The action being taken by various governments to limit the involvement of China’s Huawei in the provision of equipment for 5G has brought into sharp-focus an issue that has been around for some time, but is now becoming more acute for national security of individual countries. That is, how to ensure that purchased Information and Communication Technology (ICT) hardware and software does not contain aspects, either at time of purchase or later, that offer the possibility of being maliciously used on a large scale – either for espionage or sabotage of crucial national infrastructure.
Australia has totally banned the use of Huawei equipment in its future 5G telecommunications network, while the US has banned its use by official organizations. The US, UK and a number of other developed countries may eventually follow the Australian lead.
Recent focus has been very much on 5G because of the role that it will play in supporting the use of Artificial Intelligence (AI), Internet of Things (IoT), Cloud etc; and, the outsized role that Chinese companies in supplying much of the needed infrastructure (eg Huawei and ZTE) around the world.
The international developments seem almost certain to put Russia in a difficult position. Is it anti-Huawei, pro-Huawei, or somewhere in the middle. If it is in the middle, how does Russia ensure its national security interests?
A Russian National Technology Initiative (NTI) document in 2016 saw the world as being increasingly divided up into closed “economic-trade” blocks formed on the basis of a combination of economic and political issues. It was argued that these blocks, or “alliances, aim to develop and retain production value added chains” that are protected from outside competition by ensuring that their rules and standards become the norm. The NTI document went on to say that countries and companies which are outside these blocks/alliances and their value added chains cannot break into them because the technological standards have already been set to disadvantage them.
Thus, according to the document, the NTI was given the goal of making Russia “one of the ‘big three’ major technological states by 2035, and have its own high-tech specialization in the global chain of creating additional value”. In order to achieve this, Russia will need is own block/alliance or participate in others in such a way that it becomes a leader in “developing and confirming international technical standards”.
President Putin, in his address to the St. Petersburg economic forum on 17 June 2016, said: “Today we see attempts to secure or even monopolize the benefits of new generation technologies. This, I think, is the motive behind the creation of restricted areas with regulatory barriers to reduce the cross-flow of breakthrough technologies to other regions of the world with fairly tight control over cooperation chains for maximum gain from technological advances.”
Then US Secretary of State played-up the security aspects of such economic-trade blocs: “I have worked from day one to emphasize that foreign policy is economic policy and economic policy is foreign policy. Without a doubt, these trade agreements are at the center of defending our strategic interests, deepening our diplomatic relationships, strengthening our national security, and reinforcing our leadership across the globe.” “Even as we seek to complete TTIP and strengthen our bonds across one ocean, we know that our future prosperity and security will also rest on America’s role as a Pacific power. Central to that effort is the adoption of (Transpacific Partnership) TPP.”
However, given the prospective Brexit and the rise of Trump as an economic nationalist, such blocs seemed very unlikely when I first wrote about the NTI in 2016. Since then, Trump’s strident America first approach to the economy, abandonment of TPP, and lack of interest in an US role in international security issues would seem to have confirmed my earlier view.
Nevertheless, “Western” concern about advances in Chinese technology, the way it is being acquired (allegations of IP theft and heavy-handed treatment of companies seeking to invest in China), and the way it is being used (Xinjiang) seems to be leading to at least partial technology blocs — with the possibility of broadening to aspects of international trade and investment.
Whereas the NTI idea of economic / trade blocs was largely based on the political and economic consequences of growing global value-added chains in high-tech and Russia’s need to be part of this trend, we may now be in a situation where such economic / trade blocs will be formed by a perceived urgent need to tear existing high-tech value-added chains apart in the name of national security and create new ones. National Security is now very much in the driver’s seat!
Putin’s point about “attempts to secure or even monopolize the benefits of new generation technologies” remains valid, as does the issue — in a different form — of what bloc if any can or should Russia join.
Concerns about the security aspects of Huawei telecommunication equipment in the UK led to the establishment of the Huawei Cyber Security Evaluation Centre” (HCSEC). While Huawei pays the costs of this centre, it has no control over its operation. A HCSEC Oversight Board was established in 2014. Its fourth report in 2018 concluded that:
“5.2 The key conclusions from the Board’s fourth year of work are:
It is evident that HCSEC continues to provide unique, world-class cyber security expertise and technical assurance of sufficient scope and quality as to be appropriate for the current stage in the assurance framework around Huawei in the UK ii. However, Huawei’s processes continue to fall short of industry good practice and make it difficult to provide long term assurance. The lack of progress in remediating these is disappointing. NCSC and Huawei are working with the network operators to develop a long-term solution, regarding the lack of lifecycle management around third party components, a new strategic risk to the UK telecommunications networks. Significant work will be required to remediate this issue and provide interim risk management.
iii. The HCSEC Oversight Board is assured that the Ernst & Young Audit Report provides important, external reassurance that the arrangements for HCSEC’s operational independence from Huawei Headquarters is operating robustly and effectively, and in a manner consistent with the 2010 arrangements between the Government and the company. The issue identified was rated as low risk and two further advisory issues were identified.
5.3 Overall therefore, the Oversight Board has concluded that in the year 2017-2018, HCSEC fulfilled its obligations in respect of the provision of security and engineering assurance artefacts to the NCSC and the UK operators as part of the strategy to manage risks to UK national security from Huawei’s involvement in the UK’s critical networks. However, the execution of the strategy exposed a number of risks which will need significant additional work and management. The Oversight Board will need to pay attention to these issues.”
The qualified nature of the HCSEC reports has led to come commentators to offer strong support to the Australian bans on Huawei participation in Australian 5G. This is particularly the case with the ASPI International Cyber Policy Centre. The Centre’s Tom Uren says that the contents of the four HCSEC oversight board annual reports (2015, 2016, 2017 and 2018) “show that it is very difficult indeed” to “assess products to make sure they won’t be used to spy on us”.
However, the underlying issue is broader than Huawei and 5G. A 2018 book by Olav Lysne concludes that:
“Industrialized nation states are currently facing an almost impossible dilemma. On one hand, the critical functions of their societies, such as the water supply, the power supply, transportation, healthcare, and phone and messaging services, are built on top of a huge distributed digital infrastructure. On the other hand, equipment for the same infrastructure is made of components constructed in countries or by companies that are inherently not trusted. In this book, we have demonstrated that verifying the functionality of these components is not feasible given the current state of the art. The security implications of this are enormous. The critical functions of society mentioned above are so instrumental to our well-being that threats to their integrity also threaten the integrity of entire nations. The procurement of electronic equipment for national infrastructures therefore represents serious exposure to risk and decisions on whom to buy equipment from should be treated accordingly. The problem also has an industrial dimension, in that companies fearing industrial espionage or sabotage should be cautious in choosing from whom to buy electronic components and equipment. Honest providers of equipment and components see this problem from another angle. Large international companies have been shut out of entire markets because of allegations that their equipment cannot be trusted. For them, the problem is stated differently: How can they prove that the equipment they sell does not have hidden malicious functionality? We have seen throughout the chapters of this book that we are currently far from being able to solve the problem from that angle as well. This observation implies that our problem is not only a question of security but also a question of impediments to free trade. Although difﬁcult, the question of how to build veriﬁable trust in electronic equipment remains important and its importance shows every sign of growing.”
The basic technical reason for Australia banning Huawei has been put forward by the head of its Signals Directorate: “5G is not just fast data, it is also high-density connection of devices – human to human, human to machine and machine to machine – and finally it is much lower signal latency or speed of response. Historically, we have protected the sensitive information and functions at the core of our telecommunications networks by confining our high-risk vendors to the edge of our networks. But the distinction between core and edge collapses in 5G networks. That means that a potential threat anywhere in the network will be a threat to the whole network. In consultation with operators and vendors, we worked hard this year to see if there were ways to protect our 5G networks if high-risk vendor equipment was present anywhere in these networks. At the end of this process, my advice was to exclude high-risk vendors from the entirety of evolving 5G networks.”
The technical issues of 5G are very complex and there is no universal agreement in any country about the introduction and operation of networks. International technical standards are still being developed. Initially, many basic 5G features will be delivered in most cases by upgraded 4G infrastructure, but getting the most out of 5G – in terms of speed and capacity – will require significant new investment in telecommunications infrastructure.
A controversial US proposal to build secure 5G as a “single, inherently protected, information transportation super highway” was produced by members of the US security establishment in early 2018 – and found its way into the public arena. The document says that presently “data traverses cyberspace through a patchwork transport layer constructed through an evolutionary process as technology matured”. “Measures to secure and protect data and information result in an ‘overhead’ that affects network performance – they reduce throughput, increase latency, and result in an inherently and inefficient and unreliable construct. Additionally, the framework under which access and services are allocated is suboptimal, yielding incomplete and redundant networks. Without a concerted effort to reframe and reimagine the information space, America will continue on the same trajectory – chasing cyber adversaries in an information environment where security is scarce.”
It goes on to say that “the advent of ‘secure’ network technology and the move to 5G presents an opportunity to create a completely new framework.” “Whoever leads in technology and market share for 5G development will have a tremendous advantage towards ushering in the massive Internet of Things, machine learning, AI, and thus the commanding heights of the information domain.” “The transformative nature of 5G is its ability to enable the massive Internet of Things.” “Using efforts like China Manufacturing 2025 (CM2025) and the 13th Five Year Plan, China has assembled the basic components required for winning the AI arms race.”
While the proposal for a such extensive government involvement in US 5G infrastructure seems to have been rejected, it does indicate the level of attention being focused on the issue.
The Russian Ministry of Communications is advocating that private Russian telecommunications companies share much of the 5G infrastructure, which may to some degree allow a more secure network to be built. However, this does not solve the problem of where to source the equipment.
What should Russia do if the concerns about Huawei and Chinese technology more generally start to lead to the formation of an anti-Chinese technology based economic bloc?
There is little reason to believe Russia will be any better than Western countries in evaluating the security related aspects of Chinese technology, and there would be a strong case for Russia to follow the lead of Australia, the UK, USA etc. However, there would be several arguments against such a course of action.
Firstly, Russia will not want to jeopardize its present good political relationship with China. Apart from energy sales the economic relationship between Russia and China is not strong, however geography means that Russia has a huge stake in the political relationship.
Secondly, if it is possible for Huawei and other Chinese companies to do the harmful things that are claimed then presumably non-Chinese suppliers could also do the same to Russia at the request (or demand) of their country’s security agencies. While Western commentators make much of China’s June 2017 National Intelligence Law that obliges “all organizations and citizens” to “support, cooperate and collaborate in national intelligence work”, Western high-tech companies would almost certainly do the same when it comes to Russia given its very poor image in those countries and the perceived Russian threat to those countries.
Thirdly, at a purely technical level there is nothing to suggest that Russia could build 5G infrastructure without importing most of the equipment. While Russia has a solid reputation in the software field, Russian manufacturing capacity and quality is not high. Russia’s efforts to promote the high-tech sector from the top have not been particularly successful. Even China is very dependent on crucial imported 5G components.
Fourthly, my September 2016 report on the NTI suggested that Russia needed to put more emphasis on using available digital technology rather than trying to develop new leading-edge products. In early 2017, the Russian government announced its “Strategy for the Development of the Information Society in the Russian Federation for 2017-2030” While much can be done using existing 4G infrastructure, a good 5G network will be necessary well before 2030 to maximize the benefits of the strategy as well as take best advantage of any NTI successes.
As things now stand, Russia is likely to use Chinese Huawei (and other Chinese) hardware while attempting to ensure that Russian software is used wherever possible. However, as already noted, this will be no easy task.
It is difficult to avoid the conclusion that when it comes to 5G and national security, Russia is between a rock and a hard-place. It has neither the 5G infrastructure manufacturing capacity of the US and China, nor any real friends that are capable of helping it.
Central Banks Becoming Leaders in Blockchain Experimentation
Although central banks are among the most cautious institutions in the world, they are, perhaps surprisingly, among the first to implement and experiment with blockchain technology. Central banks have been quietly researching its possibilities since 2014. Over the past two years, the beginning of a new wave has emerged as more central banks launch large-scale pilots and research efforts, including rapid and complete cross-border interbank securities.
The Blockchain and Distributed Ledger Technology team at the World Economic Forum interviewed dozens of central bank researchers and analysed more than 60 reports on past and current research efforts. The findings were released today in a white paper, Central Banks and Distributed Ledger Technology: How are Central Banks Exploring Blockchain Today?
“As the blockchain hype cools, we are starting to see the real use cases for blockchain technology take the spotlight,” said Ashley Lannquist, Blockchain Project Lead at the World Economic Forum. “Central bank activities with blockchain and distributed ledger technology are not always well known or communicated. As a result, there is much speculation and misunderstanding about objectives and the state of research. Dozens of central banks around the world are actively investigating whether blockchain can help solve long-standing challenges such as banking and payments system efficiency, payments security and resilience, as well as financial inclusion.”
It is not widely known, for instance, that the Bank of France has fully replaced its centralized process for the provisioning and sharing of SEPA Credit Identifiers (SCIs) with a decentralized, blockchain-based solution. SEPA, or Single Euro Payments Area, is a payment scheme created by the European Union and managed on a country-by-country basis for facilitating efficient and secure cross-border retail debit and card payments across European countries. The solution is a private deployment of the Ethereum blockchain network and has been in use since December 2017. It has enabled greater time efficiency, process auditability and disaster recovery.
The fact that dozens of central banks are exploring, and in some cases implementing, blockchain technology is significant, according to the white paper. It is an early indicator of the potential use of this emerging technology across financial and monetary systems. “Central banks play one of the most critical roles in the global economy, and their decisions about implementing distributed ledger and digital currency technologies in the future can have far-reaching implications for economies,” Lannquist said.
Top 10 central bank use cases
Following interviews and analysis, how central banks are experimenting with blockchain can be highlighted by 10 top use cases.
Retail central bank digital currency (CBDC) – A substitute or complement for cash and an alternative to traditional bank deposits. A central-bank-issued digital currency can be operated and settled in a peer-to-peer and decentralized manner, widely available for consumer use. Central banks from several countries are experimenting, including those from the the Eastern Caribbean, Sweden, Uruguay, the Bahamas and Cambodia.
Wholesale central bank digital currency (CBDC) – This kind of digital currency would only be available for commercial banks and clearing houses to use the wholesale interbank market.Central bank-issued digital currency would be operated and settled in a peer-to-peer and decentralized manner. Central banks from several countries are experimenting, including those from South Africa, Canada, Japan, Thailand, Saudi Arabia, Singapore and Cambodia.
Interbank securities settlement – A focused application of blockchain technology, sometimes involving CBDC, enabling the rapid interbank clearing and settlement of securities for cash. This can achieve “delivery versus payment” interbank systems where two parties trading an asset, such as a security for cash, can conduct the payment for and delivery of the asset simultaneously. Central banks exploring this include the Bank of Japan, Monetary Authority of Singapore, Bank of England and Bank of Canada.
Payment system resiliency and contingency – The use of distributed ledger technology in a primary or back-up domestic interbank payment and settlement system to provide safety and continuity in case of threats, including technical or network failure, natural disaster, cybercrime and others. Often, this use case is coupled with others as part of the set of benefits that a distributed ledger technology implementation could potentially offer. Central banks exploring this include the Central Bank of Brazil and Eastern Caribbean Central Bank.
Bond issuance and lifecycle management – The use of distributed ledger technology in the bond auction, issuance or other life-cycle processes to reduce costs and increase efficiency. This may be applied to bonds issued and managed by sovereign states, international organizations or government agencies. Central banks or government regulators could be “observer nodes” to monitor activity where relevant. Early implementation is being conducted by the World Bank with their 2018 “bond-i” project.
Know-your-customer (KYC) and anti-money-laundering (AML) – Digital KYC/AML processes that leverage distributed ledger technology to track and share relevant customer payment and identity information to streamline processes. This may connect to a digital national identity platform or plug into pre-existing e-KYC or AML systems. Central banks exploring this include the Hong Kong Monetary Authority.
Information exchange and data sharing – The use of distributed or decentralized databases to create alternative systems for information and data sharing between or within related government or private sector institutions. Central banks exploring include the Central Bank of Brazil.
Trade finance – The employment of a decentralized database and functionality to enable faster, more efficient and more inclusive trade financing. Improves on today’s trade finance processes, which are often paper-based, labour-intensive and time-intensive. Customer information and transaction histories are shared between participants in the decentralized database while maintaining privacy and confidentiality where needed. Central banks exploring this include the Hong Kong Monetary Authority.
Cash money supply chain – The use of distributed ledger technology for issuing, tracking and managing the delivery and movement of cash from production facilities to the central bank and commercial bank branches; could include the ordering, depositing or movement of funds, and could simplify regulatory reporting. Central banks exploring this include the Eastern Caribbean Central Bank.
Customer SEPA Creditor Identifier (SCI) provisioning – Blockchain-based decentralized sharing repository for SEPA credit identifiers managed by the central bank and commercial banks in the SEPA debiting scheme. This is a faster, streamlined and decentralized system for identity provisioning and sharing. It can replace pre-existing manual and centralized processes that are time- and resource-intensive, as seen in the Bank of France’s Project MADRE implementation.
Emerging economies may benefit most: Cambodia, Thailand and South Africa and others experimenting
The National Bank of Cambodia will be one of the first countries to deploy blockchain technology in its national payments system for use by consumers and commercial banks. It is implementing blockchain technology in the second half of 2019 as an experiment to support financial inclusion and greater banking system efficiency.
The Bank of Thailand and the South African Reserve Bank, among others, are experimenting with CBDC in large-scale pilots for interbank payment and settlement efficiency. The Eastern Caribbean Central Bank is exploring the suitability of distributed ledger technology (DLT) to advance multiple goals, from financial inclusion and payments efficiency to payment system resilience against storms and hurricanes.
“Over the next four years, we should expect to see many central banks decide whether they will use blockchain and distributed ledger technologies to improve their processes and economic welfare,” Lannquist said. “Given the systemic importance of central bank processes, and the relative freshness of blockchain technology, banks must carefully consider all known and unknown risks to implementation.”
How Nuclear Techniques Help Feed China
With 19% of the world’s population but only 7% of its arable land, China is in a bind: how to feed its growing and increasingly affluent population while protecting its natural resources. The country’s agricultural scientists have made growing use of nuclear and isotopic techniques in crop production over the last decades. In cooperation with the IAEA and the Food and Agriculture Organization of the United Nations (FAO), they are now helping experts from Asia and beyond in the development of new crop varieties, using irradiation.
While in many countries, nuclear research in agriculture is carried out by nuclear agencies that work independently from the country’s agriculture research establishment, in China the use of nuclear techniques in agriculture is integrated into the work of the Chinese Academy of Agricultural Sciences (CAAS) and provincial academies of agricultural sciences. This ensures that the findings are put to use immediately.
And indeed, the second most widely used wheat mutant variety in China, Luyuan 502, was developed by CAAS’s Institute of Crop Sciences and the Institute of Shandong Academy of Agricultural Sciences, using space-induced mutation breeding (see Space-induced mutation breeding). It has a yield that is 11% higher than the traditional variety and is also more tolerant to drought and main diseases, said Luxiang Liu, Deputy Director General of the Institute. It has been planted on over 3.6 million hectares – almost as large as Switzerland. It is one of 11 wheat varieties developed for improved salt and drought tolerance, grain quality and yield, Mr Liu said.
Through close cooperation with the IAEA and FAO, China has released over 1,000 mutant crop varieties in the past 60 years, and varieties developed in China account for a fourth of mutants listed currently in the IAEA/FAO’s database of mutant varieties produced worldwide, said Sobhana Sivasankar, Head of the Plant Breeding and Genetics Section at the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture. The new mutation induction and high-throughput mutant selection approaches established at the Institute serve as a model to researchers from around the world, she added.
The Institute uses heavy ion beam accelerators, cosmic rays and gamma rays along with chemicals to induce mutations in a wide variety of crops, including wheat, rice, maize, soybean and vegetables. “Nuclear techniques are at the heart of our work, fully integrated into the development of plant varieties for the improvement of food security,” Liu said.
The Institute has also become a key contributor to the IAEA technical cooperation programme over the years: more than 150 plant breeders from over 30 countries have participated in training courses and benefited from fellowships at CAAS.
Indonesia’s nuclear agency, BATAN, and CAAS are looking for ways to collaborate on plant mutation breeding and Indonesian researchers are looking for ways to learn from China’s experience, said Totti Tjiptosumirat, Head of BATAN’s Center for Isotopes and Radiation Application. “Active dissemination and promotion of China’s activities in plant mutation breeding would benefit agricultural research across Asia,” he said.
From food safety to authenticity
Several of CAAS’ other institutes use nuclear-related and isotopic techniques in their research and development work and participate in several IAEA technical cooperation and coordinated research projects. The Institute of Quality Standards and Testing Technology for Agro-Products has developed a protocol to detect fake honey, using isotopic analysis. A large amount of what is sold in China as honey is estimated to be produced synthetically in labs rather than by bees in hives, so this has been an important tool in cracking down on fraudsters, said Professor Chen Gang, who leads the research work using isotopic techniques at the Institute. A programme is also in place to trace the geographical origin of beef using stable isotopes, he added.
The Institute uses isotopic techniques to test the safety and to verify the authenticity of milk and dairy products – work that was the outcome of IAEA technical coordinated research and cooperation projects that lasted from 2013 to 2018. “After a few years of support, we are now fully self-sufficient,” Mr Gang said.
Improving nutrition efficiency
Various CAAS institutes use stable isotopes to study the absorption, transfer and metabolism of nutrients in animals. The results are used to optimize feed composition and feeding schedules. Isotope tracing offers higher sensitivity than conventional analytical methods, and this is particularly advantageous when studying the absorption of micronutrients, vitamins, hormones and drugs, said Dengpan Bu, Professor at the Institute of Animal Science.
While China has perfected the use of many nuclear techniques, in several areas it is looking to the IAEA and the FAO for support: the country’s dairy industry is dogged by the low protein absorption rate of dairy cows. Less than half of the protein in animal feed is used by the ruminants, the rest ends up in their manure and urine. “This is wasteful for the farmer and the high nitrogen content in the manure hurts the environment,” Mr Bu said. The use of isotopes to trace nitrogen as it travels from feed through the animal’s body would help improve nitrogen efficiency by making the necessary adjustments to the composition of the feed. This will be particularly important as dairy consumption, currently at a third of global average per person, continues to rise. “We are looking for international expertise, through the IAEA and the FAO, to help us tackle this problem.”
When neuroscience meets AI: What does the future of learning look like?
Meet Dr. Nandini Chatterjee Singh, a cognitive neuroscientist at UNESCO MGIEP (Mahatma Gandhi Institute of Education for Peace and Sustainable Development) where she has been leading the development of a new framework for socio-emotional learning. MGIEP focuses on mainstreaming socio-emotional learning in education systems and innovating digital pedagogies.
Dr. Singh answered five questions on the convergence of neuroscience and Artificial Intelligence in learning, ahead of the International Congress on Cognitive Science in Schools where she will be speaking this week.
What are the links between neuroscience and Artificial Intelligence when it comes to learning?
The focus of both neuroscience and AI is to understand how the brain works and thus predict behaviour. And the better we understand the brain, the better designs we can create for AI algorithms. When it comes to learning, the neuroscience – AI partnership can be synergistic. A good understanding of a particular learning process by neuroscience can be used to inform the design of that process for AI. Similarly, if AI can find patterns from large data sets and get a learning model, neuroscience can conduct experiments to confirm it.
Secondly, when neuroscience provides learning behaviours to AI, these behaviours can be translated into digital interactions, which in turn are used by AI to look at learning patterns across large numbers of children worldwide. The power of AI is that it can scale this to large numbers. AI can track and search through massive amounts of data to see how that learning happens, and when required, identify when learning is different or goes off track.
A third feature is that of individualized learning. We increasingly also know that learning has a strong individual component. Yet our classrooms are structured to provide common learning to all children. Sometimes these individual differences become crucial to bring out the best in children, which is when we might tailor learning. Neuroscience research on individual differences has shown that detailed information on that individual can reveal a wealth of information about their learning patterns. However, this is extremely cost and labour intensive. Yet, this detailed learning from neuroscience can be provided to AI in order to scale. AI can collect extensive detailed data at the personal level, to design a path to learning for that child. Thus, what neuroscience can study in small groups, AI can implement in large populations. If we are to ensure a world where every child achieves full potential, such personalized learning offers a great promise.
How do we create a structure around AI to ensure learning standards globally?
One thing AI capitalizes on and constantly relies on is large volumes of data. AI algorithms perform better if they are being fed by continuous distributed data. We need to keep in mind that humans are the ones designing these algorithms. This means that the algorithms will only do as well as the data that they have been trained on. Ensuring that we have access to large amounts of data that comes from various situations of learning is crucial. What sometimes becomes an issue for AI algorithms is that most of the training data has been selected from one particular kind of population. This means that the diversity in the forms of learning is missing from the system.
To return to reading and literacy as an example, in neuroscience, a large part of our research and understanding of how the brain learns to read has come from individuals learning to read English and alphabetic languages. However, globally, billions of people speak or read non-alphabetic languages and scripts that are visually complex, which are not really reflected in this research. Our understanding is built on one particular system that does not have enough diversity.
Therefore, it is important that AI algorithms be tested in varied environments around the world where there are differences in culture. This will create more robust learning models that are able to meet diverse learning requirements and cater to every kind of learner from across the world. If we are able to do that, then we can predict what the learning trajectory will look like for children anywhere.
Human beings have similarities in the way they learn, but pedagogies vary across different situations. In addition, those differences must be reflected in the data provided. The results would be much more pertinent if we are able to capture and reflect those differences in the data. This will help us improve the learning of AI, and ultimately understand how the brain works. We would then be better suited to leverage the universal principles of learning that are being used across the world and effects that are cultural in nature. That is also something that we want to hold on to and capitalize on in trying to help children. People designing AI algorithms so far have not given a lot of attention to this, but they are now beginning to consider it in many places across the world.
How do you see AI’s role in inclusive education today, especially in the context of migration?
Societies have become multicultural in nature. If you go to a typical classroom in many countries, you will find children from diverse cultures sitting in the same learning space. Learning has to be able to meet a variety of needs and must become more inclusive and reflect cultural diversity. Innovative pedagogy such as games, interactive sessions and real-life situations are key because they test learning capabilities focused on skills that children should acquire. AI relies on digital interactions to understand learning and that comes from assessing skills and behaviours. We now recognize that what we need to empower our children with are skills and behaviours – not necessarily tons of information.
Digital pedagogies like interactive games are among the ones emerging rapidly to assess children’s skills. They are powerful because they can be used in multicultural environments and can assess different competencies. They are not necessarily tied to a specific language or curricula but are rather performance-based. How do you assess children for collaboration in a classroom? In the context of migration and 21st century skills, these are necessary abilities and digital games provide a medium to assess these in education. When such interactive games are played by children across the world, they provide digital interactions to AI. AI might discover new patterns and ways to collaborate since children have ways of doing things that are often out of the box. A skills-based approach can be applied anywhere, whether it is in a classroom in India, France or Kenya. In contrast, curriculum-based methods are context-specific and show extensive cultural variation.
What are the risks and the challenges?
Data protection and security is of course still a huge issue and is the biggest challenge in this sphere. We have to ensure that children are never at risk of exposure and that the data is not misused in any way. This is something that needs more global attention and backing.
Another crucial point is that learning assessments should not be restricted to just one domain. There are multiple ways, and time and space to learn. Learning is continuous in nature and should be able to be adapted to the child’s needs at that particular point. The assessment should also be continuous in order to get a full picture of the improvement that the child is demonstrating. If there is no improvement, then we can provide interventions to help and find out why learning is not happening. From what we know from neuroscience, the earlier you can provide intervention, the better is the chance of the child to be able to change and adapt. The ability of the brain to learn and change is much easier and faster in childhood compared to adulthood.
Yet, we want to be cautious about the conclusions we draw about how to intervene with children. Poor academic performance might have a social or emotional reason.
Thus, learning today needs to be multi-dimensional. Along with academic competencies, social and emotional skills also need to be assessed. If this information is used wisely, it can provide a lot of insight about the child’s academic and emotional well-being. Based on the combination of the two, the right intervention can be provided. Unless multiple assessments all converge on the same result, the child’s learning abilities should not be labeled. AI gives a great opportunity to conduct multi-skills assessments, rather than just one. And that is something that we should leverage, rather than abandon. The standards for the baselines for the algorithms must be properly taken into consideration for any type of assessment. They must come from a large quantity of distributed data in order to provide more accurate results. That is something that we should not compromise under any condition.
How is the teaching community responding to this new way of learning and assessing?
There are teachers who worry about the future of learning but that is also because they do not necessarily have the full picture. People working and promoting the use of AI in learning must play a crucial role in telling teachers that they will not be obsolete. Teachers will be more empowered and be able to meet the needs of every kind of learner in their classrooms. The ideal world would be to have one teacher per child but that is of course impossible. AI is a tool to guide teachers when it comes to finding the right intervention for a student that might be struggling to learn. That intervention comes from data that has been checked for bias and diversity and does not use ‘a one size fits all ‘approach and therefore teachers can be more certain that it will fit the needs of the child. AI gives the opportunity for the teacher to tailor learning for the child. In addition, we do not really know all the different kinds of learning. Sometimes we have to be prepared to learn from children themselves. Children can give us insights into the different ways that learning actually happens, and teachers should be able apply them back into the classroom. Teachers are extremely powerful individuals who are able to shape the brains of so many children. If they are doing a good job, they are making individuals for life.
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