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.
Digitally shaping a greener world
Women were not allowed on map-making ship voyages until the 1960s—it was believed that they would bring bad luck. Spanish nuns made maps in the 10th century.
The first A-Z street map of London was created after one woman got lost on her way home from a party, then woke up every day at 5 a.m. to chart the city’s 23,000 streets.
As it turns out, women have always contributed to the drawing of maps despite hurdles.
This puts Molly Burhans, founder of GoodLands, in good company. For the first time in history, she is setting out to digitally map the land assets of one of the world’s largest land-owners—the Catholic Church.
The journey has been spiritual. Instead of becoming a nun, she decided to pursue digital mapping instead. “Our work is grounded in science, driven by design and inspired by values of stewardship and charity,” she explains.
It all started when a course in biological illustration turned into a fascination with how everything fits together.
“You can’t do surgery unless you’ve studied human anatomy—and you can’t really do sound environmental work unless you’ve mapped the environment and landscape, and can visualize it,” she explains.
She was introduced to digital mapping by Dana Tomlin, the originator or Map Algebra and Geographic Information Systems professor at the University of Pennsylvania and Yale University. When she visited the Vatican in 2016, it got her thinking.
“The Vatican has the most fantastic maps I’ve ever seen,” she said. “White, gold, platinum frescoes flanked the doors. I thought they must have the most incredible land datasets anywhere in the world.”
The Vatican is the smallest state in the world, and its biggest land owner. There are 250,000 Catholic-affiliated parishes, orphanages, community centers and retreat monasteries around the world, reaching an estimated 57.6 million people globally.
It is also the world’s largest non-government health care provider. The Pontifical Council for the Pastoral Care of Health Care workers estimates that around 26 per cent of healthcare facilities are operated by the Roman Catholic Church.
Iyad Abumoghli, Principal Coordinator of UN Environment Programme’s Faith for Earth Initiative, said:
“Globally, faith-based organizations own 8 per cent of habitable land on the surface of the earth and 5 per cent of all commercial forests. There are around 37 million churches and 3.6 million mosques around the world.
“Burhans’ work supports UNEP’s Faith for Earth Initiative to harness the socio-economic power of faith-based organizations, where preaching meets practice.
“Mapping faith-owned assets will contribute to strategically employ faith values in managing them, ultimately leading to fighting climate change and curbing ecosystem degradation.”
Fear of the unknown
Burhans reflects: “Why not leverage this network for environmental good?”
But then the hurdle hit. The data wasn’t digital. In fact—it wasn’t even there.
“None of the land had been digitally mapped. I was surprised – this was bigger than I’d realized. We can’t manage property without foundational data—never mind ecosystem restoration. So, I just kept going to find the data.”
When she confirmed that data did not exist, Burhans asked the Holy See for permission to create the first comprehensive global digital data map of the Catholic Church’s footprint and people in history, working with a large team at mapping software company Esri, as Chief Cartographer.
Her mission: to help faith-based communities, such as religious orders, dioceses, and the Vatican to first understand what land assets they own. Next, figure out how to leverage those assets for ecosystem restoration on a scale parallel to its massive global health network.
The power of knowing
For Burhans, maps represent the power to shape our world for better health and environmental protection. “We dare to use land for environmental good. I can’t emphasize how important our surroundings and environment are,” she notes.
“Maps are just the tool, allowing us to capture complex information, from biodiversity to soil type, all in one place. If a picture is worth a thousand words, then a map is worth a million.”
“We can map where ecological failure might trigger heavy migration. Or, where sea level rise might force poor communities to move. We can see where more trees could cool hot cities; where green spaces could bring health benefits in areas with high respiratory problems.”
For Burhans, the potential of a large data hub capturing all this information across the church’s land portfolio is exciting—and unprecedented. It also has implications for all land owners and governments around the world.
Her team maps environmental, social and financial factors of a property portfolio. Centralizing information in one digital hub across sectors—health care, education, relief—could save tens of millions each year, she reflects.
She is also asking bigger questions: “How will artificial intelligence transform our world? How can we leverage land and religion to become the solution to our crises? We must be at the forefront of these issues.”
Mapping the church’s global footprint
Honing big data for environmental restoration is part of Burhans’ vision. Some of this is technical: bringing the Catholic Church into the digital area: “With relevancy, with the right information to roll out safety.”
But the vision is also about people. “We want to help people realize that mapping assets is vital to manage them responsibly. We cannot help the church improve its footprint if we don’t know what is has.”
“We all have different talents and gifts. Mine lean towards creating new technology and applying it to make land work for the greater good. That’s my vocation: to make sure that’s done—and done with integrity.”
Five New Technologies that Can Prevent Everything from Fraud to Future Financial Shocks
A new white paper, The Next Generation of Data Sharing in Financial Services, from the World Economic Forum has identified new technologies that banks and other financial institutions can implement for privacy-protected data-sharing between institutions. This data-sharing will enable broad analysis, which can be used to identify industry-wide risks and could even prevent future financial shocks.
Beyond system-wide benefits, these newly identified technologies, coined “privacy-enhancing techniques” can also use improved data-sharing to prevent fraud, offer financial advice, and much more. Privacy-enhancing techniques lessen the tensions underlying data-sharing. Instead of threatening customer privacy, this new wave of technology not only protects it but also enhances industry collaboration.
These five technologies include:
While new and novel for use in financial services, these technologies have existed within laboratories for years and are now ready for use in the real world of banking and other financial services. If harnessed, these tools could usher in a new, more collaborative, era of the sector on matters related to risk and product development.
“With advancing privacy-enhancing technologies, financial services have the ability to work more closely together on a range of important challenges and opportunities, from combating illicit financial transactions to identifying material risk exposures across institutions, to developing more personalized financial advice and products,” says Matthew Blake, Head of Financial and Monetary System Initiatives, World Economic Forum. “Privacy-enhancing techniques open a range of possibilities for enhanced risk management and financial innovation with benefits for customers, regulators and financial institutions alike.”
These technologies, used separately or in conjunction, greatly reduce the risks associated with data sharing and have the potential to fundamentally redefine the dynamics of data sharing in financial services. Opportunities from these technologies include the ability to:
· Better detect and prevent fraudulent activity: Federated analysis could be used to create shared fraud detection and prevention models across institutions without sharing the personally sensitive information about specific customers
· Identify system-wide risks and prevent financial crises: Secure multi-party computation could be used to conduct aggregate analysis on financial institutions’ risk exposures without breaching their institutional competitive secrets, allowing for an advance warning on systemic risks and exposures such as those that led to the 2008 financial crisis
· Enable new forms of personalized digital advice: Leveraging differential privacy in the analysis of transactions across an institution’s customer base could enable sophisticated and specific “people like you” recommendations without exposing individual customers’ spending habits
· And more, as explored in The Next Generation of Data Sharing in Financial Services
One of the key learnings from the financial crisis was that system-wide risk exposures were not properly quantified and understood by enterprises as well as financial supervisors. This was partly due to inadequate management information systems that did a poor job of aggregating risk exposures across institutions as well as too narrow a focus by supervisors on the risk of individual financial firms rather than the interconnections between institutions and the broader system.
Competitive dynamics also played a part; it is perilous for a financial institution to make explicit its risk exposures because other actors may take advantage and profit from that level of transparency. Enter privacy-enhancing techniques, which make sharing granular information across institutions possible – allowing for transparency without unveiling too much, presenting new possibilities for collaboration between institutions, supervisors and customers.
“It is important to note that these technologies are not a magic wand. Using them requires financial institutions to address surrounding issues such as poor data quality, legal uncertainties and siloed data infrastructures,” says Bob Contri, Principal, Deloitte United States; Global Financial Services Industry Leader. “However, addressing these roadblocks and using privacy-enhancing techniques can propel the financial services industry into a new era of collaboration and value delivery.”
According to the World Economic Forum, financial services executives should take a concerted look at these new techniques and where they might best be deployed. Bringing these technologies into practice will require a degree of experimentation and technological expertise. Nonetheless, the benefits of widescale adoption are clear and speak to greater alignment and action among key stakeholders on issues of systemic importance.
‘Digital divide’ will worsen inequalities, without better global cooperation
Inequality will worsen unless the so-called “digital divide” – the gap between under-connected and highly digitalized countries – is not addressed, warns a new report released on Wednesday by the UN trade body, UNCTAD.
The first-ever Digital Economy Report outlines enormous potential gains from the increasingly inter-connected global economy, but calls for “concerted global efforts to spread the wealth potential to the many people who currently reap little benefit from it.
US and China pull ahead, Africa and Latin America trail behind
The United States and China create the vast majority of wealth in the digital economy, the study reveals, and the two countries account for 75% of all patents related to blockchain technologies, 50% of global spending on the “Internet of Things” (IoT), more than 75% of the cloud computing market, and as much as 90% per cent of the market capitalization value of the world’s 70 largest digital platform companies.
The rest of the world, particularly countries in Africa and Latin America, are trailing considerably behind, and this trajectory is likely to continue, further contributing to rising inequality, said UN Secretary-General António Guterres, in a foreword to the report.
“We must work to close the digital divide” he writes, “where more than half the world has limited, or no access to the Internet. Inclusivity is essential to building a digital economy that delivers for all”.
Massive increase in data on the horizon
Despite the impact that digital data has already had, the world is still in the early days of the data-driven economy, according to the study, which forecasts a dramatic surge in data traffic in the next few years.
This reflects the growth in the number of people using the Internet, and the uptake of frontier technologies such as blockchain, data analytics, artificial intelligence, 3D printing, IoT, automation, robotics and cloud computing.
Platforms to rule the world
Wealth and power in the digital sphere are increasingly being held by a small number of so-called “super platforms”, comprising the seven global brands Microsoft, Apple, Amazon, Google, Facebook, Tencent and Alibaba.
Between them, these companies account for two-thirds of the total market value of the top 70 platforms: in China, WeChat, owned by Tencent, and AliPay, an Alibaba company, have captured virtually the entire Chinese mobile payment market between them. Google accounts for some 90 per cent of the global Internet search market, and Facebook is the top social media platform in more than 90 per cent of countries.
The reports shows that these companies are competing aggressively to stay on top, acquiring competitors, expanding into new services, lobbying policy-makers, and establishing strategic partnerships with leading multinationals in traditional sectors.
UNCTAD warns that the dominance of these platforms is leading to a concentration and consolidation of digital value, rather than reducing inequalities between and within countries, with developing countries at the bottom of the pile. The report calls for a rethink, that will bring about a fairer distribution of the gains from the digital economy.
The role of government in levelling the playing field
Governments can play a critical role in defining the rules of the game, explains Mukhisa Kituyi, Secretary-General of UNCTAD , by adapting existing laws, and passing new ones in many areas:
“A smart embrace of new technologies, enhanced partnerships and greater intellectual leadership are needed to redefine digital development strategies and the future contours of globalization”, he wrote.
The report calls for greater international collaboration on issues associated with the digital economy, with the full involvement of developing countries, on issues such as competition, taxation, cross-border data flows, intellectual property, trade and employment policies.
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