Finland, Switzerland, Sweden, Israel, Singapore, the Netherlands and the United States are leading the world when it comes to generating economic impact from investments in information and communications technologies (ICT), according to the World Economic Forum’s Global Information Technology Report 2016.
On average, this group of high-achieving economies at the pinnacle of the report’s Networked Readiness Index (NRI) economic impact pillar scores 33% higher than other advanced economies and 100% more than emerging and developing economies. The seven are all known for being early and enthusiastic adopters of ICT and their emergence is significant as it demonstrates that adoption of ICTs – coupled with a supportive enabling environment characterized by sound regulation, quality infrastructure and ready skills supply among other factors – can pave the way to wider benefits.
The breakaway of these seven economies is significant for other nations given the role that networked readiness is likely to play as the world transitions to the Fourth Industrial Revolution. The Global Information Technology Report 2016 finds high levels of confidence among business leaders that capacity to innovate is increasing, which suggests that other nations, too, could start to see more economic and social impact from ICT. However, on a cautionary note, the NRI data also suggest that individuals are driving ICT adoption much more enthusiastically than either governments or business, where no clear trends are discernible across regions since 2012.
Who leads the Networked Readiness Index in 2016?
The 2016 edition of the NRI finds Singapore as the highest-placed country in the world when it comes to networked readiness. Finland, which topped the ranking in 2014, remains in second place for a second year in a row, followed by Sweden (3rd), Norway (4th) and the United States (5th), which climbed two places. Making up the rest of the top 10 are the Netherlands, Switzerland, the United Kingdom, Luxembourg and Japan.
While the upper echelons of the NRI continue to reflect a strong correlation between networked readiness and per capita income, roughly 75% of the countries included in this year’s index show a score improvement in 2016. However, convergence both at the global and regional level remains elusive, with four regions – Eurasia, Emerging Europe, the Middle East, North Africa and Pakistan (MENAP) group, and sub-Saharan Africa – having widened the gap between the most and least networked-ready since 2012.
Elsewhere in the NRI, of the large emerging markets, Russia remains unchanged at 41st position. China comes next, moving up 3 places to 59th. South Africa improves markedly, climbing 10 places to 65th, while Brazil partially recovers from a previous downward trend to 72nd this year and India drops two places to 91st.
Europe remains at the technology frontier; seven of the top 10 NRI countries are European. Yet the performance range is wide, with Greece dropping four places to 70th position and Bosnia and Herzegovina closing the group at 97. Several Eastern European countries, notably the Slovak Republic, Poland and the Czech Republic, are making big strides, landing spots in the NRI top 50. Better affordability and large improvements in economic and social impacts are making major contributions to this success. Italy is another notable mover this year, improving 10 places to 45th position as the economic and social impacts of ICT are starting to be realized (up 18 in the global impact ranking).
The Eurasia region continues its upward trajectory, with the average NRI for the region increasing significantly since 2012. In particular, it is notable that the improvement is observed across all four elements that make up the index: environment, readiness, usage and impact. The region is led by Kazakhstan, which continues on its positive trajectory of recent years to land in 39th position.
Malaysia leads the Emerging Asian economies in 2016 and moves up one spot to 31st position overall. The country continues to perform strongly, supported by a government which is fully committed to the digital agenda. The top five in the region in terms of overall ICT readiness remain Malaysia, Mongolia, Thailand, China and Sri Lanka as in 2015. The group of Emerging Asian countries has been moving up and converging since 2012. Individual usage in the region is still one of the lowest in the world, but has been growing strongly in recent years.
The performance range by countries in the Latin America and Caribbean region remains widely dispersed with almost 100 places between Chile (38th) and Haiti (137th). There was no clear trend from 2015 to 2016 in terms of relative performance, with Chile and Haiti staying put and, of the remaining group, half of the countries improving their ranking and the other half dropping. Considering the absolute NRI score, however, the region has been moving up and converging since 2012. In order to foster the innovation forces that are key for thriving in the digitized world and the emerging Fourth Industrial Revolution, many governments in the region will urgently need to reinforce efforts to improve their regulatory and innovation environments.
The United Arab Emirates (26th) and Qatar (27th) continue to lead the Arab world in networked-readiness. In addition, the MENAP region (Middle East, North Africa and Pakistan) is home to two of the biggest movers in this year’s ranking: Kuwait (61st, up 11) and Lebanon (88th, up 11). In both cases, individuals are leading the charge, with the business sector catching up and strongly contributing to the successful performance. While governments are lagging behind in terms of digital adoption (Kuwait, 81st; Lebanon, 124th), the business community in both countries is registering an increased weight on ICT in government vision and efforts to improve the regulatory environment.
The NRI also sees several sub-Saharan African countries among the top upward movers, including South Africa (65th, up 10), Ethiopia (120th, up 10) and Côte d’Ivoire (106th, up 9). Leadership, in terms of digital adoption, is coming from different groups of stakeholders. While efforts are very much government-driven in Ethiopia and Côte d’Ivoire, the business sector is providing the most momentum in South Africa. The largest barriers to tackle for Côte d’Ivoire will be infrastructure and affordability; reversing the trend of a deteriorating business and innovation environment for South Africa; and boosting individual usage and skills for Ethiopia.
“The digital economy is an essential part of the architecture of the Fourth Industrial Revolution. In order for digital technology to continue contributing economic and social impact, societies need to anticipate its effects on markets and to ensure a fair deal for workers in digitized market environments. New models of governance will be key in this,” said Richard Samans, Head of the Centre for the Global Agenda, Member of the Managing Board, World Economic Forum Geneva.
“Cross-border data flows drive innovation and growth,” says Pastora Valero, Vice President of Government Affairs, Cisco. “The countries and companies innovating most prominently know that it is the free flow of ideas and information, which leads to improvements in processes and products. Initiatives to foster the free flow of data are crucial to supporting the global nature of the data economy.”
“Measuring the economic and social impact of the digital economy is important for making appropriate policy decisions in both developed and developing economies. The Networked Readiness Index is a valuable tool for helping public and private sector leaders in leveraging the potential of technology.” – Soumitra Dutta, Cornell University.
‘ “Digital” is not just about technology. It is a state of mind, and the source of new business models, new consumption patterns, new ways for business and individuals to organize, produce, trade and innovate. In the global game of digital innovation, the performance and progress made by emerging economies such as Singapore, the United Arab Emirates or South Africa for example are remarkable: they may hold the promise of even more spectacular improvements in the ways digital technologies will be harnessed to competitiveness, growth and social progress in the coming years.’ – Bruno Lanvin, INSEAD.
In addition to providing insights into countries’ performance in the unfolding digital revolution, the report notes a number of trends across ICT adoption in 2016:
How much innovation is “digital”? As the global economy becomes increasingly digitized so, it would seem, innovation is becoming much less defined in a narrow technological sense. For example, while the report finds business model innovation on the rise in more than 100 countries, it also finds stagnation in the Business Usage pillar. This would suggest that while innovation is a top priority for many businesses, they are still missing out on opportunities for greater impact through ICT adoption.
Patents are declining as a measure of innovative capacity: While the minds of business executives around the world are increasingly focused on innovation, traditional measures for innovation such as the number of patents registered are telling a smaller and smaller part of the story. This may be related to the fact that the current transformation is nurtured by a different type of innovation, increasingly based on digital technologies and on the new business models it allows.
The ICT infrastructure gap remains a chronic challenge and is getting wider: Of the 12 pillars of the report, infrastructure is the one where improvement is least pronounced. Worse, since 2012 the lowest-ranked countries have been reporting a deterioration in their infrastructure in absolute terms. Infrastructure is a key determinant of a nation’s ICT-readiness alongside affordability and skills, acting as a gateway to increased usage and ultimately economic and social impact.
Social impact needs new momentum in important areas but is picking up overall: While the social impact pillar of the NRI has seen positive change overall since 2012, most regions register a decline in one of its important components, the impact of ICT on government efficiency. Another important social impact indicator, ICTs and access to basic services, is starting to recover in 2016 after years of decline. This suggests that more people are feeling the benefits of online access to healthcare, finance, insurance and other services. Social impacts on the whole rose most strongly in the group of high-income countries over the year.
Competition in 5G Communication Network and the Future of Warfare
The present era is experiencing a shift from 4G (4th Generation) to 5G (5th Generation) networked communication. This shift will radically change all civil and defence communications. In future warfare, it is expected to develop an atmosphere of information or ‘infosphere’ for sharing real-time intelligence characterised by high-speed, low latency and increased bandwidth networks. This potential of 5G is believed to significantly impact the character and future of war. It will enable an agile and fast data communication service that will support the entire battlefield network in integrated and all-domain warfare. This support will allow the speedy transfer of all types of visual and textual data and information from one domain to another, increasing the speed of war. 5G would not only connect all domains of the battleground, but it would also link disconnected networks through network slicing. This will enable remote operations with more private, secure, and restricted access. Due to the super-fast speed of the 5G network, it can afford to carry out multiple isolated functions side-by-side.
5G would also enhance the operational capacity of autonomous military systems such as drones and Unmanned Aerial Vehicles (UAVs). Presently, the capabilities of autonomous military systems are restricted due to their limited onboard processing and data storage capacity; however, with 5G-enabled autonomous military systems, large sets of data, such as terrain maps stored on the cloud, can be downloaded in milliseconds. It is also expected that 5G might initiate the move towards fully autonomous systems due to accelerated networked response and action time. The improved real-time data, collected by the independent system in an autonomous military system through various networked sources and sensors, would be infused with AI and machine learning algorithms to identify, locate, and engage the target without human supervision. Due to such capability of 5G, many countries have shown progress in this arena.
The United States (US) and China have been competing to take the lead in 5G technologies. The major 5G telecoms in the US have deployed their initial nationwide networks. On the other hand, all cities in China and 87% of its rural areas have a 5G network. The Chinese defence forces are now focused on benefitting from 6G communication technologies to adapt to the demands of future warfare.
The US is expected to deploy 5G on its Forward Operating Bases (FOBs) as these are crucial points for collecting intelligence for launching and defending attacks. US troops also have access to 5G-enabled Android Team Awareness Kits that display data on a tablet or smartphone. Similarly, Chinese troops have also been provided with gadgets that will allow tracking of troops, terrain and intelligence on battlegrounds. China has also deployed 5G on the China-India border to monitor Indian military activities.
India has launched an initiative called 5G India (5Gi). Under this initiative, India has given the responsibility to establish end-to-end 5G test beds to research centres such as the Centre of Excellence in Wireless Technology (CEWiT) and the Society for Applied Microwave Electronics Engineering & Research (SAMEER), technical universities such as Indian Institute of Technology Madras, Delhi, Hyderabad, Kanpur and Bombay and Indian Institute of Science, Bangalore. The country is proactive in developing indigenous 5G communication networks. For this, it has provided competitive grants and has created a 5G Alliance Fund that would provide necessary financial assistance for 5G evolution. The Indian Army is also working to develop and deploy 5G networks to improve communication for its frontline forces, which could have implications for Pakistan.
The Ministry of Information Technology and Telecommunication has laid a roadmap for 5G in Pakistan. The Pakistani telecom operators, including PTCL, Telenor, Zong and Jazz, have successfully tested 5G in Pakistan. 5G was expected to be launched in 2023; however, progress were delayed due to political instability in the country. According to a study by the Pakistan Institute of Development Economics (PIDE), the exorbitant tax on phones and lack of availability of 5G enabled phones in Pakistan might hinder the evolution of 5G. Pakistan has also collaborated with China to facilitate the launch of 5G technology. China’s technological support and the efforts of the telecom industry has been the key force behind 5G success in Pakistan. A similar roadmap can be adapted for other emerging technologies such as AI, cyber and space.
5G is a leap forward in complex communication networks. Although it will significantly enhance communication speed, it will neither diminish nor eliminate the importance of 4G and 3G networks. Instead, 5G will support other emerging technologies such as Cloud, Quantum Computing, the Internet of Things, etc. Each decade, the world will upgrade its generation of networks such as 6G and 7G. The deployment of 5G networks is the need of the hour, given the growing demand for connectivity. Therefore, this is a step in the right direction, and Pakistan must also get on board to quickly set up 5G network towers in the country.
The Development of Artificial Intelligence in China: Talent creation and comparison with U.S.
In the process of developing and implementing AI technology, we need to be pragmatic and orderly. AI education intensifies the driving force for developing the related technology and industry, and it is also the fundamental guarantee for nurturing and cultivating high-quality AI talents and for the sustainable development of related technology and industry. China’s AI education initially created a subject teaching system, and curricula and courses at different levels were offered in universities such as computer science, intelligent science and technology, electronic information and automation. The existing problems of AI development in China and the basic construction of AI are inseparable from the education and training of AI experts. Only by nurturing and cultivating a sufficient number of high-quality AI talents can the smooth development of AI in China be ensured, so that it can climb to the top of international AI.
In terms of AI talent training, the State, Commissions, Ministries, and Departments have made and are making the following noteworthy suggestions:
1) increase AI talent training as a national educational priority.
Not long ago, AI-related playful and recreational activities promoted a wave of AI technology to promote economic and social intelligence in China. AI talents are the top priority in the construction activity to do a good job in planning development, mastering key technologies and promotion. Implementing all this requires high-quality talents. With a view to meeting this social demand, we need to comprehensively plan the training of high-quality AI talents and provide a guarantee for China’s AI to enter a new period of opportunities for sustainable development.
We need to further improve the understanding of AI staff training, establish a comprehensive planning system to create experts and raise the level of preparation as a national educational priority.
2) Establish and standardise AI education at all levels.
According to market demand, we need to comprehensively standardise AI education at all levels and open various schools of a certain scale and proportion, including universities, vocational and technical colleges, AI institutes, technical schools. In China, the Ministry of Education comprehensively expands the current intelligent science and technology, as well as the professional environment, which supports its management. The same holds true for other major universities which are taking action to strengthen the academic teaching of AI, also through the establishment of post-graduate education in some related institutes, as well as spreading basic technologies to primary and secondary schools. The same applies to popular science courses, which provide various forms of extracurricular activities, as well as helping to nurture and cultivate the interest of students of all ages and schools. This is because the level of teachers, who standardise and organise the preparation of various teaching materials, has improved.
3) Multimodal and multi-channel training of high-quality AI talents.
Efforts are made in China to explore and search for various types of high-quality AI talents through multimodal and multi-channel ways, carrying out activities aimed at enhancing and perfecting market-oriented products, and having the experience to promote them. The competent government Departments provide relevant policy support, and State and private research institutes primarily carry out AI product innovation, so that AI science and technology staff perform their tasks comprehensively. Besides participating in research and development of AI products, the main task of schools and colleges is to provide high-quality knowledge resources at all levels Companies strive for excellence in the production of AI products, so that skilled technicians and workers can fully perform their roles. An incentive mechanism for AI experts is established to encourage a higher-level elite to stand out. University students, graduates and science and technology practitioners engaged in AI learning and development are encouraged to pursue AI technological innovation and entrepreneurship and provide the business fund support for their innovative ideas and prototype results.
4) Make full use of the Internet to nurture and cultivate AI talents.
Full use is made of the Internet technology to lend effective technical support to provide effective means for nurturing and cultivating AI talents. The high-level AI platform is used, in line with international standards, to create and improve the domestic AI network teaching platform, provide network education services for AI teaching at all levels, and offer auxiliary teaching tools for other courses.
Some scholars or entrepreneurs believe that China’s AI technology level is already comparable to that of the United States of America. We need to scientifically and objectively evaluate the existing results. We also need to fully reaffirm the achievements and fully understand the shortcomings. Overestimating the existing AI achievements in China is neither realistic nor conducive to the healthy development of this industry.
The United States of America is now the country with the highest overall level of AI technology. Analysing the gap in AI between China and the United States of America helps to maintain a clear understanding. Many experts in the field of AI have pointed out that following the US theory in AI has meant that such applications and innovations are making the industry catch up quickly and regain ground. However, there is still a big gap with the United States of America in terms of basic theoretical research.
There are very few people carrying out basic theoretical research on AI in China. For example, the United States of America places brain science and other neurosciences at the top of research, while China’s independent research and development capabilities in this area are relatively weak and there are gaps in discoveries and innovations. Furthermore, many articles on deep learning have been published in China, but little research is truly innovative in theory or has significant application value.
The Americans are already figuring out what the next AI will be, while such a study has not yet begun at full speed in China. This is the biggest challenge facing the country: it is a difficult problem, involving a wide range of aspects, which cannot be solved by one or two teams. This gap is largely due to the national academic evaluation system and the orientation of practical application. There is room for improving the university analysis criterion: it may take 5-15 years to fully catch up with the United States in the field of AI.
US companies invest a lot of money to train a group of pure high-level technical staff who, from the moment they obtain a PhD, will be recruited by companies and employed in research and development of pure AI technology. Not surprisingly, such an elite team, driven by scientific and technological interests and beliefs, is far ahead at world level in AI research. Few companies in China are willing to spend a lot of money to train a purely technical AI research team and there is also a lack of incentive mechanism within companies. The level of AI research in national universities is also far below the world-leading level. (11. continued)
The Development of Artificial Intelligence in China: Development points and projects
Making machines mimic or even surpass human intellectual behaviour and thinking methods has always been a scientific field full of rich imagination and great challenges. The recent great advances in Artificial Intelligence technology represented by driverless cars and the AlphaGo game have led to enthusiasm and a great deal of funding for the AI field. Considering the development bases, existing problems and opportunities of Chinese AI, strategic thinking on the progress of this industry is continuously proposed for discussion and decision-making reference.
The Internet+ action guidance opinions issued by the State Council have clearly stated that AI is one of the key development areas for the creation of new industrial models. Four Departments, in addition to the National Development and Reform Commission and the Ministry of Science and Technology, have jointly issued implementation plans for Internet+.
The development plan has been promoted in three main aspects and nine minor items. Smart homes, smart wearable devices and smart robots will all become key development support projects. The implementation plan clarifies the development priorities and support projects specific to the Artificial Intelligence industry, thus showing that this field has been raised to a national strategic level.
Considering the great attention paid by the State, increased investment in scientific research and an injection of dividends for talents are expected to accelerate industrial transformation, as facial recognition, language recognition, intelligent robots and other application segments will continue to expand and further promote their marketing.
AI has reached the peak of China’s national strategy, and has shown the need to learn from the advanced Western countries’ research practices to discuss, launch and implement the national plan.
In recent years, the United States of America, the European Union and Japan have successively launched numerous programmes and huge investment, covering future information technology, as well as medicine and neuroscience.
Faced with fierce international competition, China is learning from the experience of the above stated and other countries across disciplines and sectors. The agenda includes the implementation of a project that not only involves AI, but is also inseparable from life sciences, particularly neuroscience. This is so that greater resources can be concentrated on solving the most pressing social needs, such as the development of diagnostic and therapeutic methods for the prevention and treatment of brain diseases, in particular neurodevelopmental diseases, mental illnesses, early diagnosis and intervention in neurodegenerative diseases. The main research focus is on the principle of brain functioning and frontier fields relating to the prevention and treatment of major brain diseases.
As already seen, the foundation of AI involves mathematics, physics, economics, neuroscience, psychology, philosophy, computer engineering, cybernetics, linguistics, biology, cognitive science, bionics and other disciplines and their intersections. The subject of AI has a very broad and extremely rich research content, including cognitive modelling; representation, reasoning and knowledge engineering; machine perception; machine thinking and learning; machine behaviour; etc.
Various AI researchers study such content from different angles. For example, from the ones based on brain function simulation; on the application field and application system; on the system structure and supporting environment; on the distributed artificial intelligence system; on machine theorem demonstration; on uncertainty reasoning, etc. Chinese scholars have made some important achievements in machine theorem proving, hierarchical knowledge representation and reasoning, automatic planning, iris and speech recognition, extension, evolutionary optimisation, data mining (the process of extracting and discovering patterns in large datasets involving methods ranging from machine learning intersection to statistics and database systems), etc. In AI basic research, Chinese experts have great international influence. In general terms, however, the results are not sufficient, the scope is not broad and the overall influence needs to be further improved.
AI basic research is the cornerstone of sustainable development of the related technology, and only by laying sound foundations in it can we provide the driving force for the vigorous development and comprehensive upgrading in the field of its applications. AI basic research needs to be comprehensively strengthened. Innovative multidisciplinarity needs to be encouraged, and importance needs to be attached to it on a forward-looking basis.
The demand for software is an inexhaustible source of technological innovation. AI is considered the fourth industrial revolution. Its theme is three intelligences: factory, production and logistics. The main content of the Made in China 2025 plan is to establish a production line, adopt a management and operation model and start with the following five aspects: design, technology, production, service guarantee and management. The key role of AI technology in smart manufacturing can only be seen from the progress of these aspects.
The implementation of AI technology can be extended to all investment classes and subjects. For example, the intelligent development of technology applied to industrial and mining enterprises includes five points:
1) using intelligent machines (including smart robots) to replace work in hazardous, toxic, radioactive and other harmful environments and in heavy, arduous, repetitive, monotonous, high-altitude, dusty and other difficult conditions, to reduce the intensity of physical and mental work and protect workers (the health issue);
2) using AI technology to design factories and mines, production workshops, sections and equipment, as well as quickly optimise the design scheme and achieve the design intelligence of production;
3) implementing AI technology to fully achieve the production process;
4) developing an intelligent consultation and decision-making system: providing scientific advice, decision-making and management of the production process, and moving towards intelligent production and staff management;
5) researching and developing various expert systems for production planning: monitoring and control of the production process; intelligent fault diagnosis of production systems and equipment; and improvement of labour productivity and product quality.
AI developers combine the characteristics of various enterprises and promote Made in China 2025 and Internet + plans as an opportunity. They seize the historic opportunity of the second machine revolution, achieve AI and vigorously develop these fields. Smart technology and industry inject ideas into the “new” normal of the economy. There is a need to improve the research, development and innovation capabilities of AI technology in the industrial field; to develop high-level products and avoid low-result repetition and haphazard competition. We need to deepen the promotion and implementation of these technologies and make the smart industry bigger and stronger.
As a high-tech segment, AI needs to innovate policy mechanisms, management systems, market mechanisms, and performance transformation to provide an excellent environment for its and its industries’ development and to accompany the healthy progress of initiatives.
Policies need to be introduced to encourage the implementation of AI in the promotion and market development of technology and to broaden the support of national policies, so that new funds and applications will be obtained and new technologies from the laboratory to the field be accelerated as soon as possible. (10. continued).
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