As we expected previously, the U.S. decision regarding Jerusalem not only polarised the situation, but also ended up as a test for U.S. power and influence. The testing nature of the situation was reinforced by the Americans threatening to cut American aid to countries, should the latter not side with the U.S. during the U.N. General Assembly vote for a resolution that “’demanded’ that all countries comply with Security Council resolutions regarding the status of Jerusalem, following an earlier decision by the United States to recognize the Holy City as the capital of Israel” (UN News) – a resolution that thus opposed the U.S. decision regarding Jerusalem.
Despite the threat, the “resolution [was] adopted by a recorded vote of 128 in favour to nine against (Guatemala, Honduras, Israel, Marshall Islands, Federated States of Micronesia, Nauru, Palau, Togo, United States), with 35 abstentions” (UN News). The U.S. thus lost.
As a result, the power and influence of the U.S. seems likely to have decreased.
This was not lost on China, as it held a third symposium, “of Israeli and Palestinian peace advocates” on 21 and 22 December 2017 in Beijing, where China’s Foreign Minister Wang Yi was to “meet with the Palestinian and Israeli attendees” (Foreign Ministry Spokesperson Hua Chunying’s Regular Press Conference on December 21, 2017). The Foreign Ministry’s spokeperson futher added that “We are willing to continue offering constructive assistance to promote the Israeli-Palestinian peace process.” (Ibid.)
Meanwhile, the content of the articles on the matter in Global Times (the international edition for the very official People’s Daily), not only stressed the American loss of influence, but also underlined the ideal Chinese position to now step in as potential broker for future peace negotiations between Israelis and Palestinians.
It thus appears likely that China could step in to try replacing the U.S. as peace broker.
Should this happen, then China would have extended and asserted its influence, furthermore in a region where it had not been so far a major player – however being increasingly active there – while the U.S. would have, on the contrary, lost not only regional but also global influence.
Impact on Issues and Uncertainties
➘ U.S. influence and power in the Middle East ➘ Global U.S. influence and power
➚ Chinese influence and power in the Middle East ➚ Global Chinese influence and power
By an overwhelming majority, Member States in the United Nations General Assembly on Thursday “demanded” that all countries comply with Security Council resolutions regarding the status of Jerusalem.
Diplomats brushed aside what appeared to be a hastily organized pressure campaign by the White House, including last-minute threats by President Trump to cut off aid to countries voting for the resolution. “We will not be threatened,” Mr. Malki, one of several diplomats who spoke before the vote, told the General Assembly at an emergency meeting.
The symposium of Israeli and Palestinian peace advocates held in Beijing shows China’s will to promote peaceful solutions to Palestine-Israel issues, but experts say the complexity of Middle East politics leaves limited space for China.
An emergency UN General Assembly meeting passed a resolution calling for the US to drop its recognition of Jerusalem as Israel’s capital as well as its decision to move the US embassy there. A total of 128 countries backed the resolution, nine voted against and 35 abstained.
The capability to use Alice in English could be developed in the (near-)future (Anadiotis, Ibid.). This would open the whole Yandex world to English speakers. Meanwhile this would also allow Yandex to get access to all the data of these very English speakers, so far the preserve mainly of Google, Apple and Amazon. Considering the current tensions between the U.S. and, with variations, NATO members, on the one hand, Russia on the other, one may only too well imagine the political paranoia that might then develop. Meanwhile, international competition among internet giants for users’ data, crucial to part of Deep Learning, as we shall see when explaining what is Deep Learning below, will very likely be intensified. On a more positive side, better understanding may also emerge as a result of non-Russian people discovering the Russian world. Nonetheless, this would also impact perceptions and thus international relations.
The AI world, notably in its Deep Learning component, is already here. It impacts everything, even though the extent and depth of its impacts are still hardly perceptible. We must understand Deep Learning to be able to live within this new world in the making, rather than only reacting to it.
This article thus focuses on Deep Learning (DL), the sub-field of Artificial Intelligence (AI) that leads the current exponential development of the sector. As we seek to envision how a future AI-powered world will look and what it will mean to its actors, notably in terms of politics and geopolitics, it is indeed fundamental to first understand what is AI.
Previously, we presented AI, looking first at AI as a capability, then as a scientific field. Finally, we introduced the various types of AI capabilities that scientists seek to achieve and the ways in which they approach their research.
In this article, we shall first give examples of how Deep Learning is used in the real world. We distinguish two types of activities: classical AI-powered activities and totally new AI-activities, related to the very emergence of DL. In both cases we shall point out their revolutionary potential, impacting three major emerging functions within polities we had previously started identifying: AI management, AI governance and AI-power status, when AI is most likely to be, to the least, part of the relative power ranking for world actors (Helene Lavoix, “When Artificial Intelligence will Power Geopolitics – Presenting AI“, 29 November 2017, and Jean-Michel Valantin, “The Chinese Artificial Intelligence Revolution“, 13 November 2017, The Red (Team) Analysis Society).
Then, we shall take a deeper dive in the world of Deep Learning, taking as practical example the evolution of Google’s DeepMind AI-DL program initially developed to win against human Go masters: AlphaGo, then AlphaGo Zero and finally AlphaZero. After briefly presenting where DL is located within AI, we shall focus first on Deep Neural Networks and Supervised Learning. Second we shall look at the latest evolution with Deep Reinforcement Learning and start wondering if a new AI-DL paradigm, which could revolutionise the current dogma regarding the importance of Big Data, is not emerging.
Deep Learning in the real world, AI-governance and AI-power status
In a nutshell, Deep Learning (DL) is used to solve at best complex problems and functions and to take the best possible decisions regarding whatever question it is applied or to succeed in whatever field it is used.
For example, DL is increasingly used in the oil and gas industry. Southwest Research Institute (SwRI) developed the Smart LEak Detection (SLED) system, which “uses algorithms to process images from sensors scanning infrastructure” to “autonomously and accurately detect liquid hydrocarbon leaks and spills” (Maria S. Araujo and Daniel S. Davila, “Machine learning improves oil and gas monitoring“, 9 June 2017, Talking IoT in Energy). DNV GL has explored the use of DL (actually Microsoft Azur Machine Learning) to predict corrosion in pipelines and concluded that the “performance achieved” was “extremely promising” (Jo Øvstaas, “Big data and machine learning for prediction of corrosion in pipelines“, 12 Jun 2017, DNV GL). Had Italy and the UK benefited from such systems, both the “explosion at a major processing facility in Austria, which is the main point of entry for Russian gas into Europe”, and the “shutdown of the North Sea’s most important oil and gas pipeline system”, respectively on 11 and 12 December 2017, with major consequences for European supply (Jillian Ambrose and Gordon Rayner, “Gas shortage to push up bills after ‘perfect storm’ of energy problems“, 12 Dec 2017, The Telegraph), would most probably not have happened – assuming, of course, investments related to response had been done.
Further, DL is also increasingly part of the development of what is called “Smart Factory”. “In April 2017, PCITC and Huawei jointly announced a smart manufacturing platform… a core part of Smart Factory 2.0 within the Sinopec Group”. Notably, one of the capability of the platform “creates a ‘smart brain’ for petrochemical plants using deep learning and reasoning data.” (Huawei, “Huawei Joins Hands with PCITC to Embrace Smart Factory 2.0“, 13 Nov 2017, PRNewswire).
With NVDIA’s “Metropolis AI Smart Cities Platform”, Huawei’s video content management product supports and uses Deep Learning for “accurate face recognition, pedestrian-vehicle structuring and reverse image search”, also cooperating with the Shenzhen Police. Always with Metropolis, Alibaba Cloud’s City Brain uses AI for services such as “real-time traffic management and prediction, city services and smarter drainage systems”, improving for example “traffic congestion by as much as 11 percent in Hangzhou’s pilot district” (Saurabh Jain, “Alibaba, Huawei Adopt NVIDIA’s Metropolis AI Smart Cities Platform“, 25 Sept 2017, NVDIA blog).
Most famously, Deep Learning has been and is still used to play games such as go or chess, which allows for developing and testing new AI programs, in their architecture and algorithms. It is these programs, notably those developed by Google’s DeepMind, that we shall use below to further deepen our understanding of what is DL.
These may appear as classical cases of the way AI in its DL component may revolutionise already existing ways and practices.
For the very first time in human history, we could start thinking we could manage activities in near-perfect ways, as well as govern, in the multiple dimensions ruling demands, also in near-perfect ways. This, in itself, in a world of very imperfect humans is a revolution. It leads us to wonder about new issues such as how we, humans, with all our imperfections, with our multiple cognitive biases – i.e. mental errors which we are systematically doing but which were useful to survive and reach our current level of development (Richards J. Jr. Heuer,, Psychology of Intelligence Analysis, Center for the Study of Intelligence, Central Intelligence Agency, 1999) – are we to handle suddenly near-perfect activities? The very simple example of the self-driving car springs to mind immediately. The high number of crashes involving self-driving cars seems indeed to come from their inability to handle human imperfect driving (James Titcomb, “Driverless car involved in crash in first hour of first day“, 9 November 2017, The Telegraph).
However, new activities are also starting to appear, which are less classical to say the least. We have the case of learning platforms, where AI-DL agents learn and train (Cade Metz, “In OpenAI’s Universe, Computers Learn to Use Apps Like Humans Do“, 12 May 2016, Wired). For example, Universe, developed by OpenAI (the AI Lab backed by Tesla CEO Elon Musk) is a software platform where scientists can train their AI to interact with applications and programs, many of them open source (Ibid).
DeepMind Lab is a similar platform offered by Google’s DeepMind (Ibid). The older ImageNet, created in 2009, helped AI agents to learn to “see” (Ibid.). Is this the birth of a truly new AI-activity, similar to education, and which is to be part of the emerging AI-governance?
How will these two types of activities, classical AI-powered activities and new AI-activities, be integrated within AI-management and, in the area of politics that primarily concerns us, AI-governance? How are AI-management and AI-governance be organised? How will AI-governance interact with older remaining state, regime and government structures and processes?
Further, how will be organised a world that has been so far dominated by the quest for relative competitive advantage? Is the notion of competitive advantage even still relevant? What will happen when so far competing actors, from states to companies, are each using AI-DL in such a way that management and governance are all near-perfect? The first phase will most probably be a race to obtain this AI-DL advantage, while trying possibly to deprive others. But what will happen when two or more actors reach the same AI-stage of development? As the example give in introduction points out, shall will also see competition regarding who can access to citizens’ data rise?
This is nothing less than a completely new world that is possibly being created.
We shall, however, also have to wonder if and how such developments could fail.
We shall now take a deeper dive in the world of Deep Learning, which will allow us then, throughout the series, to better understand which activities are susceptible to be impacted by AI-DL, to start envisioning which new AI-activities could be born, as well as to map out how the likely race for AI-power status could take place and around which elements.
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Silver, David Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel & Demis Hassabis, “Mastering the game of Go without human knowledge“, Nature550, 354–359, 19 October 2017, doi:10.1038/nature24270
Silver, David Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, Sander Dieleman, Dominik Grewe, John Nham, Nal Kalchbrenner, Ilya Sutskever, Timothy Lillicrap, Madeleine Leach, Koray Kavukcuoglu, Thore Graepel & Demis Hassabis, “Mastering the game of Go with deep neural networks and tree search” Nature 529, 484–489, 28 January 2016, doi:10.1038/nature16961.
Resulting from the Google AI China Center’s opening and then operations, we estimate rising likelihoods to see :
Redrawing of the power map of the world along AI-power status lines
Rising competition regarding AI between U.S. and Chinese mammoth Companies
Human talents as stake in rising AI competition
“Forced” introduction of “open source” AI work in China
AI further progress and developments
Rising U.S. ability to stem the declining tide in terms of AI
Rising China’s influence in terms of AI
Rising China’s strength and capability to further develop AI
Strengthening capability of Chinese government and State to “keep in check” mammoth IT companies
Strengthening of Chinese political authorities
Increased China’s influence
China’s rise to top major power status
US decline from sole superpower to major power status (in relative terms, the U.S. capability to stem decline out of this specific signal does not compensate for the corresponding Chinese gains)
Escalating Tension U.S. – China
(The corresponding symbolic board is located after the “facts and analysis section)
Facts and analysis
On 13 December 2017 during the 13 and 14 December Google Developer Days event in Shanghai, Fei-Fei Li Chief Scientist AI/ML *Artificial Intelligence/Machine Learning), Google Cloud announced the creation of the Google AI China Center, their “first such center in Asia”. the center will focus on basic AI research, and is located in Beijing to attract as many talents as possible.
It follows logically from Eric Schmidt, Executive Chairman, Alphabet Inc. (Google) and Chair, Defense Innovation Board’s perception and assessment we singled out in a previous signal, according to which
“These Chinese people are good… It’s pretty simple. By 2020, they will have caught up; by 2025, they will be better than us; and by 2030, they will dominate the industries of AI.” (Eric Schmidt, Artificial Intelligence and Global Security Summit, CNAS, 1 Nov 2017)
As a result Google is positioning itself to be present on a market that they see as being dominant in the future. In the meantime, by attracting these Chinese AI talents, they also potentially slow the AI development of their Chinese competitors, which are Alibaba, Huawei, TenCent or Baidu.
As underlined by the Chinese official viewpoint, such a competition may only be healthy and stimulating and promote innovation at Chinese level, notably in a field that is so close to the heart of China, which aims at becoming leader in AI. The Google AI Center shows the attractiveness of China, and will help China attracting notably Asian talents to China, de facto favouring China’s goals.
Finally, Google is certainly an interesting actor for the Chinese government as it is allowed on the Chinese-Global AI board, in as much as it can be also possibly used to check the mammoth power garnered by the IT Chinese giants. For example, according to a Huawei Director there is a Chinese lag in “developing open-source software”. Assuming that this position is shared by the Chinese political authorities, allowing Google to enter the AI competition in China is likely to be a perfect way to force Chinese companies towards more open-source efforts (yet of course without overestimating Google open efforts, as we are dealing here with for profit companies).
The Chinese government and state thus ensures it strengthens its hand in remaining master of China’s destiny.
Impact on Issues and Uncertainties
? How threatening would a leadership of China in terms of artificial intelligence (AI) be perceived? What would mean escalating tensions between China and the U.S. involving AI and how would they play out? Are mammoth U.S. companies first global or American? (Critical uncertainties)
➚➚ Redrawing of the power map of the world along AI-power status lines
➚ Rising competition regarding AI between U.S. and Chinese mammoth companies ➚ Human talents as stake in rising AI competition
➚ “Forced” introduction of “open source” AI work in China ➚ AI further progress and developments
➚ U.S. ability to stem the declining tide in terms of AI ➚ China’s influence in terms of AI ➚ China’s strength and capability to further develop AI
➚ Capability of Chinese government and State to “keep in check” mammoth IT companies ➚ Strengthening of Chinese political authorities
➚ China influence ➚ China rise to top major power status ➙➚ US decline from sole superpower to major power status
Since becoming a professor 12 years ago and joining Google a year ago, I’ve had the good fortune to work with many talented Chinese engineers, researchers and technologists. China is home to many of the world’s top experts in artificial intelligence (AI) and machine learning.
Google announced Wednesday that it is opening an artificial intelligence (AI) research center in Beijing. This may serve as a springboard for China to attract top-ranking talent from around the world.
China has entered a “new era” where it should “take centre stage in the world” said President Xi Jinping during his opening speech at the 19th National Congress of the Communist Party of China (18-24 October) (Xi Jinping: “Time for China to take centre stage”, BBC News, 18 October 2017). This is poised to have formidable effects on the global economy as well as on the international currency system. Furthermore, to see this happening, we may wonder if the Chinese currency needs not becoming supreme in the international currency system. What is thus the current international state of play for the renminbi and which factors could preside to its future international reign?
Executive Summary
This article focuses on assessing the possibility to see China’s Yuan rivalling or replacing the U.S. dollar as the world’s reserve currency, with all the consequent benefits.
As far as the current position of the “redback” is concerned, our analysis shows an increased internationalization as, for example, the Renminbi has been included in the basket of currencies on which the values of the IMF-issued Special Drawing Rights is based. The U.S. dollar, however, is still much more used in foreign-exchange trading and as a store of value at the official level. The greenback, all things being equal, is therefore likely to retain a dominant position in the foreseeable future.
However, keeping in mind that events rarely remain equal and follow expected trends, as first elements towards detailed scenario analysis for the future, we then analyse certain components of the Chinese economy that could help the renminbi in rivalling the international stance of the U.S. dollar. China’s extensive internal market and Beijing’s commercial depth are likely to help the renminbi in strengthening its position on global markets, while China’s financial markets still seem underdeveloped. This is why China’s economic authorities have announced that they will undertake dramatic reforms. Nonetheless, the facts that the judicial system is still controlled by the Communist Party and that the yuan is not fully convertible could hinder the possibilities for the renminbi to rival the dollar, at least in the short-term.
As a conclusion, the reform of the financial markets will be crucial to establish a truly global currency that could have the possibility to be on a par with the U.S. dollar, the two coexisting at the top of the currencies’ ladder. Other events, however, deserve further consideration for a fully detailed and final estimate.
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About the author: Leonardo Frisani (MA Paris) focuses currently on challenges to the US Dollar supremacy. Beyond that, his specialisation is in international security, and his main interests are in geopolitics, macroeconomics, climate change, international energy and history.
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On 9 December 2017, Libya’s Government of National Accord and Italy agreed to launch an operations center for combatting the migrant smuggling networks that facilitate the migrant flow across the Mediterranean. According to GNA Prime Minister Serraj, the operations center will include “representatives from the coastguard, the illegal migration department, the Libyan attorney general and the intelligence services, along with their Italian counterparts.”
With no details provided on how this center will operate, as well as seeing the GNA’s limited influence over militias, the effectiveness of this joint operations center and its impact on Libya’s spillover remains to be seen. Over the coming months, the center’s activities and any measurable effects will need to be monitored.
Impact on Issues
Critical uncertainty: capability to truly operationalise with efficiency the center on the shorter term
TRIPOLI (Reuters) – Libya’s U.N.-backed government agreed with Italy on Saturday to establish a joint operations room for tackling migrant smugglers and traffickers as part of efforts to curb migrant flows toward Europe, according to a statement.
On 6 December 2017, U.S. President Donald Trump declared that the U.S. recognises Jerusalem as the capital of Israel and, as a result will move its embassy there (see sources below), while also reasserting commitment to the peace process and specifying that the U.S. would support a two-state solution, if approved by both the Israelis and the Palestinians. Despite stress on peace, this declaration is highly likely to add fuel to the fire in the Middle East.
The U.S. itself is well aware of this danger as the State Department has asked “staff to defer all but essential travel to Israel, Jerusalem and the West Bank until 20 December”, according to Reuters.
It is highly likely that the fragile equilibrium that was very slowly being rebuilt despite, for example, the Hariri crisis, where most actors showed restraints, and despite the remaining difficulties related to working towards a constructive peace in Syria will be shattered.
Indeed, with this move, the U.S. forces all actors to take strong stances, which they cannot not take, but which are most probably not in the interest of a more peaceful region. These stances will also make subtle diplomatic negotiations and convergence of interests, such as those for example that developed between Saudi Arabia and Israel more difficult (see e.g. Signals: China enters the Fray in the Middle East; Israel Unprecedented Interview; Saudi Arabia…).
As a result, tension has further escalated in the Middle East. Meanwhile, Israel’s position could become not more but less secure.
Considering the discussions which preceded the American President’s declaration, where most Western and Arab allies warned America against this move, a position confirmed by the first international reactions to the American declaration, we may wonder in which way the new configuration now created serves, or, on the contrary, deserves, American power and influence. The U.S. could increasingly be seen as still powerful indeed, however a power that must be contained because also ready to sow turmoil by not considering all consequences.
The coming chains of actions reactions thus triggered will need to be closely watched.
Impact on Issues and Uncertainties
? Actions, notably of Muslim actors, beyond statements (critical uncertainties)
➚ ➃Middle East Tension ➙➚ Threat to Israel ➚ ? Test to U.S. influence and power
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.@POTUS: I have determined that it is time to officially recognize Jerusalem as the capital of Israel. I’ve judged this course of action to be in the best interest in the United States of America and the pursuit of peace between Israel and Palestinians. pic.twitter.com/X2eogVU4M0
WASHINGTON – The US State Department issued a cable to all its diplomatic posts worldwide on Wednesday asking its officials to defer non-essential travel to Israel, Jerusalem and the West Bank until Dec. 20 according to a copy of the cable seen by Reuters.
.
I share @POTUS Trump's commitment to advancing peace between Israel and all of our neighbors, including the Palestinians.
This has been our goal from Israel's first day.
And we will continue to work with the President and his team to make that dream of peace come true.
CAIRO/AMMAN/BEIRUT (Reuters) – Arabs denounced President Donald Trump’s plan to move the U.S. embassy in Israel to Jerusalem as a slap in the face but few thought their governments would do much in response.
Palestinian factions in the West Bank announced on Tuesday that they would carry out three days of protest across the West Bank over U.S. President Donald Trump’s expected decision regarding American policy on Jerusalem.
ANKARA A potential U.S. move to recognize Jerusalem as Israel’s capital may cause indignation in the Islamic world and lead to new clashes in the region, President Recep Tayyip Erdoğan said on Dec. 6. “Any such false step may cause indignation in the Islamic world, dynamiting the ground for peace and igniting new tensions and clashes,” Erdoğan said on Dec.
President Donald Trump on Wednesday will recognise Jerusalem as Israel’s capital and set in motion the relocation of the U.S. Embassy to the ancient city, senior U.S. officials said, a decision that upends decades of U.S. policy and risks fueling violence in the Middle East.
On 15 May 2017, at the opening of the Belt and Road (B&R) Forum for International Cooperation, the Chinese President Xi Jinping declared:
“We should pursue innovation-driven development and intensify cooperation in frontier areas such as digital economy, artificial intelligence (AI), nanotechnology and quantum computing, and advance the development of big data, cloud computing and smart cities so as to turn them into a digital silk road of the 21st century. It is not just about physical connectivity but also digital connectivity. Internet of Things connectivity will be an integral part of the initiative. (“Full text of President Xi’s speech at opening of Belt and Road forum”, Xinhua net, 14/05/2017).
Five months later, on 17 October 2017, President Xi Jinping, during his speech given in front of the participants to the 19th congress of the Chinese Communist Party, also said:
“Deepen supply-side structural reform. […] Accelerate the development of advanced manufacturing sectors, promote the profound convergence of the Internet, big data, artificial intelligence and the real economy, foster new growth points and create new drivers in areas such as mid- and high-end consumption, innovative leadership, greenness and low-carbon, the sharing economy, modern supply chains, human capital services and other such areas. […] Strengthen the construction of basic infrastructure networks for irrigation, railways, roads, waterways, aviation, pipelines, the electricity grid, information, logistics, … » ” (“What did Xi Jinping say about cyberspace ?”, China Copyright and Media, October 17, 2017).
In other words, the highest levels of the Chinese government are currently coupling the development of the AI revolution with the deployment of the Belt and Road (B&R) initiative (or New Silk Road, a.k.a, previously the “One Belt, One Road” initiative). This grand strategy, launched in 2013, aims at creating a land and maritime international transport, trade, and finance Chinese infrastructure, which spans Asia, Russia, Europe, the Middle East, Africa and Latin America. Its aim is to find international reserves for the resources and products necessary to the development and enrichment of China (Jean-Michel Valantin, “China and the New Silk Road – From oil wells to the moon … and beyond”, The Red (Team) Analysis Society, July 6 2015). This endeavour is deployed on such a scale that it becomes a new political, economic and strategic force in the globalised world, for the Chinese national interest.
This coupling of the Belt&Road with the development of cyberspace and of artificial intelligence was furthered on 2 and 3 December 2017, during the Fourth World Internet Conference in Wuzhen. Then, remarks from the congratulatory letter by President Xi Jinping stated the necessity to build “a common future in the cyberspace”. On the margin of the conference, China, along with Asian, Middle Eastern and European countries – namely Serbia, Saudi Arabia, the United Arab Emirates, Laos, Thailand, and Turkey – launched the “Digital Belt and Road”. The conference was also attended by Huawei, Beidou and Tencent, the Chinese Telecom and artificial intelligence and supercomputer giants, as well as by U.S. Apple and Tesla (Chen Qingqing, “Consensus grows at internet conference“, Global Times, 2017/12/3,).
In this article, we shall study how the spread of the B&R integrates the deployment of the “sinosphere” through the increasing use of AI as a tool to reinforce the efficiency of the international transport, information and communication infrastructures that actually shape the New Silk Road/B&R. Reciprocally, this will allow us to understand how the B&R is supporting the development of AI and how this dynamic is fostering the political influence of China. Then, we shall focus upon the political meaning of this coupling of the B&R grand strategy with the AI development.
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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: By Geralt, Pixabay, Public Domain.
Nato has released its latest 2017 Strategic Foresight Analysis Report.
According to General Denis Mercier, NATO Supreme Allied Commander Transformation (SACT) interviewed by Reuters, the report will be used with a SACT “companion report that maps out what NATO should do to respond to these trends in the spring” … “to inform the 2019 NATO political guidance”.
Some of the main points identified for the future are:
Increased instability
Increased likelihood of confrontation and war
Rising challenge to NATO and the West from emerging and resurgent powers (aka Russia and China)
Asymmetric demographic change
Rapid urbanization
Increasingly polarized societies
Continuous if not rising importance of new and emerging technologies, which offer enormous opportunities but also challenges and vulnerabilities
The impact of globalization
Rising importance of climate change and related cross cutting impacts, water security, food security and resource competition
BERLIN (Reuters) – China’s growing military strength and a resurgent Russia will pose growing challenges to the trans-Atlantic alliance in coming years, and NATO’s moves to bolster its capabilities could trigger a new Cold War-style arms race, a NATO report said.
“Killer Robots” worry the international community. From 13 to 17 November 2017, the Group of Governmental Experts on Lethal Autonomous Weapons Systems (LAWS), also familiarly designed as “killer robots” met for the first time in Geneva (UN Office at Geneva). LAWS are, broadly speaking, autonomous systems (robots) animated by artificial intelligence, which can kill without human decision. As stated in a preliminary paper, the creation of the Group shows an international concern “with the implications for warfare of a new suite of technologies including artificial intelligence and deep machine learning” (UNODA Occasional Papers No. 30, “Perspectives on Lethal Autonomous Weapon Systems” November 2017: 1).
Are we, however, certain that AI will impact only LAWS? Or, rather, could AI impact much more than that, indeed, everything related to politics and geopolitics?
Executive Summary
To introduce this section of the Red Team Analysis Society on the future, AI, politics and geopolitics, we start with giving instances of domains and human activities currently already involving AI. We then point out some of the related political and geopolitical questions emerging, which we shall address with forthcoming in-depth analysis. As understanding what is AI is a pre-requisite, this article focuses on presenting the AI field, while the next one will be devoted to Deep Learning.
Here, we look first at AI as a capability. We revise the technical definition to introduce agency, which enables us to point out intrinsic fears generated by AI. We use videos to illustrate them. We also thus identify a first area of intersection between AI development and politics, related to “AI governance.”
We then explain that AI is also a scientific field. This approach will notably allow us finding those scientists and labs working on AI, thus monitoring which advances and evolutions are taking place, and sometimes anticipating breakthrough.
Finally, at the intersection of both, capability and scientific field, we present the various types of AI capabilities that scientists seek to achieve and the ways in which they approach their research. This is crucial to understand where we stand, what to expect and identify emerging political and geopolitical issues. We explain first the difference between Artificial General Intelligence (AGI) and Narrow AI, focusing more on the first as the latest advances in terms of Narrow AI, i.e. Deep Learning, will be addressed with the next article. Here again we use videos, this time from the science fiction world, to illustrate what is AGI and some of the related issues imagined for a world where AGI exists. Synthesising existing experts polls, the time estimate for the happenstance of AGI is the middle of the century. We close with a brief presentation of the types of methodology used, Symbolic AI, Emergentist AI and Hybrid AI, stressing the dominance of the current Emergentist approach.
FULL ARTICLE 3065 WORDS – APPROX. 12 PAGES
Artificial Intelligence (AI) has become a buzz word and trendy topic throughout the world, generating media attention, heated debates among IT tycoons as well as scientists, and a corporate rush to be equipped with the latest AI advances, while capturing popular imagination through TV shows. Worldwide conference and summits on AI abound: e.g. Beijing AI World 2017世界人工智能大会 (8 November 2017), Beijing Baidu World Technology Conference “Bring AI to Life” (16 November 2017), Boston AI world conference and expo (11-13 December 2017), Toronto AI World Forum (27 – 28 November 2017), London AI Congress (30-31 January 2018), the AI Summit series, in Hong Kong (26 July 2017), Singapore (3-4 October 2017), London (13-14 June 2018), New York (5-6 December 2017), San Francisco (18-20 September 2018).
If the revolution is so deep and large in scope, then it is bound to have an impact that goes even further than the pertinent but still segmented understanding of its consequences, which starts to be developing. In this new section of the Red (Team) Analysis Society, we shall focus about the futures of this AI-powered world and what it means in terms of politics and geopolitics.
Let us imagine that the highly likely forthcoming leadership of China in terms of artificial intelligence (AI) starts being perceived as threatening by an America that feels it is declining and ought to remain the sole superpower (Helene Lavoix, “Signals: China World Domination in Supercomputers and Towards Lead in Artificial Intelligence“,The Red (Team) Analysis Society, 14 Nov 2017). What would mean escalating tensions between China and the U.S. involving AI and how would they play out? How would differently “trained” AIs interact – if at all – in case of conflict?
Which are thus the emerging risks, dangers and opportunities, as well as crucial uncertainties resulting from AI-powered power struggles, politics and geopolitics? Could new completely unforeseen and so far unknown dangers emerge, beyond the LAWS? Is there an element of truth in Science Fiction’s warnings? How could the future world look like? Could the international order be fundamentally redrawn between AI Haves and Have-nots? What is power in a world where AI is increasingly present?
These are some of the questions we shall explore, while others, more precise, will emerge with our research.
To start, we need first to understand and define better what is AI and what are the conditions for its progress and development. This will give us the fundamental basis for this section, as well as the capacity to monitor and scan the horizon for evolutions and break through. One of the objectives will also be to avoid surprise, as the current emphasis on the success of one type of AI – deep learning – should not make us become blind to potential progresses in other subfields.
This first article thus presents the AI field and therefore begins identifying areas where the AI intersects with politics and geopolitics. The next article will dig deeper into Deep Learning, i.e. the AI sub-field that knows since 2015 the fastest and most wide-ranging developments and that is highly likely to impact the future political and geopolitical world.
Here, presenting the AI field, and using videos as much as possible to make the presentation more real, we look first at AI as a capability. We revise the technical definition to introduce agency, which enables us to point out intrinsic fears generated by AI. We also thus identify a first area of intersection between AI development and politics, related to “AI governance.” We then explain that AI is also a scientific field. and why this approach is useful to our strategic foresight. Finally, at the intersection of both, capability and scientific field, we present the various types of AI capabilities that scientists seek to achieve and the ways in which they approach their research.
AI as a capability
The Encyclopaedia Britannica defines AI, technically, as follows:
“Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” (B.J. Copeland, “Artificial Intelligence (AI)“, updated Jan 12, 2017).
Building upon this definition, we shall add agency and dynamics to it and reach the following definition:
Artificial intelligence (AI) is first a capability with which an initially inanimate object is endowed, at the start out of human being design, and that makes it partly or totally behave as an intelligent being.
The way we define here AI points out two fundamental characteristics that frighten human beings and that we would have missed, had we stopped at the initial technical definition.
First, human beings, when constructing AI, fundamentally, behave as God(s) or change nature’s design (according to one’s belief-system and religion) by making an object animated, which behaves (more or less) as themselves, or as an intelligent natural being. In this framework, by so doing, human beings thus perpetrate a sacrilege. They break a taboo, which thus may only lead to their punishment. From this deep belief an unreasoned fear emerges.
Second, as the new entities thus created can fundamentally behave as intelligent beings, then they will also be able to act autonomously – to a point – and even to reproduce. Engrained here is the fear of one’s creation turning against oneself, or in a less tragic way becoming better than oneself, which nonetheless ego-centred and anthropocentric societies may have trouble accepting.
Relatedly, when the new entities endowed with AI are animal-like, then ancient atavistic and once forgotten fears linked to predators may emerge, all the more so if you image these robots equipped with various types of lethal device. This can be illustrated by this video from Google’s Boston Dynamics lab demonstrating “Spot” capabilities.
These very deep fears are crucial and must be considered as they are highly likely to bias any analysis carried out and judgement passed on AI. They must be neither denied, for example by an overemphasis on a rosy all positive image that would be given to AI nor, on the contrary, hyped. As for everything both positive and negative elements must be considered to, as much as possible try to benefit from the advantages while mitigating possible dangers. Failure to do so could only backfire. We must also keep theses deep fears in mind because they may well become operative in informing actor’s behaviour in the future, as AI is likely to spread.
For example, making AI palatable to citizens and overcoming fears may become part of “governance with AI”. China, which is pushing forward to become a leading if not the leading power in AI, as well as to use AI across all domains (Lavoix, “Signals: China World Domination…”; Jean-Michel Valantin, “The Chinese Artificial Intelligence Revolution”, 13 Nov 2017, The Red (Team) Analysis Society), made a special effort to explain AI to its population with a 10-episode documentary “In Search of Artificial Intelligence” – 《探寻人工智能》- (Sun Media Group, broadcast May 2017) aimed at laypeople and stressing how AI can help solve problems, while also interviewing scientists worldwide. Watch the first episode below, 《探寻人工智能》第1集 机器的逆袭 , Machine counter-attack (mix Mandarin and English).
The stakes may even be bigger if, from a relatively simple “allaying fears”, one moves to mobilising a whole society for AI, as seems to be the case in China. Indeed, as reported by the official Beijing Review, “It [the documentary] is not only appealing to scientists and amateurs, but also motivates society to explore AI,” said a netizen with the user ID Jiuwuhou Xiaoqing.” (Li Fangfang, “Man and The Machine“, Beijing Review, NO. 25 JUNE 22, 2017).
AI as a scientific field
AI is also a scientific field, which is defined as follows:
“Artificial Intelligence (AI) is the part of computer science concerned with designing intelligent computer systems, that is, systems that exhibit characteristics we associate with intelligence in human behaviour – understanding language, learning, reasoning, solving problems, and so on.” (Barr & Feigenbaum, The Handbook of Artificial Intelligence, Stanford, Calif.: HeurisTech Press; Los Altos, Calif. : William Kaufmann, 1981: 3).
Thinking about AI in these terms will allow us finding those scientists and labs working on AI, thus monitoring which advances and evolutions are taking place, and sometimes anticipating breakthrough.
Further, by looking at the various sub-disciplines constituting the AI field, we shall be able to locate where we shall find AI (as a capability this time) components, thus which areas of polities are likely to be transformed by AI, knowing that combinations of AI-powered elements will often be operative.
According to a JASON (independent group of elite scientists advising the U.S. government) study sponsored by the Assistant Secretary of Defense for Research and Engineering (ASD R&E) within the Office of the Secretary of Defense (OSD), Department of Defense (DoD) (“Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoD“; January 2017), the sub-disciplines of AI are:
Computer Vision;
Natural Language Processing (NLP);
Robotics (including Human-Robot Interactions);
Search and Planning;
Multi-agent Systems;
Social Media Analysis (including Crowdsourcing);
Knowledge Representation and Reasoning (KRR)
Machine Learning “enjoys a special relationship with AI”, and is seen as the foundational basis for the latest advances in AI.
The type of AI capability(ies) with which our inanimate object is endowed, as well as which objects are concerned vary according to the AI sub-discipline or rather sub-disciplines, as most of the time different types of sub-disciplines and related AIs are mixed for one object.
If we remain in the sub-field of robots, we can see in the video below an array of animal-robots powered with AI, which could be used for a wide array of tasks, from the most benign to lethal applications, should they be equipped with lethal device. Note that for the fascinating video (watch on Youtube) by Techzone, the cover image – although then no robot-horse is presented – plays on the intrinsic fears of watchers by choosing a black horse with red eyes. The latter may only remind watchers of the Nazgul Steed in Tolkien Lord of the Rings, as adapted for the cinema by Peter Jackson.
Types of AI capabilities and research
Artificial General Intelligence (AGI) versus Narrow AI
The field is first divided between two types of capabilities that are sought to be achieved by scientific research: Artificial General Intelligence (AGI), General AI, or Strong AI on the one hand, Narrow AI, Applied AI or Weak AI on the other.
Artificial General Intelligence (AGI)
JASON gives for Strong AI the following definition:
“Artificial General Intelligence (AGI) is a research area within AI, small as measured by numbers of researchers or total funding, that seeks to build machines that can successfully perform any task that a human might do”. (Perspectives…, January 2017)
AGI is part of the Knowledge Representation and Reasoning subfield, according to JASON (p.5).
It is that type of AI which has most captured human imagination and which gives rise to the worst fears. It is best exemplified in the (excellent, fascinating and multiple-awards winner) TV series Westworld (HBO), co-created by Jonathan Nolan and Lisa Joy,where robots are all but indistinguishable from human beings.
Similar AI-related themes, although there without embodiment were somehow prefigured in the 5 seasons strong TV series Person of Interest (CBS), also created by Jonathan Nolan, with the war between “The Machine” and “Samaritan”.
We also recall a similar theme developed in the older series of films and TV series, Terminator (1984), with a world taken over by AI-powered computer system “Skynet”, which had decided to eradicate humanity. More recently (2015), Avengers: Age of Ultron used a similar narrative: the AI peacekeeping program, “Ultron” came to believe it had to destroy humanity to save the Earth. Ultron not only took over robots but also created its own avatar. In Terminator as in Ultron the embodiments come second and are the result and creation of the initially unembodied AI. We are here in the even more frightening case where the AI “reproduces” itself and creates new entities.
It is interesting to note that the Statement of Work from DoD/OSD/ASD (R&E) for JASON’s study includes specific questions regarding the development of Strong AI or AGI, and that the objective of the study was to find out what was missing from AGI to see the field achieving its promise (Appendix A p 57). This points out that, by early 2017, the U.S. DoD had far from given up in developing AGI and, on the contrary, could have been thinking about strengthening its efforts in the area. Yet JASON’s recommendations are as follows: “DoD’s portfolio in AGI should be modest and recognize that it is not currently a rapidly advancing area of AI. The field of human augmentation via AI is much more promising and deserves significant DoD support” (p.56).
When?
In a 2010 survey, and 2014 poll, AGI researchers estimated that “human-level AGI was likely to arise before 2050, and some were much more optimistic” and that “AGI systems will likely reach overall human ability (defined as “ability to carry out most human professions at least as well as a typical human”) around the middle of the 21st century” (Ben Goertzel, 2015, Scholarpedia, 10(11):31847, using Baum et al, 2011 and ).
In a way that is not contradictory with the previous estimates, but sounds more negative because the period of studies stops in 2030, a 2015 panel at Stanford University working on the programme One Hundred Year Study on Artificial Intelligence (AI100) estimated that
“Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind. No machines with self-sustaining long-term goals and intent have been developed, nor are they likely to be developed in the near future [2030]…”(Report of the 2015 Study Panel, “Artificial Intelligence and Life in 2030”, June 2016: 4).
Narrow AI, Applied AI or Weak AI
On the opposite side of the spectrum, one finds Narrow AI, Applied AI or Weak AI, which focuses “on the pursuit of discrete capabilities or specific practical tasks” (Goertzel 2015; Goertzel and Pennachin, 2005). In other terms, the aims is to “perform specific tasks as well as well as, or better than, we humans can (Michael Copeland, “What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?“, NVDIA, 29 July 2016). Face recognition on Facebook, Google or in various Apple programmes is an example of Narrow AI. Apple Iphone Siri is another instance of narrow AI.
This approach now largely dominates the AI field (Goertzel 2015). Indeed, opposing it to AGI, the AI100 continues:
“Instead, increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030, the period this report considers.” (Artificial Intelligence and Life in 2030”, Ibid.)
It is here that one finds Deep Learning, which is now leading the current phase of AI’s exponential development, and upon which we shall focus in the next article.
Symbolic AI, Emergentist AI and Hybrid AI
Then, the field is also divided according the type of methodology used to achieve results.
The top-down approach, also called symbolic approach, was the main method used until the end of the 1980s. It seeks to apprehend cognition in a way that is independent from the organic structure of the brain and is still used (Copeland, 2017). Its main achievements have been expert systems (Ibid.). The most recent work focuses on developing “sophisticated cognitive architectures”, using notably “working memory” drawing on “long-term memory” (Goertzel, 2015).
The bottom-up or connectionist or also emergentist approach was used in the 1950s and 1960s, then fell into neglect before becoming important again in the 1980s (Copeland, 2017; Goertzel, 2015). It is now mainly focused on creating neural networks and is the methodology that brought the latest advances and boom in AI.
Deep Learning, for example, is composed notably of “multilayer networks of formal neurons”, as we shall see in the next article. Developmental robotics also uses the emergentist approach. Here one tries to control robots through allowing them “to learn (and learn how to learn etc.) via their engagement with the world” (Goertzel, 2015). Notably, “intrinsic motivation” is explored, i.e. robots learn to develop “internal goals like novelty or curiosity, forming a model of the world as it goes along, based on the modeling requirements implied by its goals” (Ibid.). “Juergen Schmidhuber’s work in the 1990s” is considered as foundational in this area (Goertzel, 2015 refering to Schmidhuber, 1991).
Work on hybrid systems, mixing the two approaches started emerging in the first decade of the 21st century, including for AGI (Goertzel, 2015).
With the next article, we shall focus on the “deep learning” revolution, exploring its components and starting looking at its applications and uses.
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Featured image: Titan, a hybrid-architecture Cray XK7 system with a theoretical peak performance exceeding 27,000 trillion calculations per second (27 petaflops). It contains both advanced 16-core AMD Opteron central processing units (CPUs) and NVIDIA Kepler graphics processing units (GPUs). It is installed at the Department of Energy’s (DOE) Oak Ridge National Laboratory, and still the largest system in the US, but slips down to number five in the Top500 for November 2017. From Oak Ridge National Laboratory media gallery, Public Domain, recolourized.
Impacts and ConsequencesIf Russia succeeds in gathering major actors in a congress in Sochi, which we estimate as likely (55% to 70%)Increased likelihood to see, at the end of the process, a constructive peace settling in Syria Increased likelihood to see the birth of a Federal Syria Increased likelihood to see the survival of the Kurdish-led Federation of Northern Syria Increased likelihood to see a serious lowering of tensions in the Middle East and even some kind of stabilisation Increased Russian influence(Nota: The symbolic board has been moved to the end of the analysis and before the sources/signals)Facts and analysisAs stated by Russian President Putin, the overarching goal is now, for Syria, “the political settlement process, with the finalization of the …
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connectivity will be an integral part of the initiative. (“
