★ Sensor and Actuator for AI (2) – Artificial Intelligence, the Internet of Things and the Future of Agriculture: Smart Agriculture Security? (1)

This article explores the way artificial intelligence (AI) is inserted within its environment through the Internet of Things in a particular domain, agriculture. As a result, “smart agriculture”, a whole new way to produce food, is born. We look at the way various actors include AI in farming and thus envision and develop the future of agriculture. We then evaluate consequences on the best way to develop and integrate AI into real life activities. Meanwhile, we assess the impact of smart agriculture not only on agriculture security, but also on governance and geopolitics.

This is the second article of the series exploring the interface between artificial intelligence and its environment, as well as related impacts on society, politics and geopolitics.

This twin interface is composed of sensor and actuator. A sensor is what senses the world around the AI, be it digital or real, to input it into the AI-agent. The actuator is the end of the AI process. It allows outputting the results found by the AI-agent in the world, again, be it digital or material, in a way that is understandable to human beings.

This twin interface is a disruptive driver for AI. Indeed, success in handling and developing sensor and actuator, or on the contrary, failure to do so, could favour the boost or burst of the current AI development phase for actors. Furthermore, the key importance of this interface implies it is a stake in the current race to AI-power, besides the other drivers of AI.

We started exploring in detail this twin interface in the first article of the series, “Inserting Artificial Intelligence in Reality“. Using those examples, we found that we could best understand and handle AI if we conceptualised the interface as a sequence between worlds: the world intelligible to humans and the world intelligible to AI-agents. Finally, we started looking at the way AI-agents could be integrated according to different realities: digital-digital and digital-material.

Content – Published in two parts (see here for the second part). The table of contents becomes interactive only for members.
  1. The IoT, an ideal ecosystem for AI-agents
    1. A brief history of the IoT, or the development of an ideal ecosystem for AI
    2. The IoT and its domains of applications
  2. AI and IoT in action – Smart Agriculture
    1. Facing the challenges of food security
    2. Smart agriculture as an answer to food security
    3. Corporate actors – The road beyond sensors and digital-digital output only
  3. Impacts and consequences
    1. Surprise, Surprise! Those key actors for the spread of AI …
    2. Knowledge is power
    3. Smart agriculture security?

This article, published in 2 parts, dives deeper into the twin interface that allows integrating AI in human reality. It notably looks for actuators.

In the first part, we look at the Internet of Things (IoT). Indeed, it is a first type of ecosystem within which AI-agents may find and use sensors and actuators, and thus be fully operational and thrive. Thus, we explain what is the IoT and why it is a favorable ecosystem for AI-agents.

Then, we focus as case study on “smart agriculture” aka the Internet of Food. We explain first what is smart agriculture. Meanwhile, we highlight how it is an answer to the challenges of current and future food security.

In the second part, we look at how companies whether giant ones, start-ups or projects, insert AI-agents in the real world. We notably feature “John Deere FarmForward 2.0 – Revolutionizing agriculture, one plant at a time”, which goes way beyond what the usual giant actors of the digital world, such as the U.S. GAFAM, promote.

John Deere’s video and others’ endeavours help us imagine how smart farming will look like. Their effort at creating not only sensors, but also actuators is crucial.

Finally, we turn to the impacts and consequences of smart farming. We find first that, considering the stage of development of AI, those actors that are currently crucial to see a further implementation of AI are not the giant digital companies, but those offering a real operationalisation of AI in the physical world. We then highlight how new beholders of data and thus related knowledge could impact the power of traditional actors. Third, we look at the new security needs of agriculture and how this potentially impacts international relations and geopolitics.

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FULL ARTICLE 6353 WORDS – pdf 23 pages – plus bibliography


Featured image: Herney via Pixabay, Public Domain.


*Note that, as with previous estimates, this trend does not include the devastating impacts of climate change. Likewise, other disasters a large population could foster are not considered.. Among others, we already pointed out this possibility in 2008, see also, for example David Talbot, “U.N. Predicts New Global Population Boom“, MIT Technology Review, 2014.

Bibliography and References

Ackerman, Jennifer, “Food: How Altered?“, National Geographic, nd.

American Institute of Physics, “Autonomous weed control via smart robots“, Science Codex, 27 March 2019.

Ashton, K. (22 June 2009). “That ‘Internet of Things’ Thing”.

Beecham Research,”Machine to Machine (M2M) – IoT”.

EESC European Economic and Social Committee, Internet of Things — An action plan for Europe“, COM(2009) 278 final; OJ C 255, 22.09.2010, p. 116-120.

European Union’s Horizon 2020 research and innovation programme, Internet of Food & Farm 2020 (IoF2020),

Fourtané, Susan, “IoT and Smart Agriculture Are Building Our Future Cities Today“, Interesting Engineering, 7 October 2018.

Gagliordi, Natalie, “How self-driving tractors, AI, and precision agriculture will save us from the impending food crisis“, TechRepublic, 12 December 2018.

Graham, Luke, “UN raises world population forecast to 9.8 billion people by 2050 due to rapid growth in Africa“, CNBC, 22 June 2017

IEEE – Institute of Electrical and Electronics Engineers – Project Standard for an Architectural Framework for the Internet of Things (IoT), Shenzhen, China, January 2019

ITU-T Rec. Y.2060 (06/2012) Overview of the Internet of things.

Magrassi, P. and Berg, T (12 August 2002). “A World of Smart Objects”Gartner research report R-17-2243.

Mattern, Friedemann; Floerkemeier, Christian (2010). “From the Internet of Computer to the Internet of Things” (PDF). Informatik-Spektrum33 (2): 107–121.  doi:10.1007/s00287-010-0417-7

McLellan, Charles, “Smart farming: How IoT, robotics, and AI are tackling one of the biggest problems of the century“, TechRepublic, 12 December 2018.

Nafeez, Ahmed, “Dramatic decline in industrial agriculture could herald ‘peak food’“, The Guardian, 19 December 2013

Newell, Heather, Hendrik Viljoen, “Stability analysis of a thin film on a rotating cylinder with low airflow“, Physics of Fluids, 2019; 31 (3): 034106 DOI: 10.1063/1.5080443

Raiwani, Y.P., “Internet of Things: A New Paradigm“, International Journal of Scientific and Research Publications, Volume 3, Issue 4, April 2013.

Shubo Liu, Liqing Guo, Heather Webb, Xiao Yao, Xiao Chang “Internet of Things Monitoring System of Modern Eco-agriculture Based on Cloud Computing“, 2169-3536 (c) 2018 IEEE, DOI 10.1109/ACCESS.2019.2903720, IEEE Access.

Talbot, David, “U.N. Predicts New Global Population Boom“, MIT Technology Review, 2014.

Valantin, Jean-Michel Valantin, “Understanding (or not) the Nature of Climate Change as a Planetary Threat“, The Red (Team) Analysis Society, 10 December 2018

Walter, Achim, Robert Finger, Robert Huber, and Nina Buchmann, “Opinion: Smart farming is key to developing sustainable agriculture“, PNAS,  June 13, 2017 114 (24) 6148 6150; https://doi.org/10.1073/pnas.1707462114

Weiser, Mark (1991). The Computer for the 21st Century (PDF). Scientific American265 (3): 94–104.  doi:10.1038/scientificamerican0991-94.

Scenarios: Improving the Impact of Foresight thanks to Biases

Foreseeing the future, whatever the name given to the endeavour, includes two major tasks.

The first one is, of course, the analysis, the process according to which the foresight, forecast, warning, or, more broadly, anticipation is obtained.

The second one is less obvious, or rather so evident that it may be overlooked. It is, however, no less vital than analysis. We need to deliver the output of the analytical process to those who need the foresight, the decision-makers or policy-makers. Ideally, the recipients must understand that output, because they will act on it. They need to integrate the new knowledge received in the decisions they will take.*

A huge challenge runs across these tasks: biases.

We must overcome the various natural and constructed biases – systematic mental errors – that limit human understanding. This article will present first the classical way we deal with biases: we consider them – quite rightly – as “enemies” and we devote much effort to mitigate them. Then, considering the specificity of the delivery stage, this article suggests that another strategy is necessary. We need to turn our usual strategy on its head and befriend biases. In that case, scenarios become a tool of choice for an enhanced delivery of our foresight to decision-makers […]

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The Chronicles of Everstate: the Actors

The Everstatans: the citizens (including companies), the people, the Nation Everstate’s central governing bodies or political authorities: the government, Parliament, the national representatives, the civil servants constituting the formal and rational modern bureaucracy. Everstate’s regional and local governing bodies: elected representatives at town, department (or county) and region level. Everstate’s political parties: Two major parties (loosely associated with social democrats on the one hand and conservative on the other). Other parties are insignificant in terms of national representation. International Special fund for Sustainable Innovation and Green Energy (ISSIGE) [Scenario 2 – Panglossy]: A special fund into which the new Everstatan government decides that Everstate must participate. This fund will help polities harnessing the ecological evolution and the increasing complexity of resources, …

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Saudi Arabia and the Chinese Belt and Road: the Great Convergence

In February 2019, during the Saudi Arabia-China economic forum, the two countries signed for more than 28 billion dollars deals (“Saudi-Chinese Investment Forum Signs 35 Deals During Crown Prince’s Beijing Visit”, Ashark Al Awsat, 22 February, 2019). These gigantic deals are part of the growing Saudi-China relationship. They are the economic and political continuation of the six weeks tour in Asia King Salman of Saudi Arabia made in March 2017. This tour ended with a state visit in China and a meeting with Chinese President Xi Jinping. The visit included the opportunity to start the negotiations about the integration of Saudi Arabia to the Chinese Belt and Road Initiative (BRI), actually a grand strategy (Michael Tanchum, “Saudi Arabia the next stop on China’s maritime silk road”, East Asia Forum, 22 March 2017).

This article explores how the specificities of the Chinese BRI and of the Saudi grand strategy create and deepen the existence of converging strategies for the two countries.

Continue reading “Saudi Arabia and the Chinese Belt and Road: the Great Convergence”

Horizon Scanning and Monitoring for Early Warning: Definition and Practice

(Rewritten and revised edition) Horizon scanning and monitoring for early warning are part of the family of activities used to foresee the future, anticipate uncertainty and manage risks. Their practice is crucial for successful strategic foresight and warning, risk management, futurism or any anticipatory activity.

While monitoring is a generic and common term used for many activities, horizon scanning is very specific and used mainly for anticipation. Horizon scanning is a term that appeared in the early years of the 21st century. It refers both to a specific tool within the strategic foresight process and to the whole anticipatory process (Habbeger, 2009).*

We shall here focus on horizon scanning as a specific tool within the entire strategic foresight process. We shall contrast it to monitoring for warning (hereafter monitoring). First, we shall present definitions for the two concepts. Then, using comparison of the practice of the two activities, we shall highlight the similarities and differences between the two. Meanwhile we shall identify best practice. Finally, we shall conclude that horizon scanning, as a tool, is, actually, the first step of any – good – monitoring for anticipation.

Definitions for horizon scanning and monitoring

Horizon Scanning

As a tool, horizon scanning allows for the identification of potential new themes or meta-issues and issues, answering our concerns as defined in our agenda or context. We shall then need to analyse in-depth the issues thus identified.

Horizon scanning looks thus for weak signals indicating the emergence of new meta-issues and issues. As a result, a scan must adopt the largest possible scope for the core question under watch.

horizon scanning, warning, monitoring, intelligence, risk management, futurism
Meteorological Service of Canada (Environment Canada): Non meteorological data from weather echos can be filtered by using Doppler velocities of targets. After cleaning, only real precipitation is left.

The idea of horizon scanning is built upon older ideas and methods such as “environmental scanning,” “strategic foresight” and “indications and warning” (also labelled “strategic warning” and “warning intelligence” see Grabo, 2004). Actually, as Glenn and Gordon underline, in the 1960-1970s, most futurists used the term “’environmental scanning’. However, as the environmental movement grew, some thought the term might only refer to systems to monitor changes in the natural environment because of human actions. To avoid this confusion, futurists created various labels, such as “Futures Scanning Systems”, “Early Warning Systems” and “Futures Intelligence Systems”. The military, for its part, uses “strategic warning’ and related terms. The objective is to avoid strategic surprises (e.g. Pearl Harbour).

The English “horizon scanning” is not the same as the French “veille”, on the contrary from what some authors assert – e.g. Nicolas Charest (“Horizon Scanning” 2012 and pdf). We could best translate “veille” by “monitoring” – taken in a general way, and not more specifically for warning as here. We could also translate it as “intelligence gathering”.

Charest, actually, refers to a process: “an organised formal process of gathering, analysing and disseminating value-added information to support decision making”. Yet, this is a process from which the future and anticipation are absent. Strangely enough, the author himself underlines that the English meaning of horizon scanning implies foresight, anticipation.

Rather than conflating two practices and two words, “veille” and horizon scanning, it is necessary to distinguish both. Indeed, even though the two activities are closely related, one, horizon scanning, has to deal with the future, when the other does not have to face this challenge.

It is the anticipating quality, the necessity to “make a judgement on the future” to use Grabo’s word (Ibid.), that generates the essential difference between the two related activities.

The use of “horizon scanning” in the denomination of various governments’ offices contributed to popularise the name. For example, we had the UK Horizon Scanning Centre, created in 2004 after a call for developing such centres of excellence across government (Habbeger, 2009, p.14), or Singapore’s Risk Assessment and Horizon Scanning (RAHS) programme, launched in 2005 (Lavoix, 2010). The way the idea became fashionable also contributed to the confusion surrounding its meaning.

Monitoring for warning

Monitoring is a part of the strategic warning process. The literature on intelligence, warning and strategic surprise documents well the idea and the process. Indeed, actors have used strategic warning since at least WWII, while intelligence studies are now a constituted body of knowledge and a discipline. For further readings, there used to be an excellent bibliography of reference on intelligence related matters: J. Ransom Clark’s Bibliography on the Literature of Intelligence, notably the section on strategic warning. Unfortunately, it has been taken down. However, it can still be accessed through the internet archive, even the section on strategic warning, but with various dates which may not correspond to the latest version, now lost.

Monitoring issues will allow for the identification of warning problems. We shall then use adequate models and related indicators for the surveillance of those problems. As a reminder, an indicator is a concept and abstraction for something. An indication is the reality corresponding to the indicator at a specific instance. We thus use indicators to collect indications. For example growth of gross domestic product (GDP) is an indicator and 5% is an indication for a specific country and time. Speed can be an indicator and 60 km/h an indication on a specific place for a specific device at a specific time.

Both monitoring and surveillance lead the collection of necessary information, as defined by the model and related indicators.

As a reminder, throughout the whole SF&W process, we process to a narrowing down of our focus, which the vocabulary used reflects. We move from the most general and encompassing to the most detailed. Let us take as example energy as a “meta-issue”. Then, “issues” could be “oil security,” “peak oil,” “peak uranium,” “the volatility of oil prices,” “the politics of energy between Europe and Russia,” “energy for China,” etc. “Problems” could be the more specific “Gasprom policies,” “the Keystone pipeline,” “Energy in the Belt and Road Initiative”, or “Energy and the Belt and Road Initiative in Pakistan”, or even “tension around this or that plant”, etc.

Horizon scanning and monitoring for warning in practice

If definitions differ, is there truly a difference in the way we do horizon scanning on the one hand, monitoring for warning on the other? Is scanning included in monitoring for warning? Should we use the same processes and the same tools for scanning and for monitoring? Or do we have to use different approaches?

Similarly grounded in models, but different sophistication of models

A first difference between horizon scanning and monitoring is the location of each within the overall SF&W process. A scan is the first step of any analysis. What does that imply?

horizon scanning, warning, monitoring, intelligence, risk management, futurism

As it is the very first thing you do when tackling an issue, then scanning the horizon implicitly assumes that no understanding or little understanding of the question exists. Yet, actually this is only an appearance.

Try to make the exercise mentally: if you start looking for something, even in the loosest way, to do that you need to have an idea, even minimal, of what you are looking for. What happens is that, unconsciously, you rely on a cognitive model. This cognitive model is implicit. Thus, to scan the horizon you already use a model, even if it is a very imperfect one.

Further away in the process of foresight or risk analysis, you monitor an issue. This is meant to happen towards the end of the analytical process, thus once you know very well your topic. On the figure above, monitoring takes place after we have created the scenarios and identified the indicators for warning.

Monitoring is thus also grounded in a model. However, we have made that model explicit. We have improved and refined it through the process of analysis.

Thus, fundamentally, both horizon scanning and monitoring are similar. Their difference, here, resides actually in the sophistication of the model used, not in the actual process utilised to do scanning or the first steps of the monitoring. Hence, scanning and monitoring can utilise most often the same of tools or supports.

Broad outlook, enmeshed outputs

Second, the definition of a scan suggests that it should only identify weak signals. However, to select beforehand signals according to their strength – assuming this is possible – would be counter-productive and in some cases impossible. Indeed, a strong signal for an issue can also, sometimes, be a weak signal of emergence for something else.

Thus, when gathering signals through a scan that aims at identifying emerging meta-issues and issues, it is desirable to be as broad and encompassing as possible.

In practice, you can note new signals, and loosely start linking them to other meta-issues or issues.

Similarly, monitoring of an issue and surveillance of a problem may also pick upon signals of novel issues emerging. Again, you should make sure you record these findings.

Thus for both horizon scanning and monitoring, you need to have a cognitive make up that is as open and as broad as possible, while also, at the same time being able to link precisely this or that fact, trend or “thing” to this issue, that problem and this indicator.

Signals and their strength for horizon scanning, indications and timeline for monitoring

horizon scanning, warning, monitoring, intelligence, risk management, futurism, bias
Image by Jens Langner (http://www.jens-langner.de/) (Own work), Public domain, via Wikimedia Commons

Last but not least, because of various biases, both analysts and clients, decision-makers and policy-makers are often unable to see, identify, and consider some signals “below the horizon.” They will be able to accept those signals only when they are “above the horizon,” which means when they are much stronger, as exemplified in the article on timeliness.

The position of the signal below or above the horizon, or the strength a signal needs to have to see actors perceiving and accepting it, will vary according to person.

It is thus not practically desirable to try sorting out signals according to their strength too early in the process.

In the case of monitoring and surveillance for warning, it is also crucial to sort the indications according to a timeline. That time sequence warns us about the evolution of the issue under watch. Finally, it will allow for the warning and its delivery. At least mentally, each indication or signal, or group of indications and signals must be positioned on their corresponding timelines. We use a plural here, because indications and signals can feed into different dynamics for various issues, as seen in the previous part.

We thus look at strength – for signals. On the other hand, we focus on timeline for indicators and their indications. Thus, does that mean that scanning and monitoring are different?

Actually, the strength of a signal for horizon scanning may be seen as nothing else than an indication of the movement of change on a timeline. Let me explain that further. If the signal is weak, then the situation is far from the actual occurrence of an event or phenomenon. On the contrary, if the signal is strong then one is close to it. A scan would thus be an instance of monitoring, where only indications leading to judgements according to which an event will not happen soon, but nevertheless deserve to be put under watch, are selected.

However, as we saw that it is neither desirable nor sometimes possible to sieve through signals according to their strength, then this vision of a scan is idealistic and impractical.

As a result, and practically, at the end of the process, a scan will gives us signals of varying strength. At that stage, we shall only have a relatively weak confidence of the very strength of the signals identified. In that case, using strength of signal would be a precursor to a much more refined judgement made in terms of timeline.

Horizon scanning thus corresponds to the first stage of monitoring (and surveillance) before judgements related to the signification of the signal, or indication in terms of timelines, are made. It thus exists not only at the very beginning of the whole SF&W process, but each time we monitor.


* The debate on national security is rich and features many authors. For a brief summary of and references to the many outstanding scholars who inform it, e.g. Helene Lavoix “Enabling Security for the 21st Century: Intelligence & Strategic Foresight and Warning,” RSIS Working Paper No. 207, August 2010.


This is the 2d edition of this article, substantially rewritten and revised from the 1st edition, June 2012.

Featured image: U.S. Navy by tpsdave. CC0 Public Domain

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.

Bibliography and References

Charest, N. (2012), “Horizon Scanning,” in L. Côté and J.-F. Savard (eds.), Encyclopedic Dictionary of Public Administration.

Gordon, Theodore J. and Jerome C. Glenn, “ENVIRONMENTAL SCANNING,” The Millennium Project: Futures Research Methodology, Version 3.0, Ed. Jerome C. Glenn and Theodore J. 2009, Chapter 2.

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

Habbegger, Beat,  Horizon Scanning in Government: Concept, Country Experiences, and Models for Switzerland,    Center    for    Security    Studies    (CSS),    ETH    Zurich,    2009.

J. Ransom Clark’s Bibliography on the Literature of Intelligence.

Lavoix, Helene, What makes foresight actionable: the cases of Singapore and Finland. (U.S. Department of State commissioned report, December 2010).

Lavoix, Helene, “Enabling Security for the 21st Century: Intelligence & Strategic Foresight and Warning,” RSIS Working Paper No. 207, August 2010 (also accessible here).

When Risk Management Meets Strategic Foresight and Warning

Risk management is codified by the International Organization for Standardization (ISO). It is aimed at any organisation concerned with risk, be it public or private (Sandrine Tranchard, “The new ISO 31000 keeps risk management simple“, ISO News, 15 Feb 2018). Its forebear is actuarial science, i.e. methodologies to assess risk in insurance and finance (e.g. ENSAE Definition). Its study, as a discipline mainly of use to the private sector, progressively developed after World War II (Georges Dionne, “Risk Management: History, Definition, and Critique“, Risk Management and Insurance Review, Volume16, Issue2 ,Fall 2013, pp. 147-166).

Another “non-academic” discipline deals with risks, uncertainties, threats and opportunities or more exactly surprise. Its name is Strategic Foresight and Warning (SF&W). It results from the meeting of the older military Indications and Warning and from Strategic Foresight. Intelligence and military officers mainly developed SF&W for their needs regarding international and national security issues. Strategic Warning, for its part, for example, remains an essential mission, for example, of the U.S. Defense Intelligence Agency (DIA) as reasserted in its September 2018 Strategic Approach. Meanwhile, classical reference books on Strategic Warning are now part of the DIA 2018 Director’s Reading List. Strategic Warning and SF&W are more specifically the origin and outlook of our experience and practice here, at the Red (Team) Analysis Society.

Both disciplines and practices, risk management and SF&W, thus have different history, actors and aims. Yet, since the ISO revised risk management in 2009, we now have an almost perfect correspondence between SF&W and risk management. The ISO 2018 update confirms the similarity. This article will detail further the two processes, their similarities and complementarities.

CIA NYSE sc

The new risk management process thus lays the foundation for easily incorporating into the risks usually managed by businesses, all national and international security issues as usually related to states’ national interests, from geopolitics to politics, from criminality to war through cyber security. In other words, the process used to manage both the external and internal risks the corporate world faces is now similar to the way states handle their mission of international and domestic security, according to their national interests.

Meanwhile, these very similarities between risk management and SF&W should facilitate discussions and exchanges between the corporate world and the public sector, including in terms of data, information, analysis and process, according to the specificities and strength of each. When differences between SF&W and risk management subsist, we may turn them around to take the best of both world.

Indeed, what matters is to anticipate properly what lies ahead and to take adequate policies. It is not to abide by one label or another.

In this article, we detail the risk management process. We explain the new definition of risk. Then we underline the similarities with SF&W. We stress, where risk management is most different from SF&W, how the former could also help the latter. Notably, risk management provides a framework to address a sensitive area: developing and offering policy or response alternatives to decision-makers.

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FULL ARTICLE 3017 WORDS – pdf 15 pages


Featured Image:  President Barack Obama attends a meeting on Afghanistan in the Situation Room in the White House. On his left, National Security Adviser James L. Jones, Secretary of State Hillary Clinton, U.S. Ambassador to the United Nations Susan Rice, National Intelligence Director Dennis C. Blair and CIA Director Leon Panetta. To his right, Vice President Joe Biden, Secretary of Defense Robert Gates (hidden), Chairman of the Joint Chiefs of Staff Admiral Michael Mullen, White House Chief of Staff Rahm Emanuel. – 9 octobre 2009, The Official White House Photostream, White House (Pete Souza) – Public Domain.

Copyrights for all references to ISO norms remain with the International Organization for Standardization (ISO).

This article is a fully updated and revised version of a text that was published first as an element of the U.S. Government commissioned report, Lavoix, “Actionable Foresight”, Global Futures Forum, November 2010 (pp. 12 & 20-24/98). 

Climate change: Shall we live or die on our changing planet ?

A cavity 1000 feet tall (1600 metres), and as large as two thirds of Manhattan has been found inside the Antarctic Thwaites glacier (Sarah Sloat, “An Enormous Cavity Inside an Antarctic Glacier Harbors a Dangerous Threat », Inverse Daily, February 1, 2019).

It has been created in three year by inside warming and melting. This shows the acceleration of the process, as well as the destabilization of the entire glacier and of its neighbours (Sloat, ibid).

The sole melting of the Thwaites glacier could add two feet to the global rise of the ocean.

Continue reading “Climate change: Shall we live or die on our changing planet ?”

The Quantum Times (Daily Updates)

Horizon scanning on Quantum Information Sciences and technologies and their use.
As a result we publish the Quantum Times, a daily scan and news brief on everything related to the emerging Quantum world. The Quantum Times is updated daily before 9:00 ECT.

You can access it here

Being informed and keeping up with what is happening in the highly competitive race to quantum is crucial. We created this scan to help our users’ community keeping abreast of developments in the field.

You will find here all news (in English) related to quantum computing and simulation, quantum sensing and metrology, quantum communication, as well as quantum key distribution, quantum machine learning and post-quantum cryptography.

Find all our in-depth reports, brief and articles on the Quantum emerging world here. 

Time in Strategic Foresight and Risk Management

From the corporate world to governments, we seek to escape uncertainty and surprises. This is crucial to survive and thrive. It is also necessary for the protection from threats, dangers and risks.

As a whole and generally, our abilities – if not willingness – to identify threats has improved with experience and practice. Notably, we became relatively efficient in assessing likelihood and impact. Nonetheless, one component of threat and risk assessment remains most often unconsidered, unnoticed, and neglected: time.

Yet, time is a crucial component of our ability to prevent surprise, handle threats and manage risks. This article assesses how we integrate time and highlights room for improvements.

Continue reading “Time in Strategic Foresight and Risk Management”

Quantum Computing, Hollywood and geopolitics

Since 2017, quantum information and technology science (QIS), and especially quantum computing, are quickly emerging as central in Hollywood and its movies, TV series and novels. Their scenarii emphasise the link between quantum power and national security situations.

Hollywood and the U.S Strategic Debate

This is a crucial indication, considering that the relation between the U.S. cultural industries and National security has been one of the main drivers of the U.S. strategic debate since World War II (Jean-Michel Valantin, Hollywood, the Pentagon and Washington: The Movies and National Security from World War II to the Present Day, 2005).

That link organizes the structure of the U.S. strategic debate through the very complex and tangled relationships between the federal centres of political power in Washington D.C, the Department of Defence, the intelligence community and the media and cultural industry (Valantin, Ibid.). That is the reason why Hollywood movies, television and video games play a vital role in the U.S. strategic debate.

Continue reading “Quantum Computing, Hollywood and geopolitics”
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