analysis[2]) is an approach to the future that has been developed by the private sector in the field of engineering, industry, finance and actuarial assessments. It started being increasingly fashionable in the 1990s. The International Organisation for Standardisation (ISO) now codifies it through the ISO 31000 family under the label of Risk Management.[3] Risk management remains primarily a tool of the private sector with its specific needs and priorities, however those approaches are now widely referred to, incorporated and used within governments. Risk management includes monitoring and surveillance, as intelligence, strategic warning and SF&W.

Risk Assessment

Risk Assessment is, as defined in risk management, the overall process of risk identification, risk analysis and risk evaluation. It tends also to be used in a looser sense, as in Singapore RAHS, or in the US DIA five-year plan, when the latter mentions that it will “Provide strategic warning and integrated risk assessment” (p.3).

Political risk

Political risk is most often practiced by many consultancies as a “classical” analysis of the political conditions in a country without much methodology, on the contrary from what should be done.
Consultancies dealing with risk and political risk quite often actually deal with “risks to infrastructures” and direct operational risks. Here we are more in the area of tactical risks and daily collection of intelligence to prevent, for example, terrorist or criminal attacks on offices or exploitation sites.

Risk governance

Risk governance is the label used by the OECD to address risk management. Although they started with a focus on economic and infrastructural risks, they now address all-hazards risk. (See also Strategic Crisis Management below).

Science

Although this tends to be forgotten in “anticipation circles” – or refused by part of the academia in the case of social sciences for various reasons – the first discipline to deal with the future is science as it can qualify as such only if it has descriptive, explanatory and predictive power (of course with all the necessary and obvious specifications that must be added to the word “prediction,” considering notably complexity science and the need to forget the 100% crystal ball type of prediction for the more realistic probabilistic approach).

Strategic Analysis

Strategic Analysis is a term that can be used by various institutions, for example by the Situation Awareness unit of the Finnish Security Police (SUPO), and is defined by them as a “general assessment of changes in the operational environment, incidents, phenomena or threats” for decision-makers.” We find it also mentioned in the DIA five-year plan as part of the strategic warning responsibilities. It can thus be seen as a part of SF&W.

Strategic Anticipation

Strategic Anticipation is a loose term that can be used to cover all strategic activities related to the future.

Strategic Foresight

Strategic Foresight covers strategic anticipation for conventional and unconventional strategic issues as we do, however without the warning component. One example is the Clingendael Institute, a leading International Relations and Security think-tank uses the term Strategic Foresight for its corresponding department and research.

Strategic crisis management

Strategic crisis management is the label used by one department of the OECD risk governance section. It seeks to address the management of crisis as it happens, but not only. It also covers exactly the same process and issues as the one we tackles here, however, doing it as crisis has happened or while it is happening. As a result, it does consider the rising tendency of policy-makers and decision-makers to wait until crisis has hit to start thinking about anticipation. We were proud to deliver one of the two keynote speeches of their 2015 workshop focused more particularly on anticipation

Strategic Futures

Strategic Futures is a term that is used in the American intelligence system, for example with the Strategic Futures Group of the NIC. Prior to 2011 the Strategic Futures Group was named the Long Range Analysis unit. It contributes, besides the National Intelligence Offices, to the overall process that produces the Global Trends series of the NIC (latest Global Trends: The Paradox of Progress). Global Trends uses all available methodologies according to needs.

Strategic Futures may be considered as synonymous with strategic foresight, in its exploratory dimension. It may also integrate a warning dimension, and in this case, would be equivalent to SF&W. Indeed, it is interesting to note that the National Intelligence Council used to have among its National Intelligence Officers a National Intelligence Officer for Warning (as shown here in the cached version of its public website for 22 August 2010 – This office had been created by the Director of Central Intelligence Directive NO. 1/5, effective 23 May 1979). This Office then disappeared (compare for example with cached version for 10 April 2011), while the Long Range Analysis Unit was renamed in Strategic Futures Group.

Strategic Warning

If the National Office for Warning disappeared from the NIC, Strategic Warning (also known as Indications and Warning), and which aims at avoiding surprises, remains nonetheless crucial within the US Intelligence system, as reasserted notably by the DIA in the 2012-2017 plan (read also Pellerin, DoD News, July 2012). The strategic warning mission of the DIA was reasserted in June 2018 in “Defense Intelligence Agency Bringing Forewarning into 21st Century” (DoD News). Strategic warning covers notably “necessary collection and forward-looking analytic methods and techniques, … to ensure warning is conveyed accurately and in a timely manner.” (p. 6). It is very similar if not identical to SF&W, but emphasises the warning aspect.

Also in the warning section, one finds the appellation that is promoted notably by the European Union, as Early Warning Systems (see 2011 Council Conclusions on Conflict Prevention building on the Treaty of Lisbon – Article 21c), and which tends to be focused essentially on conflict prevention. Note that the four steps of the process (1/ scan for high risk and deteriorating situations, 2/identify ‘at risk’ countries that require further EU analysis and action, 3/analysis including setting explicit objectives in preparation for early preventive or peacebuilding actions, 4/monitor the resulting actions in terms of impact on conflicts (see EU factsheet on EWS), on the contrary from what is promoted in intelligence notably for ethical reasons including those relative to the democratic mandate held only by policy-makers (e.g. Fingar, Lecture 3, pp. 1-2, 6-7) quite largely integrate early responses within its system. meanwhile, the available types of actions are pre-determined and consist of “preventive or peacebuilding” actions, although the broad appellation may leave some leeway in terms of establishing an efficient strategy then operationalisation of the answer. Also contrary to other approaches, EWS deal exclusively with conflict as issue.

The very specificities of the European Union in terms of its evolving institutions, the way decisions are taken and the competences (see EU competences) and prerogatives of each of its institutions according to areas, has strong influences on the approach promoted for Early Warning Systems. Notably the specificity of the Common Foreign and Security Policy – CFSP (see EU Special competences) is highly constraining on the design and then practice of early warning. Finally, the possibility to see the CFSP evolve towards more common defence notably, considering changes in the EU and international context – post Brexit, election of U.S. President Trump, election of France staunch EU supporter President Macron – (e.g. Paul Taylor, “Merkel’s thunderbolt is starting gun for European defense drive“, 30 May 2017, Politico), is highly likely to lead to changes in the EU approach to “Early Warning”.
The November 2017 document on the EU conflict EWS explains objective and process: EU conflict Early Warning System: Objectives, Process and Guidance for Implementation – 2017

Strategic Intelligence

Strategic Intelligence is a widely used but rarely defined term that Heidenrich (2007) describes as “that intelligence necessary to create and implement a strategy, typically a grand strategy, what officialdom calls a national strategy. A strategy is not really a plan but the logic driving a plan.” According to the way intelligence and security are understood, strategic intelligence and strategic foresight, or rather in this case strategic foresight and warning will more or less largely intersect; to the least they will need each other.

[1] “Unconventional,” from a Department of Defence perspective, connotes national security conditions and contingencies that are defense-relevant but not necessarily defense-specific. Unconventional security challenges lie substantially outside the realm of traditional war fighting. They are routinely nonmilitary in origin and character.” Nathan Freier, Known Unknowns: Unconventional “Strategic Shocks” in Defense Strategy Development (Carlisle, PA: Peacekeeping and Stability Operations Institute and Strategic Studies Institute, U.S. Army War College, 2008), p.3.

[2] Note that the Society for Risk Analysis considers risk assessment and risk management as part of risk analysis.

[3] The ISO31000 was first published as a standard in November 2009. The ISO Guide 73:2009 defines the terms and vocabulary used in risk management. A new version of the guidelines, ISO 31000:2018, Risk management – Guidelines, was published in February 2018. The other ISO documents related to risk management remain unchanged.

Selected Bibliography

Central Intelligence Agency (Office of Public Affairs), A Consumer’s Guide to Intelligence, (Washington, DC: Central Intelligence Agency, 1999).

Davis, Jack “Strategic Warning: If Surprise is Inevitable, What Role for Analysis?” Sherman Kent Center for Intelligence Analysis, Occasional Papers, Vol.2, Number 1 https://www.cia.gov/library/kent-center-occasional-papers/vol2no1.htm;

Fingar, Thomas, ”Myths, Fears, and Expectations,” Payne Distinguished Lecture Series 2009 Reducing Uncertainty: Intelligence and National Security, Lecture 1, FSI Stanford, CISAC Lecture Series, October 21, 2009 & March 11, 2009.

Fingar, Thomas, “Anticipating Opportunities: Using Intelligence to Shape the Future,” Payne Distinguished Lecture Series 2009 Reducing Uncertainty: Intelligence and National Security, Lecture 3, FSI Stanford, CISAC Lecture Series, October 21, 2009.

Grabo, Cynthia M. Anticipating Surprise: Analysis for Strategic Warning, edited by Jan Goldman, (Lanham MD: University Press of America, May 2004).

Glenn Jerome C. and Theodore J. Gordon, Ed; The Millennium Project: Futures Research Methodology, Version 3.0, 2009.

Heidenrich, John G. “The State of Strategic Intelligence”, Studies in Intelligence, vol51 no2, 2007.

Knight, Kenneth “Focused on foresight: An interview with the US’s national intelligence officer for warning,” September 2009, McKinsey Quarterly.

Pellerin, Cheryl, DIA Five-Year Plan Updates Strategic Warning Mission, American Forces Press Service, WASHINGTON, July 18, 2012.

Rosenbach, Eric and Aki J. Peritz, “National Intelligence Estimates”, Memo in report Confrontation or Collaboration? Congress and the Intelligence Community, Belfer Center for Science and International Affairs, Harvard Kennedy School, July 2009.

Schrodt, Philip A., “Forecasts and Contingencies: From Methodology to Policy,” Paper presented at the theme panel “Political Utility and Fundamental Research: The Problem of Pasteur’s Quadrant” at the American Political Science Association meetings, Boston, 29 August – 1 September 2002.

Warner, Michael, “Wanted: A Definition of “Intelligence”, Studies in Intelligence, Vol. 46, No. 3, 2002.

Featured Image: Morris (Sgt), No 5 Army Film & Photographic UnitPost-Work: User:W.wolny / Public domain

$2 Billion for Next Gen Artificial Intelligence for U.S. Defence – Signal

Impact on Issues and Uncertainties

Credit Image: Mike MacKenzie on Flickr
Image via www.vpnsrus.com – (CC BY 2.0).

Critical Uncertainty ➚➚➚ Disruption of the current AI-power race for private and public actors alike – The U.S. takes a very serious lead in the race.
➚➚ Accelerating expansion of AI
➚➚ Accelerating emergence of the AI-world
➚➚ Increased odds to see the U.S. consolidating its lead in the AI-power race.
➚➚ Escalating AI-power race notably between the U.S. and China.
➚➚ Rising challenge for the rest of the world to catch up
➚ Potential for escalating tension U.S. – China, including between AI actors

Facts and Analysis

Related
Ongoing series: Portal to AI – Understanding AI and Foreseeing the Future AI-powered World
★ Artificial Intelligence – Forces, Drivers and Stakes
Militarizing Artificial Intelligence – China (1)
★ Militarizing Artificial Intelligence – China (2)
Articles starting with a ★ are premium articles, members-only. The introduction remains nonetheless open access.

On 7 September 2018, the U.S. Defense Advanced Research Projects Agency (DARPA) of the Department of Defense (DoD) launched a multi-year investment of more than $2 billion in new and existing programs to favour and let emerge “the third wave” of Artificial Intelligence (AI). According to DARPA, this next generation AI should notably improve and focus upon “contextual adaptation,” i.e. “machines that understand and reason in context”.

The goal is to enable the creation of machines that “function more as colleagues than as tools” and thus to allow for “partner[ing] with machines”. As a result, the DARPA wants to create “powerful capabilities for the DoD”, i.e.:

“Military systems that collaborate with warfighters will
– facilitate better decisions in complex, time-critical, battlefield environments;
– enable a shared understanding of massive, incomplete, and contradictory information;
– and empower unmanned systems to perform critical missions safely and with high degrees of autonomy.”

The last point is highly likely to include notably the famously feared Lethal Autonomous Weapon Systems (LAWS) aka killer robots.

Even though the USD 2 billion announcement includes existing programs, DARPA’s new campaign indicates the importance of AI for the American Defence. The U.S. shows here again its willingness to remain at the top of the race for AI-power, by breaking new ground in terms of “algorithms” as well as “needs and usage”, to use our five drivers and stakes’ terminology. It also thereby adopts a distinctively disruptive strategy as it intends to go beyond the current Deep Learning wave.

Disruption would impact both public and private actors, states and companies alike.

In terms of power struggle, we may also see the launch of the DARPA campaign as an answer to the call by Alphabet (Google), Tesla and 116 international experts to ban autonomous weapons. With such an amount of funding available, it is likely that more than one expert and laboratory will see their initial reluctance circumvented.

Should the U.S. succeed, then it would take a very serious lead in the current race for AI power, notably with China, as it would deeply shape the very path on which the race takes place.

Sources and Signals

Darpa: AI Next Campaign

https://www.youtube.com/watch?v=-O01G3tSYpU&rel=0

A DARPA Perspective on Artificial Intelligence (https://www.youtube.com/watch?v=-O01G3tSYpU&rel=0)

DARPA Announces $2 Billion Campaign to Develop Next Wave of AI Technologies
Over its 60-year history, DARPA has played a leading role in the creation and advancement of artificial intelligence (AI) technologies that have produced game-changing capabilities for the Department of Defense. Starting in the 1960s, DARPA research shaped the first wave of AI technologies, which focused on handcrafted knowledge, or rule-based systems capable of narrowly defined tasks.

Elon Musk leads 116 experts calling for outright ban of killer robots
Some of the world’s leading robotics and artificial intelligence pioneers are calling on the United Nations to ban the development and use of killer robots. Tesla’s Elon Musk and Alphabet’s Mustafa Suleyman are leading a group of 116 specialists from across 26 countries who are calling for the ban on autonomous weapons.

Impacts of Chinese Baidu new no-code tool to build AI-programs – Signal

Impact on Issues and Uncertainties

➚➚ Accelerating expansion of AI

➚➚ Accelerating emergence of the AI-world

➚ Redrawing of the power map of the world along AI-power status lines

➚ Escalating AI-power race notably between the U.S. and China.
➚ Rising challenge for the rest of the world to catch up

➚ China influence and capability in terms of A.I.
➚ U.S. feeling threatened, which is possibly a factor of global instability

➚ Potential for escalating tension U.S. – China, including between AI actors

Facts and Analysis

Related

Our ongoing series: The Future Artificial Intelligence – Powered World

Artificial Intelligence – Forces, Drivers and Stakes

One of the drivers we identified as powering AI, its development and spread is “needs and usage”. We then noted that this driver was particularly active in the case of China.

The deployment of a beta version of Baidu EZDL is one more evidence in this direction. In a nutshell, Baidu EZDL is a platform for machine learning, which may be used by anyone and notably small and medium size companies without AI capabilities (we have not yet tested its ease of use or its claims). It is currently limited to object recognition, images and sound. It is likely, nonetheless to vastly spread the use of AI among first Chinese small and medium-sized companies, and then globally.

This enhances China – and Baidu – positions in the AI-world in construction, while promoting globally the expansion of AI. It also escalates competition in terms of AI between China and the U.S., when tensions between the two countries is high because of the U.S. declared trade war.

Source and Signal

Baidu EZDL website

Michael Feldman, Baidu Launches ‘No-Code’ Tool for Building Machine Learning Models, Top500, 4 September 2018:

Baidu Launches ‘No-Code’ Tool for Building Machine Learning Models

Baidu Launches ‘No-Code’ Tool for Building Machine Learning Models Search giant Baidu has released EZDL, a software development platform for non-programmers who want to build production-level machine learning models.

High Performance Computing Race and Power – Artificial Intelligence, Computing Power and Geopolitics (3)

AI, AI-world, artificial intelligence, China, computing power, Deep Learning, featured, HPC, international order, power, processor, Russia, Saudi Arabia, scenarios, supercomputer, U.S, U.S. Army, ZTE, scenarios, warning, Red (Team) Analysis Society

This article explores three major challenges actors face when defining and carrying out their policies and answers in terms of high performance computing power (HPC) and artificial intelligence (AI), considering the political and geopolitical consequences of the feedback relationship linking AI in its Deep Learning component and computing power – hardware – or rather HPC. It builds on the first part, where we explained and detailed the connection between AI and HPC, and on the second part, where we looked at the related political and geopolitical impacts: what could happen to actors with insufficient HPC in an AI-world, a world where the distribution of power now also results from AI while a threat to the Westphalian order emerges.

Related

Artificial Intelligence, Computing Power and Geopolitics (1): the connection between AI and HPC

Artificial Intelligence, Computing Power and Geopolitics (2): what could happen to actors with insufficient HPC in an AI-world, a world where the distribution of power now also results from AI, while a threat to the Westphalian order emerges.

Winning The Race to Exascale Computing – Artificial Intelligence, Computing Power and Geopolitics (4): The race to exascale computing, state of play, and impacts on power and the political and geopolitical (dis)order; possible disruptions to the race.

Faced with the hurdles and threats stemming from inadequate HPC for the creation of AI-systems for AI-governance and AI-management, and, in a lesser way, for the training of these AI-systems, actors must devise responses. As they decide upon objectives and then ways to practically carry out responses, actors will face three supplementary challenges.First, objectives, planning and implementation regarding HPC must be thought in relative terms. Second, they must be envisioned dynamically. Third, the actors must consider that the very HPC field and thus the capabilities that need to be acquired are profoundly evolving because of the very feedback relationship between hardware and deep-learning we identified in the first part of our series “Artificial Intelligence, Computing Power and Geopolitics”.

Below we explain further each of these elements, while giving concrete examples for each. Using latest available data, the cases of Russia, with possible consequences for its intelligent android robot FEDOR, and of Saudi Arabia, illustrate the significance of understanding relative HPC for AI. The importance of the dynamic element involved in the relationship between HPC and AI leads us to take a deep dive, including in terms of cost, into the race for HPC, which involves notably the U.S. and China. We underline how this very race is a strong instrument of influence, wealth and power for those at the very top of the competition: the U.S. and its companies, with China trying to catch up. Yet, as a result, the contest also works hand in hand with the AI quest for optimisation to create an overall very fluid and revolutionary HPC environment.

Access for non-members or for your package is limited. To continue reading, become a member of The Red (Team) Analysis Society.

If you are already a member, or if you have purchased access to this article, please login (don’t forget to refresh the page).

Full article 3654 words
Members can download the report in pdf (12 PAGES) after login

We are thus faced with a series of feedback loops or rather spirals involving HPC and AI-systems and their developments, foreign policy, national interest and balance for power, defence, trade, ideology, business strategy and quest for profit, which, permanently, impact the field. The easy and apparently neat categorisation of the past are being erased. Similarly, possible responses, including one’s own, must increasingly be included within the foresight and warning, risk management or anticipation process when the main issue is AI and not separated from it. This is necessary to be able to properly consider how one’s strategy and action will impact reality and thus change the very range of future possibilities the initial foresight analysis considered. If we think about this two-fold evolution, there is nothing new, actually, but the speed at which events and dynamics unfold question the tidy distinction and especially the slow processes that were once presiding to polities and companies’ organisation. This is also one way AI fundamentally impacts AI-governance and Ai-management.

Now we have defined the complex framework within which actors must design their HPC policy, we shall look with the next article at the possible responses they may devise.

—–

Featured image: U.S. Army Acquisition Center – Nongkran Ch, Public Domain.

The Warming Ocean as Planetary Threat

warming ocean, threat, strategy, food resources, acidification, Red (Team) Analysis Society, risk analysis, geopolitics

This article looks at the way the warming ocean exerts a growing pressure on food security and the economy. It is a follow-up to “The U.S. Navy vs Climate Change Insecurity” (Jean-Michel Valantin, June 15, 2018), where we focused on the current climate and ocean change becoming a major strategic threat, because of the rapid rise of the ocean level. However, as we shall detail here, the ocean change threat has also other dimensions.

As a matter of fact, the quickly heightening levels of atmospheric greenhouse gases, among them CO2, which have triggered climate change, are also acidifying the seawater (“Climate change indicators: Ocean Acidity“, U.S Environmental Protection Agency, 2016). This process combines with the chemical and biological impacts of land industrial and agricultural pollution, which endanger the fisheries, essential components of the food resources of entire maritime facades. These changes have direct geopolitical consequences, because they impact the most basic geophysical equilibrium upon which human societies and international relations are built (Lincoln Paine, The Sea and Civilization, a Maritime History of the World, 2013).

This threat can only be understood through the scale of the current planetary change. The massive strategic problem linked to this new era is that the planetary present and future are now dominated by complex dynamics of global change, signals of the new and current geological epoch named the “Anthropocene”, i.e the geological epoch defined by the consequences of human development, which creates its own stratigraphic signal (Jean-Michel Valantin, “The Planetary Crisis Rules, Part.1 and Part. 2”, The Red (Team) Analysis Society, January 25, 2016 and February 15, 2016). In this regard, the planetary crisis has become a major generator of friction, i.e., according to Clausewitz, a system of pressure and constraint. This “planetary friction” exerts itself upon every kind of activity related to the ocean.

These global changes must be understood for what they are, i.e. a strange bonding between the current state of societies and globalization with an emerging new state of permanent change of the planetary environment. In other words, the ocean upon which our globalized world depends is becoming a strategic threat matrix.

First, we shall look at how ocean change has started threatening food resources in the Western Indian Ocean. In a second part, we shall focus upon the economic dimension of the ocean, through the consequences of the intensification of extreme weather and ocean related events. Then, we shall wonder about the strategic consequences of the dangerous evolution of the relationship between human development and the world ocean.

The warming ocean as a massive resource threat

The rise of the ocean level, the heightening rhythm and intensity of ocean related climate weather events, the acidification of seawater, and the reactions to agricultural and industrial land pollution are composing a planetary nexus. This nexus threatens both the extraction of food resources and the social, economic and political stability of the littorals. The nature of the threat of this process is particularly alarming considering the gigantic scale of some of these crises.

As we saw in The Planetary Crisis Rules (2) (The Red (Team) Analysis, February 15, 2016), a mammoth crisis may well be currently unfolding in the western Indian Ocean rim. A study shows that an alarming loss of more than 30% of the phytoplankton in the western Indian Ocean took place over the last 16 years (Koll Roxy and al., “A reduction in marine primary productivity driven by rapid warming over the tropical Indian Ocean”, AGU Publications, 19 January 2016). This loss is most certainly due to the accelerated warming of the surface water, where the phytoplankton lives. This warming is blocking the mixing of the surface water with deeper and cooler subsurface waters, where the nutrients of the plankton – nitrates, phosphates and silicates – come from and remain blocked (K. S. Rajgopal, “Western Indian Ocean phytoplankton hit by warming”, The Hindu, 29 December 2015).

Indian ocean, warming ocean, threat, strategy, food resources, acidification, Red (Team) Analysis Society, risk analysis, geopolitics

The problem is that plankton is the foundation for the whole ocean feed chain (Callum Roberts, The Ocean of life, the fate of Man and the Sea, 2012). For example, the researchers unveiled that there is a massive decline in the shoals of fish near the Kenyan and Somali coast. These declines are not solely the result of overfishing, but also the consequences of the combination of this practice with the loss of plankton (David Michel and Russel Sticklor, “Plenty of fish in the sea? Food security in the Indian Ocean”, The Diplomat, 24 August 2012). This trend is very likely to prolong itself in the foreseeable future, because of the ocean warming due to climate change, and is going to alter the whole Indian Ocean, with the risk of turning this biologically rich ocean into an “ecological desert” (Amantha Perera, “Warmer Indian Ocean could be “ecological desert” scientists warn”, Reuters, 19 January 2016).

This means that the decline of marine life due to anthropogenic climate change is a direct threat to the food security of the whole Western Indian Ocean ecosystem, thus to the lives of the populations of eastern African societies – i.e South Africa, Mozambique, Tanzania, Kenya, Somalia, Ethiopia, as well as archipelagos, such as Comoros, Maldives, Seychelles, Madagascar, Mauritius, Mayotte – and to their economies (Johan Groeneveld, “The Western Indian Ocean as a source of food”, in The Regional State of the Coast Report: Western Indian Ocean, Chapter: Chapter 20, Publisher: UNEP-Nairobi Convention and WIOMSA, 1 May 2015). This is most likely to happen despite the rapid development of fish farming, which induces its own cascade of issues (Michel and Sticklor, ibid).

The plankton and sea food crisis is particularly worrisome given the profound economic and social inequalities known by the region, and the political, confessional and military tensions that arise, for example in Kenya and Somalia (Jean-Michel Valantin, “Somali Piracy: a model for tomorrow’s life in the Anthropocene?”, The Red Team Analysis Society, 28 October, 2013 ). This means that, nowadays, a giant biodiversity and geophysical crisis is unfolding on such a scale that it concerns numerous countries and dozens of millions of people at the same time. Moreover it combines itself with political and strategic current crises.

India satellite image, warming ocean, threat, strategy, food resources, acidification, Red (Team) Analysis Society, risk analysis, geopolitics

Since the discovery of this giant dead zone, and as was foreseen in The Planetary Crisis Rules (2), the chemical and biological situation of the Indian Ocean has continued to deteriorate, because of the multiplication of two other giant dead zones in the Indian Ocean (Harry Pettit, ‘The ocean is suffocating’: Fish-killing dead zone is found growing in the Arabian Sea – and it is already bigger than SCOTLAND”, Mail on Line, 27 April 2017. One has been identified in the Gulf of Oman and threatens marine life and fisheries in this part of the Arabian Sea. Another giant one, that spans at last 60 000 square km has been discovered in the Bay of Bengal, and threatens the food resources of the 200 million people installed on the littoral of the eight countries that surround the Bay (Amitav Gosh and Aaron Savion Lobo, “Bay of Bengal: depleted fish stocks and huge dead zone signal tipping point”, The Guardian, 31 January 2017) . In other terms, climate and ocean change is directly threatening the food security of hundred of millions of people in Africa, in the Arabian Sea area and in South Asia.

As a matter of fact, it must be remembered that the rise of Somali piracy at the start of this century has been largely triggered by the depletion of the Somali fisheries and that turning fishermen into pirates has proven it was an efficient way for littoral endangered communities to adapt to their dangerous new socio-environmental conditions of life (and death) (Andrew Palmer, The New Pirates: Modern Global Piracy from Somalia to the South China Sea, 2014).

Littorals and economy under siege

Another dimension of the ocean change threat is the way it literally puts under “economic siege” the littorals. As a matter of fact, the littorals are at once the most attractive space because of their economic development and the interface between countries separated by the ocean. Those regions are heavily impacted by the rise of the ocean and by the rising power and violence of climate-related extreme weather events.

Hurricane Harvey, warming ocean, threat, strategy, food resources, acidification, Red (Team) Analysis Society, risk analysis, geopolitics

For example, let us look at the U.S. and the mammoth disasters wrought by hurricane Harvey in Texas between the 25 August and 2 September 2017. “Harvey” killed 68 people and wrought immense damages, which costs amount to 125 billion dollars, making it the costliest hurricane after “Katrina” that destroyed New Orleans in 2005 and did cost 161 billion dollars (“Fast facts Hurricane Costs”, The Office for Coastal management-National Ocean and Atmospheric Agency and Insurance Information Institute, 2018). These damages alone put a massive pressure on economic activities and on the insurance sector, because of the direct destructions wrought to the infrastructures, cities, homes, fields and industries.

To these costs have to be added those of repairs, of business interruption, and of detoxification made necessary because of the massive industrial chemicals and sewage spillage (Erin Brodwin and Jake Canter, “A chemical plant exploded twice after getting flooded by Harvey – but it’s not over yet”, Business Insider, 30 August, 2017). These human and economic costs are multiplied to consider those incurred by Houston and the whole state of Texas, as well as by Louisiana during the same week. It must also be remembered that a lot of oil extraction and transaction operations were suspended, and thus impact the companies involved in these activities (Matt Egan and Chris Isidore, “Tropical storm Harvey threatens vital Texas energy hub”, CNN Money, August 26, 2017).

If we take a look at just the littoral counties of Harris and Galveston in Texas, for example, we see that “Hurricane Harvey has damaged at least 23 billion dollars of property…” (Reuters, Fortune, 30 August 2017). 26% of this sum is land value, the remaining part is being constituted by dozens of thousands of houses, buildings and infrastructures. Some of those were insured but a lot more were not, which means that, potentially, millions of people found themselves brutally projected in very precarious situations. (“Tallying Massive Costs of Harvey to Victims, Insurers, Taxpayers and Economy“, Insurance Journal, 31 August, 2017).

To these tremendous costs were added those resulting from the heavy damages wrought by the giant Hurricane Irma in Florida and the Keys to infrastructures, cities, business and agriculture, especially to the orange production (Berkeley Lovelace Jr, “Irma could be “the last straw” for the Florida orange industry, commodities expert says”, CNBC, 8 September 2017). (Rob While, “The estimated costs of hurricanes Irma and Harvey are already higher than Katrina”, Money, September 11, 2017).

All in all, the 2017 hurricane season did cost more than a staggering USD 220 billion in economic damages. Out of these, 80 billion were supported by the re-insurance industry (Matt Sheehan, “Hurricanes Harvey, Irma, and Maria cost re/insurers $80bn: Impact Forecasting », Reinsurance News, 5 April 2018). In other terms, the ocean-related extreme weather events of the end of the summer 2017 were a massive economic, social, infrastructural and human blow to the US.

Bonding with Chaos: opening a window on the future

The Western Indian Ocean case and the Harvey and Irma cases are a few examples among many of the emerging reality defined by the installation of contemporary societies on the “Defiant Earth” of the Anthropocene Era (Clive Hamilton, Defiant Earth, The fate of the Humans in the Anthropocene, 2017). Ocean change is defined by the way its thermal, chemical, biological and volumetric parameters are changing and are becoming hostile to current forms of infrastructural, economic, social and human development. In other words, all the countries in the world, not only those that are directly linked to the ocean, but also those in the hinterlands of neighbouring countries with a mesa facade, are literally bonding with the growing climate-ocean rising chaos.

In strategic terms, this means that the ocean is becoming a potential planetary factor and driver of violence. It deprives immense populations of a large quantity of food through its own complex biological collapse. It repeatedly and endlessly directly impacts infrastructures. It is thus a social threat for littoral communities and all the stakes vested in them. We are faced with issues ranging from the sustainability of the littoral development, to the very survival of entire populations. Studying the current development of dead zones in the Indian Ocean and their consequences on food security, as well as the infrastructural and financial costs of hurricanes such as Harvey opens up a window on a short and middle term future when the forces of the climate ocean change will besiege and endanger the different forms of human development as well as social, economic and political cohesion.

In other words, the violence stemming from ocean change demands new ways to control violence on a changing planet bonding with chaos. This phenomenon emerges while the relation between artificial intelligence and security is starting to be explored (Jean-Michel Valantin, “The Chinese Artificial Intelligence Revolution”, The Red Team Analysis Society and Hélène Lavoix, “Artificial Intelligence, Computing power and Geopolitics” (2), The Red Team Analysis Society, November 13, 2017 and June 25, 2018, or more generally our ongoing series on Artificial Intelligence: The Future Artificial Intelligence – Powered World).

In other terms, will artificial intelligence be a means to inject some measure of control in the emerging planetary chaos?

Featured image: ISS-52 Hurricane Harvey by NASA/Randy Bresnik [Public domain], via Wikimedia Commons.

Artificial Intelligence, Computing Power and Geopolitics (2)

This article focuses on the political and geopolitical consequences of the feedback relationship linking Artificial Intelligence (AI) in its Deep Learning component and computing power – hardware – or rather high performance computing power (HPC). It builds on a first part where we explained and detailed this connection.

Related

Artificial Intelligence, Computing Power and Geopolitics (1): the connection between AI and HPC

High Performance Computing Race and Power – Artificial Intelligence, Computing Power and Geopolitics (3): The complex framework within which the responses available to actors in terms of HPC, considering its crucial significance need to be located.

Winning the Race to Exascale Computing – Artificial Intelligence, Computing Power and Geopolitics (4) : The race to exascale computing, state of play, and impacts on power and the political and geopolitical (dis)order; possible disruptions to the race.

There we underlined notably three typical phases where computation is required: creation of the AI program, training, and inference or production (usage). We showed that a quest for improvement across phases, and the overwhelming and determining importance of architecture design – which takes place during the creation phase – generates a crucial need for ever more powerful computing power. Meanwhile, we identified a feedback spiral between AI-DL and computing power, where more computing power allows for advances in terms of AI and where new AI and the need to optimize it demand more computing power. Building upon these findings we envision here how the feedback spiral between computing power and AI-DL systems is increasingly likely to impact politics and geopolitics.

Considering thus the crucial and rising importance of computing power, with the next article we shall address how the resulting race for computing power could play out and has already most probably started. There we shall notably consider a supplementary uncertainty we identified previously, the evolution and even mutation of the field of computing power and hardware as it is impacted by AI-DL.

Members-only

Download article as pdf – Artificial Intelligence, Computing Power and Geopolitics part-2.pdf – 12 pages

Become a member of The Red (Team) Analysis Society.

Here we first imagine the political and geopolitical impacts faced by actors with insufficient computing power. We examine these potential consequences according to the choices the actors have. We focus on the very creation of the AI-systems and speak more briefly of the training phase. Then we look at the distribution of power in the emerging AI-world according to computing power and underline a possible threat to our current modern international order.

Living without high performance computing power in the age of Artificial Intelligence: dependency and loss of sovereignty

Understanding and imagining for the future the political and geopolitical impacts of the feedback relationship between computing power and Artificial Intelligence-Deep Learning may be more easily grasped when looking first at what the absence of computing power or rather high performance computing could entail.

As we started pointing out in the previous article, not having the computing power necessary for the phase of the creation of AI systems (phase 0 in our previous article) will de facto make various actors dependent upon those who have computing power.

What we are facing is a situation comparable to a brain drain of a new age, or rather an initial brain deficiency, which forbids or, to the least, makes very difficult evolution. As shown in the detailed example of Google’s AutoML (see When AI started creating AI), if AI-created Deep Neural Networks are always or most of the time more efficient than those created by humans, then those actors who cannot perform best during this initial phase, when AIs are designed, will have less efficient AIs, no AIs, will depend upon external computing power to create their AIs or, worse, upon others for the very core programme of the AI-DL they will use. If these AI-systems are crucial for their governance or AI-management, then potential negative impacts may ripple throughout the whole system. As a result their AI-power status in the international relative distribution of power will be impacted thrice: once because of potentially sub-efficient AI-governance or AI-management, once because they cannot wield influence thanks to their optimal AI-systems and once because they do not have useful and necessary computing power. Impact on general international influence and international power status will follow and stem from all the areas where AI-governance and AI-management are increasingly used positively, when this will only be fully realised by those who have computing power. We shall look more in detail to each of the choices available to those actors who do not have sufficient computing power.

Here we assume – and this is indeed a very strong assumption – that potential negative effects and unintended consequence of the use of AI-systems for governance and management are mitigated. Note that detailed scenarios would be necessary to move from assumption to a better understanding of the future across the whole range of possibilities.

For example, we may think about a completely opposite possibility, according to which actors using AI-systems abundantly have completely underestimated and mismanaged adverse impacts and where, finally, those actors who had no computer power and decided for not using AI in governance or in management end up faring much better that their AI-friendly counterparts.

Choice 1: No AI-systems and Non-AI actors

Notably if we consider the still emerging and highly changing field of AI, as well as the cost entailed notably in terms of computing power, we may imagine a scenario in terms of international interactions where, out of a conscious political decision or out of sheer necessity and duress, some AI-free actors finally develop strategic, operational, and tactical advantages across governance or management, which allow them to fare better than AI-endowed actors. We should here remember the famous war simulation Millenium Challenge 2002 – a war simulation exercise sponsored by the defunct U.S. Joint Forces Command – where an a-doctrinal Red Team (playing ‘the enemy’) initially won over the Blue Team (the U.S.), including by not using the expected technology (Micah Zenko, “Millennium Challenge: The Real Story of a Corrupted Military Exercise and Its Legacy“, War On The Rocks, 5 Nov 2015; Malcolm Gladwell, Blink: The Power of Thinking Without Thinking, 2005: pp. 47-68).

If political authorities faced with a large deficit in computing power make the conscious and willed choice to decide to exclude AI, then, on top of the possibility to develop unexpected advantages – which is however, in no way a given – evoked above, they may be able to try capitalising on this strategy. As an analogy, everything being equal, we may think about what Bhutan decided in terms of national policy. The country – true enough, so far, largely “guided” by India in terms of external relations, with a revision of the Indo-Bhutan Friendship Treaty in 2007, and by an international system where peace has rather prevailed as a norm since the end of World War 2, despite a grimmer reality – chose a specific cultural “official stress on Bhutanese distinctiveness” for development, foregoing a mad quest for modernity, and erecting this specificity as national pride, policy and asset (Syed Aziz-al Ahsan and Bhumitra Chakma, “Bhutan’s Foreign Policy: Cautious Self-Assertion?“, Asian Survey, Vol. 33, No. 11 (Nov., 1993), pp. 1043-1054.

Short of this thoughtful and planned approach, which furthermore may neither remain viable in the medium-term and even shorter term future in a changing international order, nor be adaptable to each and every actor, governing without AI may soon become complex. Indeed, if many areas of governance increasingly involve AI-systems in most countries, then, a “non-AI country”, when interacting internationally on a host of issues with others, may rapidly face challenges, ranging from speed of reaction and capability to handle data, to inability to communicate and misunderstanding because of different ways to handle problems (with or without AI). Non-AI companies would most probably face similar difficulties, even more so if they are located in countries where AI is promoted by the political authorities. In that case, these non-AI businesses would most probably have to move towards AI, assuming they can, or disappear.

Choice 2: Suboptimal AI-systems

Similar problems, with even worse hurdles, may arise if the absence or inadequacy of computing power leads to the use of suboptimal AI.

All areas of governance or management where a less efficient AI is used can be impacted.

By less efficient, we cover a very large scope of problems from energy inefficiency to accuracy decrease through speed, i.e. all those elements for which a quest for optimisation and improvement is ongoing, as we saw previously (see “Artificial Intelligence, Computing Power and Geopolitics (1)“, part 3).

Imagine, for example, that drones, enabled with carrying weapons and firing, use AI-systems for object detection (for an example with open source Google-created NASNet, see “When AI Started Creating AI”). If your AI-system for Object Detection is less efficient than the system used by the adversary, then your drone may be destroyed even before it started doing anything. It may also be tricked with a whole range of decoys.

artificial intelligence, smart city, geopolitics, AI, driver, scenarios, strategic warning, deep learning high performance computing power, risk analysis, risk management, strategic foresight, red team analysis society, indicator, drones, LAWS — “To achieve the upper hand on a battlefield that’s expected to be complex and multidimensional”, the U.S. Army Research Laboratory, ” ARL is developing interconnected weapons that will incorporate advances in shared sensing, computing and navigating.” Image by Evan Jensen, ARL – from Dr. Frank Fresconi, Dr. Scott Schoenfeld and Dan Rusin, Lt. Col., USA (Ret.), “On Target”, January – March 2018 issue of Army AL&T magazine, Public Domain.

We could even imagine that the enemy’s superior computing power having allowed for creating better and more numerous AI-systems, could have the capability to feed fake or slightly skewed information into the sub-optimal drone, leading the latter to target exclusively its own army’s troops and material. Here, even with the best will in the world, the actor deficient in computing power cannot – it truly does not have the capability – protect itself nor preempt what superior computing power and thus, de facto, AIs can create and do. Furthermore, because AIs create strategies that are AI specific and are not usually imagined by humans, as shown by Google’s series of AI programs devoted to the game of Go (see “Artificial Intelligence and Deep Learning – The New AI-World in the Making“), it is likely that, as in the offensive example imagined above, only efficient and optimal AIs will be able to counter AIs.

This is only one example but it may be declined across the whole spectrum of AI-powered objects such as the Internet of Things (IoT).

Choice 3: Optimal AI but created on external computing power

Let us turn now to an actor with insufficient computing power available, yet having a willingness to develop and optimize its own AI systems – assuming this actor also has the other necessary ingredients to do so, such as scientists for example.

This actor may have no other choice than using others’ computing power. This actor will have to pay for this usage, be it in monetary terms, if it uses commercial facilities, or in terms of independence if, for example, specific cooperation agreements are imagined. This may, or not, involve security liabilities according to the actors, to the providers of computing power, and to the specific goal of the AI-systems being developed.

In terms of national security, for example, can we really imagine a ministry of Defence or a Home ministry developing highly sensitive AI-systems on a commercial computing facility?

Actually, yes, it can be imagined as, already, the U.S. army is moving “to the cloud with the help of industry”, with, for example, the “Joint Enterprise Defense Infrastructure (JEDI)”, to be finally awarded in Autumn 2018 (e.g. “Army modernizes, migrates to cloud computing“, Military and Aerospace Electronic, 20 March 2018; Frank Konkel,, “Pentagon’s Commercial Cloud Will Be a Single Award—And Industry Isn’t Happy“, NextGov, 7 March 2018; LTC Steven Howard, U.S. Army (Ret.), “DoD to Award Joint Enterprise Defense Infrastructure Cloud Contract in Fall 2018“, Cyberdefense, 23 May 2018). This cloud should be used for war and “a commercial company” – probably Amazon – will be “in charge of hosting and distributing mission-critical workloads and classified military secrets to warfighters around the globe” (Howard, Ibid; Frank Konkel “How a Pentagon Contract Sparked a Cloud War“, NextGov, 26 April 2018). JEDI could be awarded to Amazon during Autumn 2018 (Ibid.). True enough, we do not know if this cloud will be used as distributed architecture also to create AI-systems, but it may be. Using commercial companies for governance, even more so if the purpose is related to defence, demands that commercial companies assume a security mission that was, until recently, a prerogative of the state. The power thus given to a commercial company makes even more the American political dynamics. Notably, Eisenhower’s military-industrial complex could well be changing (e.g.”Military-Industrial Complex Speech“, Dwight D. Eisenhower, 1961, Avalon Project, Yale).

Now, this is about American security, privatised to American companies. However, would the Pentagon award such contracts to Chinese companies or European ones?

Similarly, we may wonder if the creation of AI-systems may be done on commercial super computers belonging to foreign companies, and/or localized abroad. This is even more so if the foreign company is already contracted by a foreign Army or Defence ministry, as, in that case, the foreign Army has a larger power of coercion on the commercial companies: it may threaten to withhold the contract, or delay payment if the commercial company does not do its bidding, whatever the bidding.

The possibility to face hacks and other security vulnerabilities rapidly increases.

A similar phenomenon may also occur for elements constituting computing power, such as foreign manufactured chips, as recently shown by two researchers of the Department of Electrical and Computer Engineering of U.S. Clemson University, pointing out computing power supply chain vulnerabilities for machine learning (Joseph Clements and Yingjie Lao, “Hardware Trojan Attacks on Neural Networks“, arXiv:1806.05768v1 [cs.LG] 14 Jun 2018).

The use of distributed architecture, i.e. computing power distributed over various machines, as in the example of JEDI above, which may be envisioned to a point to offset the absence of super computers, not only multiplies the power needed (see Artificial Intelligence, Computing Power and Geopolitics (1)), but also opens the door to new dangers, as data travel and as each computer of the network must be secured. It may thus not be such an easy way out of super computing power deficiency.

Outside the field of cybersecurity, using others’ computing power also opens the door to very simple vulnerabilities: a round of sanctions of the type favoured by the U.S., for example, may suddenly forbid any actor, public or private, access to the needed computing power, even if the provider is a commercial entity. The dependent actor may be actually so dependent upon the country host to computing power that it has lost much of its sovereignty and independence.

This is also true for companies, if they hand their fate to other countries and competitors – without an adequate policy of diversification of supply of computing power, assuming this is possible – as shows the example of ZTE and American sanctions, even though the case involves more elements than computing power (e.g. Sijia Jiang, “ZTE’s Hong Kong shares rise after clarification of U.S. bill impact“, Reuters, 20 June 2018; Erik Wasson, Jenny Leonard, and Margaret Talev “Trump to Argue ZTE Fine, Penalties Are Punishment Enough, Official Says“, Bloomberg, 20 June 2018; Li Tao, Celia Chen, Bien Perez, “ZTE may be too big to fail, as it remains the thin end of the wedge in China’s global tech ambition“, SCMP, 21 April 2018; Koh Gui Qing, “Exclusive – U.S. considers tightening grip on China ties to Corporate America“, Reuters, 27 April 2018).

Choice 4: Optimal AIs but created by others

Finally, using AI-systems designed and created by others may also lead to similar vulnerabilities and dependency, which may be acceptable for companies when using mass-market products but not for actors such as countries when national interest and national security is at stake, nor by companies when competitively sensitive areas are at stake (especially when faced with predatory practice, see “Beyond the end of globalisation – from the Brexit to U.S. President Trump“, The Red (Team) Analysis, 27 February 2017).

We already evoked the influence gained by those being able to sell such systems and the risks borne by those buying and using them in the case of China that “export[ed] facial ID technology to Zimbabwe” (Global Times, 12 April 2018), in “Big Data, Driver for Artificial Intelligence… but not in the Future?” (Helene Lavoix, The Red (Team) Analysis, 16 April 2018).

Let us take another example with the future smart cities. We may imagine that a country, not endowed with sufficient computing power, has to rely on either computing power or directly on foreign AI-systems for their cities. The video below, although not focused on AI, gives an idea of the trend towards connected and “smart cities”.

Now, knowing that, in war, urban operations are considered as being a major component of the future (e.g. UK DCDC Strategic Trends Programme: Future Operating Environment 2035: 2-3, 25), it is highly likely that urban operations will increasingly take place in smart and AI-powered cities. To better envision what is likely to happen in the future, we should thus mentally juxtapose the video and the urban combat images below created by the U.S. Army Research Laboratory. In other words, instead of a devastated “modern world” traditional background for the Army pictures, we should have a smart, AI-powered city as background.

https://www.youtube.com/watch?v=THiQtn9hVB8&rel=0

The Smart Cities Of Tomorrow Are Already Here | Mach | NBC News (https://www.youtube.com/watch?v=THiQtn9hVB8&rel=0)

Now, if a foreign actor has created the AI-systems that manage the AI-powered city, what stops that actor to potentially include “elements” that would play in its favour should its troops have to carry out offensive operations in the future within this very city?

Or, as another example, if strategically wise political authorities wanted to endow their cities with AI-powered defence, able to counter both traditional and AI-endowed attacks, but if these very political authorities did not have any computing power to develop such systems, would foreign commercial companies be allowed by their own political authorities to develop such systems?

In an AI-powered world, sovereignty and independence become dependent upon computing power.

The absence of computing power for the training phase of the AI-system somehow corresponds to a country that would have no education system and would have to completely rely on external and foreign sources to deliver this education. This is true for supervised learning when training on big data set has to be done and only heightens the hurdles already identified previously in Big Data, Driver for Artificial Intelligence… This is also true, as we saw previously (part 1), for reinforcement learning as computing power is even more important for this type of deep learning, even though it does not need external big data. Could this also be true with the latest Google Deep Mind’s approach, Transfer Learning? This will need to be examined later, with a deep dive into this latest AI-DL approach.

Distribution of Power in the AI-World, High Performance Computing Power and Threat to the Westphalian System?

As a result, the Top500 list of supercomputers, which is produced biannually, and thus ranks every 6 months supercomputers throughout the world, becomes a precious indication and tool to evaluate present and future AI-power of actors, be they companies or states. It also gives us a quite precise picture of power on the international scene.

For example, according to the November 2017 Top500 list (the next issue was presented on 25 June 2018, and made public after the publication of this article – watch out for a signal on the June 2018 list), and assuming all supercomputers have been submitted to the benchmark of the list, in the whole Middle East, only Saudi Arabia possesses supercomputers among the top 500 most powerful computers of the world. It has four of them, ranked 20, 60, 288 and 386. The last three belong to oil company Aramco. Saudi Arabia’s most powerful supercomputer delivers a performance of 5,5 Petaflops, i.e almost 17 times less than China’s most powerful computer and 36 times less than the U.S. new Summit (see for more details on Summit, When AI started creating AI). If Saudi Arabia wants to be independent in terms of AI, then it will need to construct a strategy allowing it to overcome a possible lack of capacity in terms of computing power. The situation is even more challenging for a country such as the U.A.E, which, despite a willingness to develop A.I., does not have any supercomputer (U.A.E. AI Strategy 2031 – video).

Meanwhile, as another example, NVIDIA put online in 2016 supercomputer DGX Saturn V, which ranked 36 in November 2017 and delivers a performance of 3,3 Petaflops, but is built with DL in mind. Added to its other supercomputer, DGX SaturnV Volta, this means that NVIDIA has a computing power equal to 4,37 Petaflops thus superior to Russia, with its three supercomputers ranked 63, 227, 412 and exhibiting respectively performances of 2,1; 0,9 and 0,7 petaflops. Note that NVIDIA latest GPU accelerator, NVIDIA DGX-2 and its 2-petaFLOPS may only reinforce the company’s power (see part 1). In terms of international power, of course, Russia benefits from the attributes and capabilities of a state, notably its monopoly of violence, which NVIDIA does not have. Yet, imagining as seems to be the case, that the new emerging AI-world in construction increasingly integrates AI throughout state’s functions and governance, then Russia would face new dependency as well as new security challenges stemming from its relatively lower computing power. For its part, NVIDIA – or other companies – could progressively take over state functions, as shown in the example above of the U.S. defense JEDI. If we recall the British East India Company, that would not be the first time in history that a company behaves as a ruling actor.

Here these are the very principles of our modern Westphalian world that may potentially change.

However, things are even more complex than the picture just described, because the very hardware field is also being impacted by the AI-revolution, as identified in the first part. If we consider these hardware evolutions and changes, where is the necessary computing power, and, more difficult, where will it be?

Furthermore, if High Performance Computing power is so important, then, what can actors decide to do about it? They can build and reinforce their computing power, deny others’ computing power or find alternative strategies? This is what we shall see next, alongside changes in the hardware field.

Featured image: U.S. Army illustration, “Army research explores individualized, adaptive technologies focused on enhancing teamwork within heterogeneous human-intelligent agent teams.” in U.S. Army Research Laboratory (ARL), “Army researchers advance human-intelligent agent teaming“, Public Domain.

Artificial Intelligence, Computing Power and Geopolitics (1)

With this article we shall look more in detail at the relationship between Artificial Intelligence (AI) in its Deep Learning component, and computing power or hardware, a connection we started exploring with our previous article, “When AI Started Creating AI“. The foundations for understanding the link between AI-Deep Leaning and computing power being laid, the next article will focus on political and geopolitical consequences of this relationship, while considering a critical uncertainty uncovered here and according to which the evolution towards co-designing AI-Deep Learning architecture and hardware could alter the whole field.

Related

Artificial Intelligence, Computing Power and Geopolitics (2): what could happen to actors with insufficient HPC in an AI-world, a world where the distribution of power now also results from AI, while a threat to the Westphalian order emerges

High Performance Computing Race and Power – Artificial Intelligence, Computing Power and Geopolitics (3): The complex framework within which the responses available to actors in terms of HPC, considering its crucial significance need to be located.

Winning the Race to Exascale Computing – Artificial Intelligence, Computing Power and Geopolitics (4): The race to exascale computing, state of play, and impacts on power and the political and geopolitical (dis)order; possible disruptions to the race.

Our aim is to understand better how computing power can be at once driver, stake and force for AI expansion and the related emerging AI-world. Computing power is one of the six drivers we identified that not only act as forces behind the expansion of AI but also, as such, become stakes in the competition among actors in the race for AI-power (Helene Lavoix, “Artificial Intelligence – Forces, Drivers and Stakes” The Red Team Analysis Society, 26 March 2018).

In this article we show that AI-Deep Learning indeed needs large computing power, although varying across the different phases of computation and evolving with improvements. Even though advance of AI systems leads to a decreasing demand for computing power across the process of an AI-system’s creation, the very search for optimisation not only demands more computing power, but also leads to changes in the hardware field (which we shall see more in detail in the next article), and even, potentially, in terms of algorithms. Meanwhile, more computing power also means the capability to go further in terms of Deep Learning and AI, indeed confirming that computing power is a driver of AI expansion. Feedback loops or rather spirals are thus starting to appear between AI and its expansion and at least two of its drivers, computing power and “algorithms”.

We explain first the methodology used to uncover the link between AI-Deep Learning (DL) and computing power in a rapidly evolving ecosystem, and point out two likely new frontiers in the field of Deep Learning, namely Evolutionary Algorithms applied to Deep Learning in general and Reinforcement Learning. We also briefly present the three phases of computation of an AI-DL system. Then, we deep dive into each of the phases: creation, training or development, and inference or production. We explain each of the phase and the needs in terms of computing power for each of them. We then move beyond categorisation and explain the constant quest for improvement across the three phases, pointing out the balance that is sought between key elements. We notably emphasise there the latest evolution towards codesign of Deep Neural Network architecture and hardware.

The life of an AI-DL system and computing power in a rapidly evolving ecosystem – methodology

This is a premium article. To access this article, you must become one of our members. Log in if you are a member. A pdf version of the article is available for members.

Full Article: 3627 Words – pdf 11 pages

Featured image: ORNL Launches Summit Supercomputer on Flickr (Public Domain) 30 May 2018.

The U.S. Navy vs Climate and Ocean Change Insecurity (1)

The U.S. Navy is under higher and growing pressure from climate and ocean change. This situation is emphasized in The Impact of Sea-Level Rise and Climate Change on Department of Defense Installations on Atolls in the Pacific Ocean (Curt D. Storlazzi, Stephen B. Gingerich et al., February 2018, full pdf report), funded among others by the Department of Defense Strategic Environmental Research and Development Program (SERDP). This research shows that numerous Pacific atolls and islands are impacted by repeated floods and slat water infiltration, and could be submersed during the next decades because of the rising ocean, and as a result the U.S. Navy could be directly impacted because some of these islands are used as bases between America and the Asia-Pacific region. In other words, climate change-led rising ocean is putting at extreme risks the fulcrum needed by the U.S. Navy to project itself in the Asia-Pacific region (Charles Edel, “Small dots, Large strategic areas: US Interests in the South Pacific”, Real Clear Defense, 03 April 2018).

Meanwhile, climate change is also affecting the U.S. Navy on continental America, because of the ever-faster rise of the ocean, which interacts with the littoral where the U.S. Navy bases are installed (Jim Morrison, “Flooding Hot Spots: Why Seas are Rising Faster on the Eastern Sea Coast”, Yale Environment e360, April 24, 2018). Beside a rising ocean, climate change also means a present and future multiplication and reinforcement of extreme weather events. Those events are having a disrupting potential on the sea lanes navigated by the six US fleets (Bob Berwyn, “Hurricane Season 2018: Experts Warn of Super Storms, Call For New Category 6”, Inside Climate News, June 2, 2012). In other words, one should wonder if climate change, and the new emerging geophysical conditions that are currently emerging, are not jeopardizing the very infrastructures and missions of the U.S. Navy, thus imposing a perfectly unexpected but growing constraint on its global reach.

In a first part, we shall look at how climate change is literally “besieging” the U.S. Navy. In a second part, we shall look at the way this planetary challenge is imposing an ever-growing amount of “friction” on the infrastructures and missions of the U.S. Navy. Then, we shall wonder about the strategic consequences of the interactions between a changing climate and ocean and the U.S. Navy. Could we see these dynamics as a signal of a planetary assault on U.S. sea power over the coming years?

The US Navy and the climate-ocean Hyper siege

The rising ocean has started besieging the U.S. Navy. The rate of the sea-rise is rapidly accelerating, especially on the U.S. eastern coast: for example, in Florida, since 2006 the rise’s rate went from 3 to 9 millimetres a year (Erika Bolstad, “High ground is becoming hot property as sea level rises”, Scientific American, 1 May 2017). This accelerating rate is accompanied by a multiplication of high tide floods events (Jim Morrison, “Flooding Hot Spots: Why Seas are Rising Faster on the Eastern Sea Coast”, Yale Environment e360, April 24, 2018). For example, the Norfolk station, headquarter of the Atlantic fleet, and part of the gigantic Hampton roads complex, home to the nuclear aircraft carriers fleet, is flooded ten times a year nowadays (Laura Parker, “Who’s Still Fighting Climate Change? The U.S. Military”, National Geographic, February 7, 2017).

https://www.youtube.com/watch?v=psDE4Ccqui8&t=1s

Overview of US Navy base at Naval Station Norfolk and Shipyards (https://www.youtube.com/watch?v=psDE4Ccqui8&t=1s)

This situation is already exerting a growing pressure on the military readiness of the station and of all those installed around the Chesapeake Bay, because of the cascade of disruptions and costs triggered by the floods, including cleaning up and repairs. According to an estimate by the Union of Concerned Scientist, the sea level in this area has already risen by a staggering 14.5 inch (35,5 cm) since 1914. Given this trend, the region will be flooded more than 280 times a year in 2100 (The US Military on the Front Lines of Rising Seas, 2016, Rising seas will increasingly flood many of our coastal military bases, Union of Concerned Scientists, 2016). It appears extremely dubious that the Norfolk station and the Hamptons Road complex could remain functional in their current form, while being assaulted by hundreds of flooding events every year.

As showed by the 2018 Department of Defense “Climate-Related Risk to DoD Infrastructure Initial Vulnerability Assessment Survey (SLVAS) Report”, the climate change-led ocean rise that besieges the Norfolk station is shared, with variable degrees of intensity, by the other U.S. naval bases of the East and West Coast (including Hawaii), while many of the U.S. bases located abroad will most often meet the same fate. In other terms, the U.S. Navy, as a mammoth and global organization, is under climate-ocean change siege.

U.S. Navy area of responsibility -U.S. Naval Forces Europe-Africa / U.S. 6th Fleet – map [Public Domain]

Indeed, the very global scale of the U.S. Navy’s deployment reinforces the climate-ocean siege situation. The U.S. Navy is composed of 6 operating fleets, each of them assigned to an area of responsibility (AOR) covering a part of the Atlantic, of the Indian Ocean or of the Pacific ocean and thus, as a whole, able to reach each and every littoral on Earth (US Navy). This extensive capability of force projection confers de facto a global reach to the American sea power. However, these fleets are dependent on the multiple ports of anchorages, bases and other facilities on the American mainland, as well as in other countries such as, among others, Japan, Italy, Spain, Greece, Bahrain, Kuwait, Qatar, Saudi Arabia, the United Arab Emirates, Djibouti, El Salvador, Egypt, Cuba, Hong Kong, South Korea, Singapore, and the Philippines (US Navy Bases, Wikipedia, and Commander Navy Installations Command Map).

Click to access interactive map of the website of Commander, Navy Installations Command (CNIC)

The littoral of these countries are also affected by the rising ocean and by the multiplication of climate change-related extreme weather events, as is tragically shown, for example, by the growing series of giant hurricanes battering the Philippines (Andrea Thompson, “Land Falling Typhoons have Become More Intense”, Climate Central, September 5, 2016). In Japan, the Yokosuka naval base in Tokyo is severely assaulted by storm surges and ever-more powerful tempests, which accompany the warming and rising ocean (Forrest L. Reinhardt and Michael W. Toffel, “Managing Climate change: Lessons From the US Navy”, Harvard Business review, July-August 2017 issue). In Alaska, the thawing permafrost necessitates the relocation and rebuilding of existing bases (Reinhardt and Toffel ibid). Similarly, the home of the Pacific fleet in Hawaii must face a growing number of mudslides and flash floods (Reinhardt and Toffel, ibid).

https://www.youtube.com/watch?v=Z0Jzb8dfcC4&rel=0

USS Kitty Hawk (CV-63) slammed by giant wave during typhoon (https://www.youtube.com/watch?v=Z0Jzb8dfcC4&rel=0)

The same can be said of the bases located in the Pacific such as Guam and the Marshall Islands, which are under growing pressure from the rising ocean, to the point that some of their composing atolls could be submersed within 12 years (Curt D. Storlazzi, et al., Ibid.). In the meantime, there is a high and growing risk of a multiplication of floods on these islands, already battered by the ocean. Consequently, the salt water of the sea is infiltrating the water sources of the atolls. This situation could soon trigger a potable water crisis for the islands and the Navy bases (John Conger, “Study: Atolls Hosting Critical Military Sites May Be Uninhabitable in 12 Years”, The Centre for Climate and Security, April 27, 2018). As shown by these examples, the planetary change currently occurring is imposing a global pressure on the network of Navy bases. In other words, the very worldwide fulcrum of the U.S. sea power meets what we call here “planetary friction”.

“Planetary friction” and U.S. sea power

Beyond the immediately catastrophic impact of the extreme weather events and their human, social and economic toll, these events and the rising of the ocean are signals of a new planetary and geopolitical reality (Jean-Michel Valantin, “Climate Blowback and US National Security”, The Red (Team) Analysis Society, March 31, 2014). As a matter of fact, the rise of the ocean is due to the convergence of the warming and dilatation of the surface waters, and of the ever-increasing warming and melting of the terrestrial ice caps of Greenland, Antarctica and of the continental mountain ranges.

https://www.youtube.com/watch?v=Vn3_hviRfdU&rel=0

Anthropocene: The closing doors of climate targets (https://www.youtube.com/watch?v=Vn3_hviRfdU&rel=0)

This convergence of the warming ocean and melting ice sheets leads to a global process of accelerated and heightening rise of the ocean at a planetary scale, while the warming atmosphere-ocean interface is becoming the emergence system of a growing number of extreme weather events (Chris Mooney, “Greenland and Antarctica isn’t just raising seas- it’s changing the Earth’s rotation”, The Washington Post, April 8, 2016). In other terms, the warming and rising of the ocean will be more and more important and powerful. According to the most conservative studies, the ocean will rise by almost one meter between today and 2100 (IPCC Report, 2018). However, numerous studies point out the risk of a much higher rise: between 2 and 5 meters (Robert de Conto and Robert Pollard, “Contribution of Antarctica to past and future sea level rise“, Nature, 31 March 2016, Eric Holtaus, “James Hansen Bombshell’s climate warning is now part of the Scientific canon”, Slate.com, March 22, 2016 and Chris Mooney, “One of the most Worrysome Prediction About Climate Change Maybe Coming True”, The Washington Post, April 23, 2018). That would be a civilization-changing event.

The massive strategic problem linked to this new epoch is that the planetary present and future are now dominated by complex dynamics of global change, also qualified as being the signals of the new and current geological epoch named the “Anthropocene”, i.e the geological epoch defined by the consequences of human development, which creates its own stratigraphic signal (Jean-Michel Valantin, “The Planetary Crisis Rules, Part. 1 and Part. 2”, The Red (Team) Analysis Society, January 25, 2016 and February 15, 2016). In this regard, the planetary crisis has become a major generator of friction, i.e., according to Clausewitz, a system of pressure and constraint. This “planetary friction” exerts itself upon the American sea power, i.e. upon the way the U.S. extends its military power onto the sea, and through the sea, towards other nations, because the U.S. sea power is the Naval form of the U.S. (geo)political will (David Gompert, US Sea Power and American Interests in the western Pacific, 2013).

https://www.youtube.com/watch?v=59CyXAUEa2M&rel=0

The toll of climate change, from US to the Marshall Islands: 'No one's an exception' (https://www.youtube.com/watch?v=59CyXAUEa2M&rel=0)

As such, the U.S. sea power is a major and essential component of the U.S. global power. The U.S. Navy is crucial to project forces and to, potentially or actually, exert coercion on a global scale, on the sea, as well as from the sea to littoral and hinterlands, through the use of planes, drones, missiles and cyber capabilities. Its global network of bases ensures a global refuelling capability. Being composed of complex and technologically updated platforms, the U.S. Navy is also a core part of the U.S. land, air, space, nuclear and cyber power, notably through the complex networks of interactions with satellite constellations, and its 11 nuclear aircraft carriers groups (e.g. Chief of Naval Operations, Future Navy, May 2017; Technology for the United States Navy and Marine Corps, 2000-2035 Becoming a 21st-Century Force: Volume 6: Platforms (1997), Chapter: 2 Surface Platform Technology). The U.S. navy is also a major actor for troops transportations.

Taken together, those different capabilities are essential components of the global U.S. military power, which thus appears as profoundly dependent on its maritime dimension. However, nowadays, it has started meeting the growing resistance of the “living and reactive force” (Clausewitz, On War, 1832), in our case the warming ocean. As Edward Luttwak (Strategy, the Logic of War and Peace, 2002), following Carl von Clausewitz (On War, 1832), points out about friction, there is strategy when will is applied against a resisting and reacting object, for example during a war, or, in our case, when ocean change imposes resistance and constraint to the political will embedded into and dependent upon naval infrastructures and fleets.

A signal of the things to come: friction in an age of planetary crisis?

As a result, the different U.S. Navy operations are meeting a growing level of friction, and thus of potential disruption. For example, the U.S. Navy and the U.S. Air Force are collaborating in order to manage the Air Force station of the Kwajalein Island, part of the Marshall Islands. The mission of this base is to monitor the “space fence”, i.e. the planetary wide debris belt around the Earth, in order to optimize the trajectory of U.S. civil and military space missions. The multiplication of flood events and of salt-water infiltration, as well as the coming submersion of the Island are exerting a complex “friction” upon the base, and thus upon the space mission, which will no longer be viable when the Island will be submersed (Conger, ibid). This example shows how the interactions between the U.S. Navy and the ocean, i.e. the medium that defines and determines the Navy very existence, are becoming factors of growing and immense friction with cascading effects: in this case, the pressure exerted by the rising ocean upon sea power is transferred to an infrastructure of space power (Timothy Mc Geehan, “A War Plan Orange for Climate Change”, Proceedings Magazine, U.S. Naval Institute, October 2017).

It means that the very environmental medium of the U.S. sea power is becoming a planetary-wide system of constraints on this very power, while the constraints will only become stronger. This implies that, in a very unexpected, strange and disturbing way, the Anthropocene epoch is thus emerging as a new kind of strategically disruptive force that, in the U.S. Navy case, exerts itself on the very capabilities upon which the US military might is built.

https://www.youtube.com/watch?v=dPXmekq3bTM&rel=0

Houston Under Water: Special Report (https://www.youtube.com/watch?v=dPXmekq3bTM&rel=0)

Knowing the importance of the U.S. sea power for the global U.S. force projection capabilities, this raises the question of the future of the U.S. sea power in a time of rapidly worsening planetary crisis. As a result, the U.S. Navy now navigates an ocean of strategic uncertainty, as well as other historic and new maritime powers, such as Russia and China.

About the author: Jean-Michel Valantin (PhD Paris) leads the Environment and Geopolitics Department of The Red (Team) Analysis Society. He is specialised in strategic studies and defence sociology with a focus on environmental geostrategy.

Featured Image: Defense Department facilities are visible in this satellite photo of Roi-Namur Island. Credit: DigitalGlobe. Public Domain, from USGS “Pacific Missile Tracking Site Could Be Unusable in 20 Years Due to Climate Change“.

Timeliness: enabling the coordination of response

Timeliness, credibility and biases

Timeliness as the intersection of three dynamics

References

The Race to Exascale

State of Play

Feedbacks and impacts

Notes and Additional Bibliography

Definition of Strategic Foresight and Warning – Risk management for strategic uncertainties

Futures Studies (also futurology)

Forecasting

Foresight

Horizon Scanning

Intelligence

National Intelligence Estimate

National Intelligence Assessment

La Prospective

Risk Management

Risk Management

Risk Assessment

Political risk

Risk governance

Science

Strategic Analysis

Strategic Anticipation

Strategic Foresight

Strategic crisis management

Strategic Futures

Strategic Warning

Strategic Intelligence

Selected Bibliography

Impact on Issues and Uncertainties

Facts and Analysis

Sources and Signals

Impact on Issues and Uncertainties

Facts and Analysis

Source and Signal

The warming ocean as a massive resource threat

Littorals and economy under siege

Bonding with Chaos: opening a window on the future

Living without high performance computing power in the age of Artificial Intelligence: dependency and loss of sovereignty

Choice 1: No AI-systems and Non-AI actors

Choice 2: Suboptimal AI-systems

Choice 3: Optimal AI but created on external computing power

Choice 4: Optimal AIs but created by others

Distribution of Power in the AI-World, High Performance Computing Power and Threat to the Westphalian System?

The life of an AI-DL system and computing power in a rapidly evolving ecosystem – methodology

The US Navy and the climate-ocean Hyper siege

“Planetary friction” and U.S. sea power

A signal of the things to come: friction in an age of planetary crisis?

GDPR, Privacy and Cookies