The unrest in the Arab world, which has continued for over a year now, implies one important conclusion beyond any ongoing regional struggle for democracy: It is a reflection on the globally important technological, even more about a crucial geopolitical breakthrough – an escape from the logics of the hydrocarbon status quo, which – after Copenhagen 2009 and Durban 2011 – will fail again in Rio (Earth Summit 2012/Rio+20) later this year.
“No one governs innocently” – de Beauvoir noted in her 1947’s The Ethics of Ambiguity. After a lot of hot air, the disillusioning epilogue of the popular McFB revolt is more firearms and less confidence residing in the Middle East and North Africa (MENA) region, as well as a higher (moral and environmental, socio–economic and political, psychological and security) carbon-energy price everywhere else. As if the confrontational nostalgia, perpetuated by intense competition over finite resources, in lieu of a real, far-reaching policy-making has prevailed again. Caught in the middle of its indigenous incapability and the global blind obedience to fossil carbon addiction, and yet enveloped in just another trauma, the Arab world and the wider Middle East theatre remains a hostage of a geopolitical and geo-economic chess-board mega drama. However, all that appears over-determined now was not necessarily pre-determined in the beginning.
A Grand Dilemma and the MENA
The MENA theatre is situated in one of the most fascinating locations of the world. It actually represents the only existing land corridor that connects 3 continents. Contributing some 6% to the total world population, its demographic weight is almost equal to that of the US (4,5%) and Russia (1,5%) combined. While the US and Russia are single countries, the MENA composite is a puzzle of several dozens of fragile pieces where religious, political, ideological, history-cultural, economic, social and territorial cleavages are entrenched, deep, wide and long. However, the MENA territory covers only 3% of the Earth’s land surface (in contrast to the US’ 6,5%, coverage and Russia’s 11,5%). Thus, with its high population density and strong demographic growth, this very young median population (on average 23–27 years old) dominated by juvenile, mainly unemployed or underemployed, but socially mobilized and often politically radicalized (angry) males, competes over finite and scarce resources, be they arable or settlers land, water and other essentials.
Competition in this theatre, that has a lasting history of external domination or interference, is severe, multiple, unpredictable, and therefore it is fluid and unsettled on the existing or alternative socio-economic, ideological, cultural and politico-military models, access, directions and participatory base.
Interestingly enough the recent crisis, pejoratively nicknamed the Facebook Revolution has so far ‘knocked down’ only MENA republics (declaratively egalitarian and secular regimes of formal democracy). For the time being, it has spared the Arab peninsular absolutistic monarchies (highly oppressive theocratic regimes of real autocracy). The modern-day version of Metternich’s Alliance of the Eastern Conservative Courts – the Gulf Cooperation Council (GCC) club has so far gained considerably from the calamities: (i) strategically – more durable regimes and ideologies, translated into their political and diplomatic offensive; (ii) institutionally – besides dominating the Organization of the Petroleum Exporting Counties (OPEC), the GCC theocracies now practically control the League of Arab States (LAS), sets its agenda, political direction and punitive actions; and (iii) geo-economically – huge petro-dollar revenues: enlarged quotas caused by the delivery disruptions and embargoes in Libya and elsewhere, as well as the general crude price increase due to MENA uncertainties – e.g. the Bahrain’s State Information Agency reports nearly 20% economic growth for 2011. Hence, if there was any Spring in the Arab world, it was the budding of (Wahhabi sectarian) ideological and hydrocarbon exports of the GCC autocracies in 2011.
Nevertheless, the announced reductions of the American physical presence in Afghanistan, its limits in (nearly failed, nuclear state of) Pakistan, massive overextensions suffered on the southwestern flank of the Euro-Asian continent, as well as the recent US Army pullout from Iraq, is felt within the GCC (in France, Israel and Turkey too) as dangerous exposure to neighboring (increasingly anticipated as assertive) Iran, as well as Russia and China behind it.
Right now, Syria pays a (proxy war) prize for it: This multi-religious country may end up entirely combusted, creating a dangerous security vacuum in the heart of MENA. Oil, its suppliers and its consumers are resolute to fortify and eventually diversify and intensify their bitter covert and overt fight in maintaining the status quo course.
Petro-retro Status Quo: Petrodollars and petro-security
The US has a lasting geo-economic interest in the Gulf of a rather extensive agenda, which is inevitably coupled with its overarching global security concerns. As is well known, oil is the most traded commodity in the world– roughly 12% of overall global trade. By far the largest portion of internationally–traded crude originates from the Gulf. Thus, the US imperatives in the Gulf are very demanding: (i) to support the friendly local regimes with their present socio-political and ideological setups; (ii) to get, in return, their continued approval for the massive physical US military presence and their affirmative vote in international fora; (iii) to maintain its decisive force in the region, securing unhindered oil flows from the Gulf; (iv) to remain as the principal security guarantor and tranquilizer, preventing any hostile takeover – be it of one petrol-exporting state by another or of internal, domestic political and tribe/clan workings; (v) to closely monitor the crude-output levels and money flow within the Gulf and to recycle huge petro-dollar revenues, usually through lucrative arms sales and other security deals with the GCC regimes; (vi) will not enhance, but might permit (calls for) gradual change of the domestic socio-economic and politico-ideological frames in the particular Gulf state, as long as it does not compromise the US objectives in the region as stated above, from (i) to (v).
On the other side of Hormuz, Iran is a unique country that connects the Euro-Med/MENA with Central and South, well to the East Asia, so as it solely bridges the two key Euro-Asian energy plateaus: the Gulf and Caspian. This gives Iran an absolutely pivotal geopolitical and geo-economic posture over the larger region – an opportunity but also an exposure! No wonder that the US physical presence in the Gulf represents a double threat to Iran – geopoli- tically and geo-economically. Nearly all US governments since the unexpected 1979 Shah’s fall, with the G.W. Bush administration being most vocal, have formally advocated a regime change in Teheran. On the international oil market, Iran has no room for maneuver, neither on price nor on quotas. Within OPEC, Iran is frequently silenced by cordial GCC voting.
The US hegemony in the Gulf, a combination of monetary control (crude is traded exclusively in US dollars, predominantly via the New York-based NYMEX and London-based IPE) and physical control (the US Navy controls all transoceanic oil transports), is the essential confirmation as well as the crucial spring of the overall US global posture. In exchange for the energy inflow security, the US anchors loyal bandwagoning in many places around the globe. As long as oil remains priced in USD, it will represent the prime foreign reserve currency (some 68% of global reserves is held in USD), as the functional tie between the major currencies’ exchange rates, (economic and politico-military) security and fossil-fuel energy cannot be derailed and delinked. Finally, this hegemony is not only based on the exclusivity of oil currency, but also on the exceptionality of the very policy of pricing.
Throughout most of oil’s short history, the price for ‘black gold’ was high enough to yield profits (via the 7-Sisters, mostly for Wall Street – besides the US military, another essential pillar of American might), still without pricing it overly high, which would in return encourage sustained and consequential investments in alternative energy sources. Basically, the main problem with Green/Renewable (de-carbonized) energy is not the complexity, expense, or the lengthy time-line for fundamental technological breakthrough; the central issue is that it calls for a major geopolitical breakthrough. Oil and gas are convenient for monopolization (of extraction location and deployed machinery, of intl. flows, of pricing and consumption modes) – it is a physical commodity of specific locality. Any green technology (not necessarily of particular location or currency) sooner or later will be de-monopolized, and thereby made available to most, if not to all. Therefore, the overall geopolitical imperative for the US remains preservation – not change – of the hydrocarbon status quo.
Ergo, oil (and gas) represents far more than energy. Petroleum (be it a finite biogenic mineral or not) is a socio-economic, psychological, cultural, financial, security and politico-military construct, a phenomenon of civilization that architectures the world of controllable horizontalities which is currently known to, possible and permitted, therefore acceptable for us.
In a broader historical, more vertical or philosophical sense, the hydrocarbons and its scarcity phychologization, its monetization (and related weaponization) is serving rather a coercive and restrictive status quo than a developmental incentive. That essentially calls not for an engagement but compliance. It finally reads that the fossil fuels’ consumption (along with the policy of prizing it) does not only trigger one CC – Climate Change (repeated failure in Durban), but it also perpetuates another global CC – planetary Competition and Confrontation (over finite resources) – to which the MENA calamities are only a tip of an iceberg. Therefore, this highly addictive construct logically permits only a (technological) modernization which is defensive, restrictive and reactive. No wonder that democracy is falling short.
Anything terrific between Arctic and Pacific?
“…bold Russian Arctic policy is (yet) another signal that the Federation… will increase its (non territorial leverage and geopolitical) projection as a major energy supplier of the world throughout the 21st century…” – I noted in 2009. To clarify: Neither Russian territorial size and historical passions, nor pride and socio-economic necessity will cause Moscow to sink down to a second-rank power status. How will the Federation meet its strategic imperative? We have already discussed the two important pillars of the US strength (the so-called ‘East Coast twin might’: the Pentagon and Wall Street). Well, there is the ‘Pacific Coast twin might’ too. The post-Soviet Russia has neither the ideology – global soft power appeal of the US entertainment industry and its ravenous (Hollywood), nor has it the vibrant, world-leading and highly lucrative High-Tech and IT sector (Silicon Valley) that the US possesses.
Let us generously assume the quantitative and qualitative parity between the US and Russia’s armed forces. Still, military modernization requires constant cash injections. How to maintain that? Moscow holds a big advantage: the US imports hydrocarbons while the Federation exports it. Nevertheless, Wall Street controls the international (petrodollar) monetary flow – even the post-Soviet republics are not trading oil in Rubles, but in US dollars. Hence, to meet and finance its strategic imperatives, as well as to respond to the growing international energy demands and to the domestic pressures, Moscow has only non-high tech exports – fossil-fuels – at convenient disposal (no Silicon Valley, no Hollywood). Ergo, Russia is more exposed and vulnerable than the US, and therefore it is an even stronger supporter of both current international market conditions and the hydrocarbon status quo.
On the eastern, ascendant flank of the Eurasian continent, the Chinese vertigo economy is overheated and too-well integrated in the petrodollar system. Beijing, presently, cannot contemplate or afford to allocate any resources in a search for an alternative. The Sino economy is low-wage- and labor intensive-centered one. Chinese revenues are heavily dependent on exports and Chinese reserves are predominantly a mix of the USD and US Treasury bonds. To sustain itself as a single socio-political and formidably performing economic entity, the People’s Republic requires more energy and less external dependency. Domestically, the demographic-migratory pressures are huge, regional demands are high, and expectations are brewing. Considering its best external energy dependency equalizer (and inner cohesion solidifier), China seems to be turning to its military upgrade rather than towards the resolute alternative energy/Green Tech investments – as it has no time, plan or resources to do both at once. Inattentive of a broader picture, Beijing (probably falsely) believes that lasting containment, especially in the South China Sea, is unbearable, and that – at the same time – fossil-fuels are available (e.g., in Africa and the Gulf), and even cheaper with the help of warships.
Opting for either strategic choice will reverberate in the dynamic Asia–Pacific theatre. However, the messages are diametrical: An assertive military – alienates, new technology – attracts neighbors. Finally, armies conquer (and spend) while technology builds (and accumulates)! At this point, any eventual accelerated armament in the Asia-Pacific theatre would only strengthen the hydrocarbon status quo. With its present configuration, it is hard to imagine that anybody can outplay the US in the petro-security, petro-financial and petro-military global playground in the following few decades. Given the planetary petro-financial-tech-military causal constellations, this type of confrontation is so well mastered by and would further only benefit the US and the closest of its allies.
To complete the picture, both Russia and China are supporting the hydrocarbon status quo. Other major theaters are all too dependent geo-economically: on a supply end (Central Asian republics, Brazil, Canada, Mexico, Norway, Venezuela, etc.) and on a receiving end (India, Australia, South Africa, etc.) – none is geopolitically emancipated enough to seriously consider any significant tilt towards de-carbonization.
EU-genic or Dynamic?
Less explicitly, the EU (as the post-Westphalian concert of 4 Europes – conglomerate of the Atlantic, Central, Eastern and Scandinavian Europe) will turn consensual to the hydrocarbon status quo, too. If taking a closer look at any of the previous and current Brussels’ transportation and energy policy initiatives, it would clearly show us that the notion was primarily driven by the closest common security consideration denominator – as an attempt to decrease the external vulnerabilities, that includes those of an energy dependency (e.g. energy efficiency initiatives: EEP, Europe 2020, EUFORES, etc.).
Hence, the Union was first and still is most of all a peace treaty for the post WWII Europe recovery. Therefore, both settings (ECSC and EuroAtom) served the confidence building purpose, not as energy-related clearing house/s. The energy policy (suppliers for and composition of the primary energy mix, taxation, etc.) as well as the transportation (means and modes) strictly resides in the individual competence of the Block’s Member States (MS). Any change in the present status quo would assume the common platform of the MS via the Council of the EU (and the subsequent formalization of such a position, at least through the EU Parliament’s promulgation). The absence of such a commonly agreed policy means more of the hydrocarbon status quo. Lastly, it is not only that Atlantic Europe and Central Europe manage their respective energy inflow, its composition and external dependences differently (and selectively). The issue of the hydrocarbon status quo is closely related to the very question of the Euro (and the US dollar-alternate/reserve currency: the British Pound).
For the severely exposed Euro-zone (unsettled global financial crisis), it is a bitter choice between a petrol-pampered dollar (as a stability pillar) and the return to gold (meaning to the pre-Nixon Shock times, before the Bretton Woods consensus was renounced). Brussels and the European Central Bank (ECB) believe they can exercise an influence on the American dollar, via the US Federal Reserves, while nowadays gold resides everywhere – least of all in the US or EU reserves or their mines. Simply put, the post-Nixon currency/ies is/are negotiable; gold is a solid, non-corrosive metal. Also, one should never forget that the politically most influential segment of the Union – Atlantic Europe – shares the same ocean with the US, and all that comes with it (including the ‘monetary nationalism/exceptionalism’).
However, besides Japan, Brussels will remain a main promoter of the “Kyoto II” mechanism. The UN Framework Convention on Climate Change (UNFCCC) with its protocol from Kyoto of 1997 placed China and India in the “emissions tolerant” Annex II, so both subsequently ratified the Instrument. The US and Russia were situated in the much less forgiving Annex I. Past the collapse of the Soviet Union and contraction of the post-Soviet economy and demographics, Kremlin knew it could easily meet the pre-1990 emissions target. Still, it was bargaining until the end of 2004. With the 17% pollution allocation, Russia’s ratification was sufficient enough to activate Kyoto, which eventually entered into force shortly after, in 2005.
The EU’s formal support to the Kyoto protocol and “spirit of UNFCCC/IPCC” has several reflex levels. Without ambition to elaborate it all in detail, let us just note that the Union’s reasons are of political (declared principles) and economic (pragmatic) nature. As the conglomerate of states committed to the supranational principle rituality, it is natural for the Block to (at least declaratively) support any multilateral endorsement, which assumes the supranational notion as well as the full horizontality of implementation and monitoring of compliance mechanism.
The Kyoto provisions of the late 1990s were in perfect harmony with the two grand strategy roadmaps of the EU: the Lisbon (2000) and Goteborg (2001) – hence, the EU’s voluntary self-endorsement via the Emissions Trading Scheme (ETS). This virtue out of necessity was clear: in the globalized competitive world, the Union of modest economical and of no demo-graphic growth has only the option to become a knowledge based economy, re-architectured as the fair and balanced post-industrial society. Both strategies were gradually abandoned, the Block enlarged (to Eastern Europe, mostly the states whose economies also contracted past the breakup of the Warsaw Pact lager countries – meaning, who are able to meet the Kyoto targets), and the Union’s post-industrial Green-tech renewal waits for better days.
How swift is the shift?
Brussels is well-positioned, but it will not be a global frontrunner in any technology shift. For such a (hydrocarbon de-psychologization) turn, it has neither an inner coherence, visionary strength, nor an external posture. The EU’s economic growth is very symbolic, despite all the huge territorial enlargements of the past decade. Actually, the Union’s growth could be portrayed as negative in many categories. It always serves as a good reminder that a Europe of (economic and demographic) growth was a Europe of might. Europe without growth is a Europe of principles (or to say: of administrative frameworks’ colonialism). The Eastern enlargement of the EU was this very virtue out of necessity: a last territorial expansion, exceptionally based not on coercion but on an ‘attraction’ of the EU’s transformative power.
Within the OECD/IEA grouping, or closely; the G-8 (the states with resources, infrastructure, tradition of and know-how to advance the fundamental technological breakthroughs), it is only Japan that may seriously consider a Green/Renewable-tech U-turn. Tokyo’s external energy dependencies are stark and long-lasting. After the recent nuclear trauma, Japan will need a few years to (psychologically and economically) absorb the shock – but it will learn a lesson. For such an impresive economy and considerable demography, situated on a small landmass, which is repeatedly brutalized by devastating natural catastrophes (and dependent on yet another disruptive external influence – Arab oil), it might be that a decisive shift towards green energy is the only way to survive, revive, and eventually to emancipate.
An important part of the US–Japan security treaty is the US energy supply lines security guaranty given to (the post-WWII demilitarized) Tokyo. After the recent earthquake-tsunami-radiation armageddon, as well as witnessing the current Chinese military/naval noise, Japan will inevitably rethink and revisit its energy policy, as well as the composition of its primary energy mix. That indicates the Far East as a probable zone of the Green-tech excellence and a place of attraction for many Asians in the decade to come.
(Based on the public lecture “Asia – Pacific: The Hydrocarbon Status Quo and Climate Change”, Chulalongkorn University, Mahachulalongkorn/MEA Think-Tank; Thailand, Bangkok 04 OCT 2011)
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The World After COVID-19: Does Transparent Mean Healthy?
The insanity of despair and primaeval fear for one’s health (and today, no matter how ironic and paradoxical it sounds, this may be the state of mind that brings many of us together) will most likely give rise to a new global formation that will then become a global reality. It is still hard to say what it will be like exactly, but it is clear that the world will become more transparent. And I do not mean in the usual sense of anti-corruption measures, but rather in the original sense of the word – the world will become more “see-through.” Our temperature will be monitored. Smartphones with built-in sensors will collect precise data not only about our clicks and likes, but about our physical and possibly emotional state. The world and the people that live in it will undergo a number of changes once the current coronavirus pandemic is over, and many of those changes will be accompanied by a leap in technological development.
For many experts and scientists, the events that are unfolding today are reminiscent of what happened in 2003, when the SARS virus presented the first large-scale threat to human health of the new millennium. Unlike today’s unbidden crowned guest, SARS was not so virulent, yet it caused major concerns for a number of countries, particularly in East and Southeast Asia. Hence the deadly lessons learned in Singapore and partly in Taiwan, where the government has for two decades now been successfully using a system of mass surveillance of the everyday life of its citizens – a system that has received the approval of the people. This system is part of Singapore’s cybersecurity strategy and allows the physical condition of large masses of people to be monitored, thereby preventing diseases from spreading and escalating into epidemics. This, combined with their ability to enforce extremely strict quarantine measures and carry out mass testing instead of the selective testing currently practised in Europe and Russia, has allowed Singapore and Taiwan to contain the spread of the disease and prevent it from turning into an epidemic. Of course, their compact territories have certainly played a part here. Other countries, for instance, Israel and Russia, have already followed this example and approved a monitoring system that uses mobile data and geolocation in order to trace the movements of persons with confirmed infection. We have to assume that one of the first steps after the COVID-19 pandemic will be to embed this surveillance system even deeper into the public life. Most likely, this step will be met with approval instead of protests and street rallies.
I would not wish to speak for everyone, but it seems to me that the choice between health and privacy is a no-brainer. The pandemic will end, and what the world emerging from the pandemic will look like is an interesting question worthy of discussion. To quote the Deputy Minister of Health of Iran, who had COVID-19, we can note that the coronavirus came to us from a relatively safe country and, contrary to recent rumours, it does not only affect those of Asian heritage: quite the opposite, it is very democratic in its choice of victims, which is to say, it affects everyone.
Hence the question: by self-isolating, we are buying doctors and scientists time to find a cure to the virus and test vaccines, but what are we going to do in the event of a new pandemic? Here, humanity faces two choices. The first is to give free rein to nationalists who are already jubilant and triumphant over the failures of globalization and the inability of liberal democratic countries to shut down their borders to viruses and undesirable immigrants. The second is to move to a radically new formation where we will become even more mutually dependent and open to our societies and governments, because this will be a mandatory condition for moving about and doing business, and perhaps even starting a family. Personal secrets will become a thing of the past, a fairy tale we tell our grandchildren. In fact, the issue is far more serious, with multiple additions and ensuing consequences.
Following the COVID-19 pandemic, consensus and mutual understanding between states will be relevant like never before, especially since the problems of disarmament, nuclear warheads, defence budgets propped up by taxpayer money, international sanctions, etc., that appeared and developed during the presidencies of Nikita Khrushchev and Ronald Reagan may finally move into the background. Instead, world leaders, especially given that most of them are at an age that makes them particularly vulnerable to the coronavirus, should start thinking about new plans for investing in healthcare, socioeconomic aspects of life and technological development, because those will be intrinsically linked with the other aspects of improving the state mentioned above. Will this represent a new social contract between the government, the public and the citizen? Probably. Will it represent a new pact between governments? One would hope so. Perhaps the coronavirus pandemic will break down the old world and give rise to the new one that so many expected to appear in the 1990s. But what was to await us back then was proxy wars and a confrontation through sanctions that split societies from within and raised barriers between states. Maybe this new world will be one where surveillance cameras and sensors will first prompt a feeling of relief and then become an integral part of the picture. Perhaps it will be a world where life without external surveillance and control will appear unsafe and unnatural.
From our partner RIAC
Future Goals in the AI Race: Explainable AI and Transfer Learning
Recent years have seen breakthroughs in neural network technology: computers can now beat any living person at the most complex game invented by humankind, as well as imitate human voices and faces (both real and non-existent) in a deceptively realistic manner. Is this a victory for artificial intelligence over human intelligence? And if not, what else do researchers and developers need to achieve to make the winners in the AI race the “kings of the world?”
Over the last 60 years, artificial intelligence (AI) has been the subject of much discussion among researchers representing different approaches and schools of thought. One of the crucial reasons for this is that there is no unified definition of what constitutes AI, with differences persisting even now. This means that any objective assessment of the current state and prospects of AI, and its crucial areas of research, in particular, will be intricately linked with the subjective philosophical views of researchers and the practical experience of developers.
In recent years, the term “general intelligence,” meaning the ability to solve cognitive problems in general terms, adapting to the environment through learning, minimizing risks and optimizing the losses in achieving goals, has gained currency among researchers and developers. This led to the concept of artificial general intelligence (AGI), potentially vested not in a human, but a cybernetic system of sufficient computational power. Many refer to this kind of intelligence as “strong AI,” as opposed to “weak AI,” which has become a mundane topic in recent years.
As applied AI technology has developed over the last 60 years, we can see how many practical applications – knowledge bases, expert systems, image recognition systems, prediction systems, tracking and control systems for various technological processes – are no longer viewed as examples of AI and have become part of “ordinary technology.” The bar for what constitutes AI rises accordingly, and today it is the hypothetical “general intelligence,” human-level intelligence or “strong AI,” that is assumed to be the “real thing” in most discussions. Technologies that are already being used are broken down into knowledge engineering, data science or specific areas of “narrow AI” that combine elements of different AI approaches with specialized humanities or mathematical disciplines, such as stock market or weather forecasting, speech and text recognition and language processing.
Different schools of research, each working within their own paradigms, also have differing interpretations of the spheres of application, goals, definitions and prospects of AI, and are often dismissive of alternative approaches. However, there has been a kind of synergistic convergence of various approaches in recent years, and researchers and developers are increasingly turning to hybrid models and methodologies, coming up with different combinations.
Since the dawn of AI, two approaches to AI have been the most popular. The first, “symbolic” approach, assumes that the roots of AI lie in philosophy, logic and mathematics and operate according to logical rules, sign and symbolic systems, interpreted in terms of the conscious human cognitive process. The second approach (biological in nature), referred to as connectionist, neural-network, neuromorphic, associative or subsymbolic, is based on reproducing the physical structures and processes of the human brain identified through neurophysiological research. The two approaches have evolved over 60 years, steadily becoming closer to each other. For instance, logical inference systems based on Boolean algebra have transformed into fuzzy logic or probabilistic programming, reproducing network architectures akin to neural networks that evolved within the neuromorphic approach. On the other hand, methods based on “artificial neural networks” are very far from reproducing the functions of actual biological neural networks and rely more on mathematical methods from linear algebra and tensor calculus.
Are There “Holes” in Neural Networks?
In the last decade, it was the connectionist, or subsymbolic, approach that brought about explosive progress in applying machine learning methods to a wide range of tasks. Examples include both traditional statistical methodologies, like logistical regression, and more recent achievements in artificial neural network modelling, like deep learning and reinforcement learning. The most significant breakthrough of the last decade was brought about not so much by new ideas as by the accumulation of a critical mass of tagged datasets, the low cost of storing massive volumes of training samples and, most importantly, the sharp decline of computational costs, including the possibility of using specialized, relatively cheap hardware for neural network modelling. The breakthrough was brought about by a combination of these factors that made it possible to train and configure neural network algorithms to make a quantitative leap, as well as to provide a cost-effective solution to a broad range of applied problems relating to recognition, classification and prediction. The biggest successes here have been brought about by systems based on “deep learning” networks that build on the idea of the “perceptron” suggested 60 years ago by Frank Rosenblatt. However, achievements in the use of neural networks also uncovered a range of problems that cannot be solved using existing neural network methods.
First, any classic neural network model, whatever amount of data it is trained on and however precise it is in its predictions, is still a black box that does not provide any explanation of why a given decision was made, let alone disclose the structure and content of the knowledge it has acquired in the course of its training. This rules out the use of neural networks in contexts where explainability is required for legal or security reasons. For example, a decision to refuse a loan or to carry out a dangerous surgical procedure needs to be justified for legal purposes, and in the event that a neural network launches a missile at a civilian plane, the causes of this decision need to be identifiable if we want to correct it and prevent future occurrences.
Second, attempts to understand the nature of modern neural networks have demonstrated their weak ability to generalize. Neural networks remember isolated, often random, details of the samples they were exposed to during training and make decisions based on those details and not on a real general grasp of the object represented in the sample set. For instance, a neural network that was trained to recognize elephants and whales using sets of standard photos will see a stranded whale as an elephant and an elephant splashing around in the surf as a whale. Neural networks are good at remembering situations in similar contexts, but they lack the capacity to understand situations and cannot extrapolate the accumulated knowledge to situations in unusual settings.
Third, neural network models are random, fragmentary and opaque, which allows hackers to find ways of compromising applications based on these models by means of adversarial attacks. For example, a security system trained to identify people in a video stream can be confused when it sees a person in unusually colourful clothing. If this person is shoplifting, the system may not be able to distinguish them from shelves containing equally colourful items. While the brain structures underlying human vision are prone to so-called optical illusions, this problem acquires a more dramatic scale with modern neural networks: there are known cases where replacing an image with noise leads to the recognition of an object that is not there, or replacing one pixel in an image makes the network mistake the object for something else.
Fourth, the inadequacy of the information capacity and parameters of the neural network to the image of the world it is shown during training and operation can lead to the practical problem of catastrophic forgetting. This is seen when a system that had first been trained to identify situations in a set of contexts and then fine-tuned to recognize them in a new set of contexts may lose the ability to recognize them in the old set. For instance, a neural machine vision system initially trained to recognize pedestrians in an urban environment may be unable to identify dogs and cows in a rural setting, but additional training to recognize cows and dogs can make the model forget how to identify pedestrians, or start confusing them with small roadside trees.
The expert community sees a number of fundamental problems that need to be solved before a “general,” or “strong,” AI is possible. In particular, as demonstrated by the biggest annual AI conference held in Macao, “explainable AI” and “transfer learning” are simply necessary in some cases, such as defence, security, healthcare and finance. Many leading researchers also think that mastering these two areas will be the key to creating a “general,” or “strong,” AI.
Explainable AI allows for human beings (the user of the AI system) to understand the reasons why a system makes decisions and approve them if they are correct, or rework or fine-tune the system if they are not. This can be achieved by presenting data in an appropriate (explainable) manner or by using methods that allow this knowledge to be extracted with regard to specific precedents or the subject area as a whole. In a broader sense, explainable AI also refers to the capacity of a system to store, or at least present its knowledge in a human-understandable and human-verifiable form. The latter can be crucial when the cost of an error is too high for it only to be explainable post factum. And here we come to the possibility of extracting knowledge from the system, either to verify it or to feed it into another system.
Transfer learning is the possibility of transferring knowledge between different AI systems, as well as between man and machine so that the knowledge possessed by a human expert or accumulated by an individual system can be fed into a different system for use and fine-tuning. Theoretically speaking, this is necessary because the transfer of knowledge is only fundamentally possible when universal laws and rules can be abstracted from the system’s individual experience. Practically speaking, it is the prerequisite for making AI applications that will not learn by trial and error or through the use of a “training set,” but can be initialized with a base of expert-derived knowledge and rules – when the cost of an error is too high or when the training sample is too small.
How to Get the Best of Both Worlds?
There is currently no consensus on how to make an artificial general intelligence that is capable of solving the abovementioned problems or is based on technologies that could solve them.
One of the most promising approaches is probabilistic programming, which is a modern development of symbolic AI. In probabilistic programming, knowledge takes the form of algorithms and source, and target data is not represented by values of variables but by a probabilistic distribution of all possible values. Alexei Potapov, a leading Russian expert on artificial general intelligence, thinks that this area is now in a state that deep learning technology was in about ten years ago, so we can expect breakthroughs in the coming years.
Another promising “symbolic” area is Evgenii Vityaev’s semantic probabilistic modelling, which makes it possible to build explainable predictive models based on information represented as semantic networks with probabilistic inference based on Pyotr Anokhin’s theory of functional systems.
One of the most widely discussed ways to achieve this is through so-called neuro-symbolic integration – an attempt to get the best of both worlds by combining the learning capabilities of subsymbolic deep neural networks (which have already proven their worth) with the explainability of symbolic probabilistic modelling and programming (which hold significant promise). In addition to the technological considerations mentioned above, this area merits close attention from a cognitive psychology standpoint. As viewed by Daniel Kahneman, human thought can be construed as the interaction of two distinct but complementary systems: System 1 thinking is fast, unconscious, intuitive, unexplainable thinking, whereas System 2 thinking is slow, conscious, logical and explainable. System 1 provides for the effective performance of run-of-the-mill tasks and the recognition of familiar situations. In contrast, System 2 processes new information and makes sure we can adapt to new conditions by controlling and adapting the learning process of the first system. Systems of the first kind, as represented by neural networks, are already reaching Gartner’s so-called plateau of productivity in a variety of applications. But working applications based on systems of the second kind – not to mention hybrid neuro-symbolic systems which the most prominent industry players have only started to explore – have yet to be created.
This year, Russian researchers, entrepreneurs and government officials who are interested in developing artificial general intelligence have a unique opportunity to attend the first AGI-2020 international conference in St. Petersburg in late June 2020, where they can learn about all the latest developments in the field from the world’s leading experts.
From our partner RIAC
How as strategist we can compete with the sentient Artificial intelligence?
Universe is made up of humans, stars, galaxies, milky ways, black holes other objects linked and connected with each other. Everything in the universe has its level of mechanisms and complexities. Humans are very complex creatures man-made objects are more complex and difficult to understand. With the passage of time human beings are more evolved and become more advanced technologically. Human inventions are reached to that level of advancement, which initiates a competition between machines and humans, itself. Humans are the most intelligent mortals on the earth but now human are being challenged by the intelligence (artificial intelligence), which was invented as helping hand for humans to increase efficiency. Here it is important to question that whether human’s intelligence was not enough to survive in the fast growing technological world? Or the man-made intelligence has reached to its peak so that humans come in competition with machines and human intelligence is challenged by the artificial intelligence? If there is competition, then how strategists could compete with artificial intelligence? To answer these questions we first need to know what artificial intelligence actually is.
Artificial intelligence was presented by John McCarthy in 1955; he characterized computerized reasoning in 1956 at Dartmouth Conference, the main counterfeit consciousness meeting that: Every fragment of learning or another element of insight can on a basic level be so unequivocally depicted that a machine can be made to empower it. An endeavor will be made to learn how to influence machines to exploit vernacular, mount deliberations and ideas, take care of sort of issues now held for people, and enhance themselves. There are seven main features of artificial intelligence as follows:-
“Simulating higher functions of brain
Programming a computer to use general language
Arrangement of hypothetical neurons in a manner so that they can form concept
Way to determine and measure problem complexity
Abstraction: it is defined as quality of dealing with ideas , not with events
Creativity and randomness”
Another definition is given by Elaine rich who expressed that counterfeit consciousness is tied in with making computer to do such thing which are presently being finished by human. He said that each computer is artificial intelligence framework. Jack Copland expressed that critical elements of artificial intelligence are speculation discovering that empowers the student to perform in the circumstance that are beforehand experienced. At that point its thinking, to reason is to make inference fittingly, critical thinking implied that by giving information it can finish up comes about lastly trickiness intends to break down a checked situation and investigating the highlights and connection between the articles and self-driving autos are its case.
Artificial intelligence is very common in the developed nations and developing nations are using artificial intelligence according to resources. Now question is that how artificial intelligence is being utilized in the above mentioned fields? Use of AI will be elaborated with help of phenomenon and examples of related fields for better understanding.
World is being more advanced and technologies are improving as well. In this situation states become conscious about their security. At this point states are involving AI approaches in their defense systems and some states are already using artificially integrated technologies. On 11 May 2017, Dan Coats, the executive of US National Intelligence, conveyed declaration to the US Congress on his yearly Worldwide Threat Assessment. In the openly discharged archive, he said that (AI) is progressing computational abilities that advantage the economy, yet those advances likewise empower new military capacities for our enemies’. In the meantime, the US Department of Defense (DOD) is taking a shot at such frameworks. Undertaking Maven, for example, otherwise called the Algorithmic Warfare Cross-Functional Team (AWCFT), is intended to quicken the incorporation of huge information, machine learning and AI into US military capacities. While the underlying focal point of AWCFT is on computer vision calculations for protest identification and characterization, it will unite all current calculation based-innovation activities related with US resistance knowledge. Command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) are achieving new statures of proficiency that empower information accumulation and preparing at exceptional scale and speed. At the point when the example acknowledgment calculations being produced in China, Russia, the UK, the US and somewhere else are combined with exact weapons frameworks, they will additionally expand the strategic preferred standpoint of unmanned elevated vehicles (UAVs) and other remotely worked stages. China’s resistance part has made achievements in UAV ‘swarming’ innovation, including an exhibition of 1,000 EHang UAVs flying in arrangement at the Guangzhou flying demonstration in February 2017. Potential situations could incorporate contending UAV swarms attempting to hinder each other’s C4ISR arrange, while at the same time drawing in dynamic targets.
Humans are the most intelligent creatures that created an artificial intelligence technology. The technology we human introduced is more intelligent than us and works fastest than humans. So here is big question marks that can humans compete with the artificial intelligence in near future. Now days it seems that AI is replacing humans in every field of life so what will be condition after decades or two. There is an alarming competition started between the human and AI. AI was called as demon by Tesla Elon Musk. A well physicist Stephen Hawking also stated that in future artificial intelligence could be proved as a bad omen for humanity. But signs of all this clear and we can clearly see the replacement of humans. We human are somehow losing the competition. But it is also clear that a creator can be destructor also. So as strategist we must have the counter strategies and second plans to overcome the competition. The edge human have over AI is the ability to think and we generate this in AI integrated techs so we must set the level for this. Otherwise this hazard could be a great threat in future and humanity could possibly be an extinct being.
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