The Philippine Department of Science and Technology (DOST) launched nine new research projects on artificial intelligence (AI) that are intended to aid various sectors in the country, from agriculture to the education sector.
In a virtual launch, the DOST’s Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD) unveiled the AI projects to be undertaken by the DOST-Advanced Technology Science Institute (ASTI), along with various universities in the country.
First is the Autonomous Societally Inspired Mission Oriented Vehicles (ASIMOV) Programme, composed of two-component projects, to be handle by ASTI and a university based in Mindanao. It will take on the challenge of developing AI-enhanced, mission-driven robots working autonomously or with humans to help address society’s needs. In its initial phase, it will focus on laying the groundwork by developing and innovating these key functional modules of intelligent mobile robots: sensing, actuation, control, navigation, and communications.
They will also handle the Harmonised Aerial Watch and Knowledge-based Survey (HAWKS) Project, the aerial component of the ASIMOV Programme and will primarily conduct R&D towards the development of core technologies necessary for autonomous drone deployment.
Moreover, the Mindanao-based university will also spearhead the Philippine Sky Artificial Intelligence Programme (SkAI-Pinas). Its main research component is the Automated Labelling Machine – Large-Scale Initiative (ALaM-LSI), which will be conducted in partnership with the DOST-ASTI once again. SkAI-Pinas aims to bridge the gap between the availability of massive remote sensing data in the country. It is comprised of an AI knowledge base, including experts, protocol, and an AI repository for models and labelled images to accelerate the workflows of remote sensing applications and fill the gaps in past and present remote sensing projects.
Also, to help protect the environment and reduce marine pollution, the same team will also develop a simple, cost-effective technology to monitor and quantify the marine litter in shallow coastal areas. The developers will base their technology on an existing towed optical camera array system for deep-sea monitoring that has undergone sea trials. They will redesign and improve this by adding sensors and cameras to be efficiently used in shallow coastal water surveys.
DOST-ASTI, on other hand, will work on the Robot for Optimised and Autonomous Mission-Enhancement Response (ROAMER) Project. It will develop prototypes of unmanned ground vehicles (UGV) that will help increase the productivity of different industries in the country, especially agriculture. Techs under Project ROAMER are envisioned to monitor, survey, and map agricultural farms for better decision-making and management.
Meanwhile, another university intends to develop a low-cost, wireless structural health monitoring system with visualisation through the Intelligent Structural Health Monitoring via Mesh of Tremor Sensors (meSHM) Project. The system will be made up of less than 50 sensors, that will utilise internet of things (IoT) technology and mesh networks, and can be installed in buildings, bridges, or metro rail systems.
Another project from them is the Development of Multi-lingual Chatbot for Health Monitoring of Public-School Children Project. They will create a system that can interpret audio input and can converse with students using two major Philippine languages, Filipino and Bisaya. The information gathered by the healthcare chatbot will be extracted to update the health database of the students stored in the cloud.
On the other hand, a university based in Luzon is set to develop an automated software that accepts values from a standard Impedance Spectrometer and uses a machine-learning algorithm to identify electrical, mass, and temperature parameters. It also involves properly fitting a spectrum with sufficient parameters that minimise common errors in existing numerical fittings. Industries involving electronics, semiconductors, food, medicine, and agriculture, are targeted to benefit from this project.
Lastly, using an IoT sensor network and deep learning, another Mindanao-based university will design and develop an intelligent traffic control and management system. It will monitor traffic in a selected area by using various devices that can measure several physical traffic parameters like flow, density, volume, as well as pollution. The base station will be established and equipped with intelligent behaviour and direct policy search capabilities using reinforcement learning to manage traffic automatically and efficiently and to avoid congestion. They will also develop and test a prototype of intelligent mobile traffic lights and will design web-based or mobile-based applications that enable easy access to traffic conditions.
The DOST- PCIEERD said that AI is one of their priority areas as it can boost the country towards the fourth industrial revolution. The agency also said that AI can disrupt traditional processes and provide solutions and opportunities that Filipinos can maximise.
A pregnant mother wanting to test for Down’s Syndrome in her unborn baby without invasive testing. A doctor trying to make a call on the optimal drug and dosage for a safer and more effective treatment. These are some of the people that the Singapore National Precision Medicine (SG-NPM) programme aims to help.
Established in 2017, the vision of this 10-year effort is to enable a healthcare strategy that is tailored to Singapore’s population diversity through precision medicine – a move that can revolutionise how healthcare is delivered.
Precision medicine takes individual variations in genetics, environmental and lifestyle factors into account, allowing doctors to more accurately predict which treatment and prevention strategies will work in different groups of people. Enabled by tools to analyse data on a large scale and with DNA sequencing becoming more affordable, precision medicine can improve healthcare by giving doctors a more detailed understanding of each patient.
Central to the effort is the Centre for Big data and Integrative Genomics (c-BIG), a collaboration between four A*STAR research institutes – the Genome Institute of Singapore (GIS), the Bioinformatics Institute (BII), the Institute of High Performance Computing (IHPC) and the Institute for Infocomm Research (I2R).
These efforts are coordinated under A*STAR’s Artificial Intelligence, Analytics And Informatics Horizontal Technology Programme Office (AI3 HTPO), which catalyses the development and application of A*STAR’s broad range data science, AI capabilities and technologies for a wide range of industry sectors.
“The first step was to build an IT infrastructure to securely store, analyse and share genomics data at scale to produce and distribute a reference catalogue that captures the genetic variation of 10,000 healthy Singaporeans,” said Dr Shyam Prabhakar, Associate Director, Spatial and Single Cell Systems at A*STAR’s GIS.
This first phase of the NPM has been completed, where the researchers have created the world’s largest genetic databank of Asian populations, which has three Asian populations: Chinese, Indian, and Malay represented. The time is now ripe for Phase 2, which will be to scale up the database.
“The next step is to extend the generation of genetic and phenotypic diversity data to 100,000 healthy Singaporeans in NPM Phase 2, drawing on the capabilities of A*STAR and our ecosystem partners,” said Prof Patrick Tan, Executive Director of GIS, and Executive Director of PRECISE (Precision Health Research Singapore).
“The richness of the data provided by the database, combined with our knowledge of Asian genetics accumulated over the years, means that the clinical applications of genomics are vast.”
This genetic databank is useful for analysis to reveal patterns, trends, and associations, and especially to identify millions of novel Asian-specific genetic variants. Understanding the actual genetic makeup of the Asian population allows the tailoring of products and medicines for this specific market.
For example, genomics can be found at the core of diagnostic tests, such as the use of non-invasive prenatal testing (NIPT) in pregnancy to identify children who may be born with debilitating or fatal genetic defects. Similarly, knowing the genetic variants that an individual carries can be used to estimate their likelihood of suffering from diseases such as diabetes or schizophrenia. Genomics can also be used to guide targeted treatments, such as administering the right drug in the right dose, relevant in pharmacogenomics (PGx), the study of how genes can influence responses to drugs.
The c-BIG initiative has contributed to delivering that vision through a variety of technologies and ecosystems. Leveraging the data storage and computing power capability from the National Supercomputing Centre, the team was able to deploy state-of-the-art genome analytics algorithms at an industrial scale to uncover the genetic variants of each individual.
A custom-built secured cloud-based big-data infrastructure has also been developed to enable and facilitate controlled programmatic and web-based graphical interface data access and analysis capabilities to Singapore’s biomedical research community. As the programme grows in the next phase, c-BIG will continue to scale by building on next-level data management, analytics and artificial intelligence (AI).
“The custom data sharing services built by c-BIG will enable secure mining of the resource, and thus pave the way for the discovery of new research insights and actionable clinical findings,” said Dr Nicolas Bertin, Chief Architect of the c-BIG’s NPM infrastructure.
As the team looks to tackle the new scalability challenges posed in NPM Phase 2, researchers are already working to source new types of data to enable richer integrative analyses, including methylation and single-cell expression signals.
The addition of new data types and scaling up of the databank will empower researchers and medical professionals to better understand the inherited diseases in Asian populations. This would pave the way to develop new treatments and ways to predict and diagnose diseases and enable more effective and efficient healthcare services for both Singapore and Asian populations.
Immersive virtual reality (VR) technology could help speech pathologists treat communication disorders, according to University of Queensland research.
Dr Atiyeh Vaezipour, from the RECOVER Injury Research Centre, said the results provided a foundation to inform the design, development and implementation of a VR system to be used in the rehabilitation of people with acquired communication disorders.
“Communication disorders can result in significant barriers to everyday life activities, and commonly require long-term rehabilitation,” Dr Vaezipour said. “Traditionally, speech pathologists deliver therapy in places such as hospitals and health centres, where there are limited opportunities for real-life interaction.”
It was noted that VR applications could simulate social communication situations that are difficult to create within the clinic in realistic, personally relevant and safe environments. VR could be used as a rehabilitation tool in communication environments that mimic the richness, complexity and dynamics of everyday situations.
Dr Vaezipour interviewed and surveyed speech pathologists following their use of an immersive VR kitchen environment. Participants in this study were positive about the usefulness of VR and its potential applications to the management of communication disorders within speech-language pathology, she said.
She also noted that speech pathologists considered VR to be a viable option for observation of communication performance in more life-like environments, bridging the gap between communication in the clinic and communication in external environments where distractions are present, such as background noise or visual complexity.
VR could provide valid contexts for people to practise their communication skills, build confidence interacting with others and generalise their communication skills to various environments. Dr Vaezipour said a human-centred design process was critical in developing VR tools for use in clinical practice. “Immersive VR applications will require customisation and adaptation capabilities that enable tailoring to the specific target goals, and physical, cognitive, and communication needs of the client,” she said.
Incorporating human factors from the early stages of design and development could enable the successful adoption of novel technologies in rehabilitation. More evidence-based research to support the use of immersive VR in the management of adult neurogenic communication disorders is critical to enhancing uptake and sustained use by speech pathologists.
The study is published in the journal Disability and Rehabilitation.
The potential of VR in the medical profession
According to another article, virtual reality technology is used in many areas of healthcare, in a variety of applications. These include medical training, for both doctors in training and students, patient treatment, medical marketing, and educating people about a disease or medical condition or process.
Current medical training has shifted from the rote memorisation of facts to imparting skills to use facts to arrive at a proper management strategy when faced with a given patient. This training includes problem-oriented learning, communication skills, and VR-based learning.
Any kind of medical situation can be simulated using VR, to allow the students to deal with it as in real life. This is followed by feedback and debriefing, to allow them to learn from their mistakes, if any. The cheapness of VR systems and the fact that faculty are not required to be present makes access more flexible and broad-based.
VR can be used to help medical professionals visualize the interior of the human body, thus unveiling otherwise inaccessible areas. For one, the dissection of cadavers, which was a norm for every new medical student, has given way to the study of human anatomy via VR.
Computer graphics have made it possible to recreate any part of the body in great detail, with extreme faithfulness to reality. Moreover, training can be offered using scenarios that closely mimic common surgical situations.
The high cost of such VR environments, including the cost of monitors, programming, and the other tools required for such training, may perhaps be offset by including a greater number of students in each program. However, the results are superior, with more accurate knowledge resulting from the use of VR.
In the recently held e-symposium Artificial Intelligence (AI) for Air Warriors, the Indian Air Force (IAF) Air Chief Marshal RKS Bhadauria and domestic and international experts explored AI-based solutions for air combat operations.
AI has grown significantly in the commercial sector and militaries across the world are pushing to deploy advanced technologies in their war-fighting facilities. Several initiatives to automate processes to improve the efficiency of aircraft maintenance operations have been launched. The sector has already digitised parts through electronic management systems. IAF is now focusing on AI-based applications on aircraft maintenance-related projects. Currently, IAF is working on predictive maintenance and the use of AI for predictive threat scenarios.
According to a C4I (command, control, communication, computers, and intelligence) expert, information received from heterogeneous sources is fused to enhance detection capabilities and identify targets. Multi-platform and multi-sensor data fusion is key. An AI-based decision support systems (DSS) architecture must be created for complex air combat operation environments. The latest generation of fighter jets are up to 90% software-centric for target detection, categorisation, tracking, and engagement activities. A human pilot cannot process the enormous amount of high-speed data being generated by multiple sensors. Only high-end processors that are manufactured for hard real-time architecture and run on a real-time operating system (RTOS) can process this data.
The net-centric tactical ISR information, combined with the joint operations in a combat mission requires information collection and transmission among net units (like satellites and air electronic warfare). Moving real-time information across multiple systems in the loop always diminishes the `real-time’ quotient within the information, making the data stale for use. Here, AI-driven, multi-access networking, and edge computing architecture are ideal communication solutions. Free-space optical (FSO) communication, 5G, and Satcom channels of communication can achieve flexible and assured bandwidth.
AI in unmanned aerial vehicles (UAVs) is the natural extrapolation, making the drones truly autonomous. These air-launched UAVs are capable of stand-off imaging and extended range communication. UAVs are expected to improve the decision support capabilities on the edge, making the DSS systems more efficient.
The use of AI for predictive maintenance is an already evolved field commercially. AI-based predictions maximise efficiency, reduce unplanned downtime, and increase equipment reliability. Coupled with a maintenance scheduler application, it provides the ability to manage, schedule, and execute maintenance programmes for thousands of machines. It also helps a user to manage the full asset lifecycle to aid intelligent strategic planning. It is possible to provide alerts via alarms, email triggers, or SMS notifications to prompt action. Aircrafts have a well-defined, structured, and strict maintenance schedule. The Ops Logistic Concept can be effectively implemented using similar AI-based predictive maintenance techniques.
The need for unbiased data to train and test combat systems is one of the biggest challenges for IAF. Also, security aspects like smart cloud servers available in India independently to provide data confidentiality and cybersecurity in support infrastructure needs to be addressed. AI solutions in air combat and predictive maintenance are expected to change the IAF standard operating procedures in the near future.
A robotic fish with wide-ranging functions from search and rescue to providing entertainment at an aquarium sounds like an unattainable dream but is the fruit of research by a young engineering team at the University of Hong Kong (HKU).
SNAPP, the robotic fish, currently holds the Guinness World Record for the fastest 50m swim by a robotic fish in 22.92s or at 2.18 m/s (meters per second), which is faster than most Olympic swimmers including Michael Phelps, who averages a speed of 2.1 m/s.
The robotic fish was invented by a student-staff team led by the Department of Mechanical Engineering and sponsored by the Tam Wing Fan Innovation Wing under HKU’s Faculty of Engineering.
The founder of the robotics team BREED is Timothy Ng, an HKU mechanical engineering graduate, who is happy to see that the team’s joint effort had reached one milestone after another. The team started out trying to invent a fish that could beat top high-school swimmers.
After initial success, they furthered their research to beat Olympic champions, and the result has been astounding. In January 2020, the team first set the Guinness World Record for the fastest 50m swim by a robotic fish with 26.79s. SNAPP is another breakthrough. “We have surpassed most Olympic swimmers except Cesar Cielo, who swam 50 meters in 20.91 seconds,” said Ng.
SNAPP is the fastest robotic fish to date, breaking the scientific boundaries known to mankind swimming, at a speed of 2.18 m/s. Other noteworthy fish robots such as Harvard’s Tunabot swims at 1m/s. Mr. Ng said: “By using flexible and soft methods in the tail design, we achieved our present record from the original 1.2m/s. This is the key to underwater propulsion.”
The team is encouraged by the fact that SNAPP is optimal for an array of functions. Professor Dennis Leung, Head of the Department of Mechanical Engineering and an environmental specialist, said: “I am very pleased with the research output of the robotic fish project. Apart from breaking the Guinness record, the robotic fish can also be applied in our everyday life. It is particularly useful in environmental protection such as monitoring water quality as well as surveillance of rubbish and oil spillage in seawater.”
Although SNAPP cannot yet match the swimming speeds of natural fishes, which have undergone millions of years of optimization in an evolutionary process, through the efforts of the team, it emulates the motions and profile of a real fish, hence it can integrate with the ocean environment seamlessly. Its fish-like gait produces low acoustic noise, keeping underwater sound pollution to a minimum.
With its unparalleled underwater mobility, and the ability to provide floating support and towing capability in the absence of lifeguards, the robotic fish is also ideal for rescue and search operations. When integrated with an artificial intelligence-based vision system and using an aerial drone, it could form a robust system providing unparalleled search and rescue of victims from both air and water.
It brings many new opportunities when integrated with other robotic technologies like drones, according to the supervisor of the project, Dr Fu Zhang, Assistant Professor of the Department of Mechanical Engineering, who is a robotics specialist, especially in aerial drones.
He stated, “The robotic fish project is truly interesting and significant in both research and practice. Its success would benefit applications such as underwater exploration and in saving lives, etc. Most of the oceans are yet to be seen by humankind, and new technologies can help protect the shorelines and public beaches from sharks while policing water boundaries and defining territorial maps.”
According to the World Health Organization, an estimated 320,000 deaths are caused by drowning each year. “The deaths of the professional divers in the Thai cave rescue operation years ago could have been avoided if SNAPP were available to them,” said Mr. Ng.
With its thin profile, SNAPP is fit for both shallow and deep-sea operations, capable of moving through undersea rock formations and fitting through tight crevices. The current prototype allows it to accelerate to a maximum speed within 0.5s, make tight turns with its caudal fin, and swim continuously for hours in a mixed swimming mode fish on a 48V, 850 mAh battery.
The robotics team is already working on using SNAPP to address ocean pollution and to scout for underwater garbage patches. The fish can relay their location back to a much larger collector, or be deployed to take water samples periodically in river basins, and to monitor the water quality, specifically for microplastics.
“It can also be used as “pet” for divers, carrying crucial equipment and oxygen tanks for them,” Mr. Ng added. Snapp can also act as a lifeline for divers that are caught in an underwater current, pulling them away from it.
While being in talks with commercial companies on utilising the search, rescue, and patrol functions of SNAPP, Mr. Ng is eyeing other wider applications. “Perhaps in the future, we would not need to keep real fishes captive for entertainment; robots can replace them instead.”
The spread of the pandemic – first in China and then across the world – was swift and caught governments, companies, and citizens off-guard. This global health crisis developed into an economic catastrophe that disrupted all manner of services, production, industry and created a supply chain crisis within weeks.
With business leaders needing to act quickly, the crisis provided a chance for advanced analytics and Artificial Intelligence (AI) based techniques to augment decision-making. Uncertainty touched every aspect of life under the pandemic – from health to work to economic impact – and expedited the accelerated adoption of advanced analytics and AI techniques.
Machine learning models were a natural aid but the development time for machine learning or advanced analytical models typically need a four- to eight- week window. And that is after there is a clear understanding of the scope of the use case, as well as the necessary data to train, validate and test the models. If a use-case evaluation is added before model development and deployment after the model has been trained, the time frame expands to three to four months from initial conception to production deployment
OpenGov Asia had the opportunity to speak exclusively to Indrek Onnik, the Global Affairs Director of the Government CIO Office of Estonia, to gain invaluable insights on how their digital government utilised advanced data analytics and AI during and even before the COVID-19 pandemic.
Indrek has in-depth experience in digitalisation, international affairs and cross-border cooperation and represents his country in international organisations. He is a keen advocate of digital transformation and takes every opportunity to share how going digital has positively affected his country and the people in it.
In his previous position as the Project Manager of the e-Estonia Briefing Centre, he had the role of hosting high-level information-sharing events. Through these, he has interacted with thousands of leaders around the world and has talked about how specific policies and strategies of Estonia allowed them to become one of the most digital societies in the world.
Across the globe, organisations and governments are searching for innovative ideas to tackle problems created by the COVID-19 pandemic. Countries are scrambling to ease pressure on their healthcare systems and find immediate solutions to combat the economic crisis – even as they try to ensure that life can continue as normally as possible. While innovation would be ideal, the pandemic does not allow many the luxury of time. In such a scenario, learning from others means the difference between life and death, survival, and collapse.
And what better example than Estonia? Considered the most advanced digital society in the world, the nation has built an efficient, secure, and transparent ecosystem in which 99% of governmental services are online. Indrek revealed that Estonia’s digital shift 30 years ago was vital to their current digital avatar. They already had in place tools for their citizens that other countries are struggling to provide today.
It is no surprise then that Estonians have designed numerous digital solutions to help tackle the ongoing COVID-19 crisis. One of which is a strong and secure digital identification system that is used not only by the public sector but also the private. This innovative digital identity can not only access government services but can be used for banking, social and community services (like libraries) and can even be used to buy prescription medicines in Estonia and Finland.
As a direct response to the unfurling COVID-19 crisis, the Estonian Patient Portal launched a new feature in a matter of days. This allows patients to temporarily start their sick leave in the system, helping take some of the administrative load off doctors and nurses.
Indrek says, “Estonia is ensuring the quality of data and high-value data sets” and is eager to manage and exploit them efficiently. In terms of data management and analytics, Estonia has set rules and regulations for data houses. These are not directive; instead, they are a set of guidelines and it is up to these houses their data integration programmes in conformance.
For example, when COVID-19 struck, Estonia immediately identified what the users needed in a time of crisis. They used data analytics in their programmes, such as analysing client calls where the needs of a user could be identified first-hand. This helped them deploy services in a faster cheaper and more efficient way. The government believes if resources can be saved in one area, they can be allocated in other areas that need these resources more urgently.
The COVID-19 crisis also gave rise to significant unemployment challenges. As in other countries, they had fiscal support programmes. Using the same digital identification system, these pay-outs could be done online and in a prioritised fashion.
Additionally, a data analysation tool that forecasts the probability of unemployment versus getting employed was put to use. The tool assesses which factors are impacting people, maps their needs to appropriate government assistance and so gets people into the labour market faster.
Another area where data analytics was used was to manage outdoor recreation and physical activity. While such tools were already in use before the pandemic, they were incredibly useful during the crisis where social distancing measures were in place. Recognising the need for exercise, physical movement and recreation, Estonia wanted to allow these activities safely.
For example, their hiking trails are much in demand. Using apps linked to the analytics tool, people can see which trails have a prohibitively large number of people already, so they can avoid these overcrowded ones.
The government fully appreciates the wider contribution of people and deeply values community involvement. To harness people’s creativity, experience, skills and intelligence, to further combat the crisis, the Estonian Ministry of Economic Affairs and Communications launched a fully online hackathon – Hack the Crisis. More than 1,000 innovators across 14 time zones got busy mentoring, conceptualising, clarifying, and refining solutions aimed at the COVID-19 pandemic.
The hackathon generated projects that have been taken been made live. For example, the state chatbot, Suve, is already up and running on many public sites, answering pandemic-related questions. A platform that matches volunteers with people needing assistance in the crisis has been launched. Another platform helps companies share their workforce, allowing employees to have adequate work (and the related pay) while simultaneously reducing that cost burden on business and/or their employee idle time.
With its success, the government is planning another Global Hack, bringing onboard new mentors such as tech entrepreneurs.
Indrek also touched on Kratt AI – a network of AI applications that enables citizens with public services equipped with virtual assistance through voice space interaction. For him, it is not just a simple IT project or an Estonian voice assistant, but it is a tool for a person to get everything they need from one device and one virtual assistant in one communication.
The Estonian Digital Government ensures that all these digital solutions are made available for all individuals across both the public and private sectors and endeavour them as transparent as possible. Examples range from machine translation, chatbot speeches and AI. For Indrek, it is not about democratising the AI itself, but the data the machine uses. Thus, they must make sure that the data available is simplified and complete.
Apart from its national source code repository, Estonia is building an AI artifactory whose mission is still the same – to give as many stakeholders as possible the means to use the available solutions the government had already built for them.
The outcome of decisions made by the Estonian government over the last decade in terms shows that their digital transformation is on the right path. Their digital foundations helped craft services tailor-fit for the new normal such as remote work, public buildings being closed and so on.
But they do not want to rest on their laurels and successes. Indrek confirmed that the government, from a digital perspective, is committed to being the initiators of change. Estonia intends to build more on cross-functionality, cloud technology, and the availability of data and solutions in the newer normal. This means more efficiency, better decision making and better services for the users of these services and solutions. But for them to be successful, stakeholders from both the private and public sector need to commit to their roles for the long term.
In the end, Indrek believes that the pandemic taught the world to do things faster. Nations have gained digital momentum and this momentum must not be lost. All governments must have a strategy and a vision to provide the most convenient and readily available public services for their citizens and these governments must continue striving towards that end goal.
The learning environment promises to be more fun and energetic with a new robot teaching assistant – a creation by Chula inventors rubber-stamped by the Gold Medal and the Innovation Excellence Award from the International British Innovation, Invention, Technology Exhibition (IBIX) 2020.
For kids, playing games and learning will no longer be two separate things. Following the recent launch of the teaching assistant robot “Avatar”, an innovative collaboration between Chula’s Faculties of Education and Engineering in the “TARAL: Teaching Assistant interactive Robot for Active Learning” research project.
“We developed the robot teaching assistant from a robot teddy bear, the first-generation robot that we submitted to a contest in South Korea. The highlight of the Avatar TA robot is the new feature that will transform the boring learning environment into fun lessons that learners will enjoy, including raising their Avatar robot with QR Codes received from answering quizzes. This process is called Gamification because it evokes a sense of enjoyment that learners may forget that they are studying”, said Prof. Dr Naowanit Songkram, Department of Educational Technology and Communications, who is a co-developer of the 10-inch, resin Avatar robot with Assoc. Prof. Dr Krerk Piromsopa of the Department of Computer Engineering, about the highlights and key features of the innovation.
The team applied the Learning Management System (LMS) in growing Avatar. The more learners answer quizzes, the more Avatar grows, “so learning and playing are pretty much the same thing,” the Professor said. Avatar is also equipped with Moodle open-source LMS which allows teachers to add and modify as needed all forms of contents and teaching materials in Avatars, be it animations, electronic books, or URL links. It was noted that the quizzes may include fill-in-the-blank, or full-sentence answers types. The evaluation and summary of the results are also done in real-time.
Prof. Dr Naowanit concluded that Avatar is currently under petty patent application and that an extension of the project to Chulalongkorn Demonstration School to develop exercise aids for students’ fitness test in P.E. is currently underway as well.
AI in education
A recent article noted that AI is slowly making its way into education, although robots in the classroom are yet to become a staple. Specific tasks can be rendered easier with artificial intelligence. Soon, it is expected that AI will be used to make grading relatively fast and simple on computer equipment. This will significantly improve the quality of education by helping students be as successful as possible.
Teachers and learners are already benefitting from machine-learning capabilities, improving access to information, and enhancing learning.
Some examples include:
- Personalized Learning: By offering personalized recommendations to each student, teachers can perform much better than before. With AI, students receive personal assistance with their in-class assignments as well as their final exams. It’s essential to give students immediate feedback through artificial intelligence apps since they’re targeted and customized. Lessons can be condensed into intelligent flashcards or study guides. Students can also be taught based on the challenges they face in learning class materials.
- Easy to Understand Materials: AI is being developed to make complex texts more understandable to students with varying levels of learning abilities. Students with learning disabilities should find it easier to relate and engage with the material if they simplify it or replace famous quips with simple alternatives.
- Educators Access to More Data: AI has enabled educators to have more access than ever before to a variety of data that can provide them with valuable insights into a student’s characteristics.
- Globalized Learning: Through AI-powered education, students learn the fundamentals of computer literacy. With the advent of more technological advances, there’ll be a broader range of courses available online.
- Identification of Learning Disabilities: Learning to identify learning disabilities in students is the first step in providing effective learning for them. Not all current testing is highly effective in detecting dyslexia, dyscalculia, and other learning disabilities. Some teachers are being trained on new AI systems to administer more effective tests to discover some of these conditions. A learning disability can be identified and the resources available can be used for the student.
- Simplified Administrative Tasks: With technology, grading can be automated in instances where multiple tests are being administered. So, professors wouldn’t be spending as much time grading them as they would be with their students. AI is expected to do this soon.
- Uses AI for Student’s Reliable Feedback: As AI gets increasingly advanced, this makes it possible to give students direct feedback on their performance. The system allows students to work at their own pace as needed to master the material and it won’t move on until students demonstrate mastery.
- New Innovations: AI can help in creating data-driven forecasts allowing operations departments to analyse complex data. Hence, they can adequately plan for the future, assign seats during school functions, or order food from local cafeterias. School districts can drastically reduce waste by eliminating over-ordering, thus saving money.
As the COVID-19 pandemic continues to dominate the global landscape, there is a pressing need for organisations to re-examine their businesses and priorities in this new normal. No doubt, many are already making changes in the way they run their businesses and the way they make decisions to emerge stronger. Nonetheless, there remains an urgency for the deployment of technologies that help bring greater efficiencies and wider reach in this new digital-first – or digital-only for some – environment.
Artificial Intelligence (AI) and Intelligent Automation (IA) are recognised as key enablers for organisations to repair, rethink and reconfigure to emerge from the pandemic. They allow businesses and governments to adapt their operating models for sustainable competitive advantage as well as make adjustments and fine-tune along the way. And when it comes to customer experience (CX), such technologies have allowed businesses to manage high volumes and sudden spikes in customer requests during times of uncertainty.
Undeniably, the adoption of AI has grown exponentially as a result of the pandemic. In fact, usage of AI-enabled support channels has increased as high as 157% in the Asia Pacific (APAC) since February 2020. Right from the start, AI played a pivotal role in mitigating the effects of the pandemic across sectors. In its most basic usage, it eased the administrative burden by automating processes, prioritising customer queries and intercepting simple and repetitive queries with articles from a help centre.
OpenGov Asia had the opportunity to speak exclusively with Malcolm Koh, Customer Experience Strategist, APAC at Zendesk, a customer service software company with support and sales products designed to improve customer relationships. Malcolm has deep expertise in both operational and strategic elements of customer service delivery with over 20 years of experience spanning 8 industries.
“In 2020, governments and businesses faced exceptional challenges,” notes Malcolm. “Adapting to a world reshaped by COVID-19 has meant significant changes in how they run and interact with their citizens and customers respectively. The massive shift online has accelerated the digitalisation efforts across the private and public sector, casting the spotlight on the importance of great CX.”
The increase in digital adoption has reset the benchmark of customer expectations, in terms of access, ease and turnaround time. Not unsurprisingly, with more platforms and options than ever before, consumers are spoilt for choice in the digital space, and expect more from the businesses they interact with. According to Zendesk, 2 out of 5 customers in APAC say the customer experience is more important to them now than a year ago.
“With this heightened demand for great CX, consumers have adopted new behaviours. They want quick and effective resolutions to their problems – particularly in times of crisis – and are often keen to figure things out themselves first. They also want to reach out to brands through channels they’re already familiar with, such as messaging,” Malcolm adds.
Change alone is not enough
Companies are now looking to integrate these new demands into their overall business, but this is easier said than done. Often bogged down by legacy infrastructure and processes, companies struggle to scale digital solutions quickly enough to meet ever-changing customer needs. Change, then, is not the sole criteria for success. Agility and flexibility are also key ingredients. While those lagging must catch up, everyone must have the ability to adapt quickly to stay ahead of these new challenges and trends, even as they continue to evolve.
Though the introduction of AI to streamline processes and manage spikes in customer queries cannot be built overnight and may not be sufficient in and of itself to satisfy customer service demands, it is necessary to drive greater efficiencies, which ultimately help drive business growth. “Think of AI like a muscle. The more you train it, the stronger and more accurate it will be, “ says Malcolm.
“Being efficient has always existed as a business priority, but what that means to businesses and governments has evolved when it comes to implementation. And AI and automation have been central to that evolution,” he added. For those new to such technologies, starting small helps according to Malcolm. “That way, you can implement small changes and closely measure its effect and progress, which will go a long way to garnering more internal support and influence as change is often a team effort.”
Keeping the human touch with personalisation and empathy
When there’s talk of AI, Malcolm notes that there’s also a common misconception that AI will replace humans. “It is about automating manual, high volume processes where possible to be more productive and redeploying human resources to more complex tasks,” says Malcolm. “While AI has become increasingly sophisticated, the human element and our ability to empathise with the customer is still currently an irreplaceable piece to any successful CX strategy.” In such cases, Malcolm shares that AI-enhanced chatbots “need to know when a customer query is beyond its ability and to facilitate the seamless hand-off to a human agent without requiring the customer to repeat everything again to the agent, which can be incredibly frustrating.”
Moreover, customer engagement today also calls for more personalised experiences. This is where predictive AI technologies come in. Having the trend or history of all interactions people have with a business can be turned into insightful data that allows companies to predict and tailor the customer experience across multiple channels.
Supporting customers on their preferred channels
As a result of the pandemic, Zendesk found that over two-thirds of customers in APAC used a new support channel to get in touch with a business – 70% of which intend to continue using said channel. That is why businesses need to incorporate their services on more channels to address these demands.
Of course, tailor-made omni-channelled services need time, resources and research on how to scale, integrate data and train agents to make the most of the predictive AI approach. But, Malcolm acknowledges, there are a lot of AI tools available that can help in terms of personalising customer experiences and engagement on multiple platforms.
Investing in customer-centric CX reaps long-term benefits
Ultimately, Malcolm believes that businesses “need to be efficient to be agile”. Companies and organisations that are lagging need to move faster by investing in technology and processes that enable them to be customer-centric across the entire organisation.
Whether it involves utilising multiple channels for real-time, personalised customer engagement, implementing better collaboration tools for employees, enhancing efficiency with AI and automation, investing in CX will go a long way to drive sustainable growth in this time of crisis and beyond for companies and businesses in all sectors.
“Businesses need to consider the impact CX has on the bottom line. One in two customers will switch to a competitor after just one bad experience. And when businesses deliver on good CX, three in four are likely to spend more,” says Malcolm.
“AI simply cannot work alone – there’s such a unique interdependence between AI and humans that demands attention. And there’s no one-size-fits-all approach to figuring out the right balance,” Malcolm notes. Businesses need to look at what their customers want and expect from them to inform their decisions. Malcolm firmly believes that this customer centricity is what will help businesses navigate these unchartered waters.