Reimagining the New Normal with AI

COVID-19 is accelerating change across industries; trends that were already picking up prior to the pandemic are now being implemented in full force. Artificial Intelligence (AI) is a prime example of this.

For example, it was only in 2017 when China announced its plans of becoming the world leader in AI by 2030. But since the coronavirus outbreak, China has had to put those theories into practice: corporate giants and Research and Development (R&D) companies were making their algorithms public for more efficient virus detection. AI-powered infrared technologies were being installed to measure body temperature in a contactless and reliable manner. And “One-minute clinics” run by AI-powered chatbots were made available to provide online consultations to thousands of users.

Just a few years ago, AI and Deep Tech were seen as theoretical, faraway technologies. Now, it seems we get a few steps closer to that reality every day. This begs the question: what kind of future are we looking at? As the pandemic ensues and a vaccine remains to be seen, what opportunities does AI provide in shaping our new normal?

Let’s take a look at some of the possibilities.

As one of the greatest healthcare crises in recent history, the burden is placed on the shoulders of healthcare professionals all around the world. In countries like the Philippines, hospitals are already at full capacity as they attend to tens of thousands of suspected COVID-19 patients. The traditional way of doing things—scheduling appointments, waiting in a room with other patients, and conducting face-to-face interviews—is simply not as feasible right now.

Telehealth is now growing in the region. Through the use of digital information and communication technologies, patients can get access to medical treatment without having to break self-quarantine measures. An example of this is the AI-powered chatbots that can answer common health-related questions. Another example would be telehealth platforms that can intelligently connect patients with doctors, like Singapore’s MyDoc or Doctor Anywhere.

These technologies will remain useful even after COVID-19 as this solves the issue of accessibility. Patients who cannot leave their houses due to disabilities or patients who come from remote, far-flung areas now have an alternate option.

AI is also being used to analyse X-rays, CT and MRI scans, and other data to identify signs of COVID-19 or diagnose general health issues with patients. This is what HealthTech startup Alkenist is doing in India.

All this is painting a picture of what may be the future of healthcare—a future where doctors and AI can work together to deliver a better healthcare experience to patients.

Dr Kai Fu-Lee, the chairman and CEO of leading Chinese technology venture capital Sinovation, shared his thoughts on this topic during SGInnovate’s most recent webinar “AI for Good”:

“A very good symbiotic use of humans and AI is where AI can be used for optimisation and routine work, and humans elevate creativity and compassion. I can envision in the future that the doctor will become more of a compassionate caretaker… But AI can be used for analysing radiology, MRI and CT, likelihoods and outcomes, proposing diagnoses.”

AI can be harnessed as a doctor or scientist’s assistant so that doctors can put more focus on the human aspects of their profession, which include decision-making and caretaking.

Another industry that was badly hit by the pandemic is manufacturing. Traditional factory floors involve an assembly line of workers operating in close proximity with one another. It’s either they place strict measures and enforce workers to remain six feet away from each other at all times or work remotely. The way traditional factory floors work, both options are infeasible.

The health risks of continuing factory operations were just too big, so major manufacturing companies have had to lower production levels or shut down their factories altogether. But through the use of new AI technologies, it’s possible for manufacturers to continue working in a safer manner.

Cloud-based monitoring technologies can be used to observe factory floors to ensure that everyone is following proper protocol. Thermal imaging feeds can also be implemented to observe body heat and identify workers with higher-than-average temperatures. These allow for remote, accurate, and efficient management of factory operations.

If you take AI a step further, manufacturers can leverage industry 4.0 technologies to create smart factories that can be fully automated and require little to no human intervention. Not only does this minimise risk significantly, but it also offers more efficient, contactless operations.

The concept of the smart factory came about a few years ago alongside the emergence of Industry 4.0. Amazon has been toying with robotics and automated shipping centres for the past few years. The e-commerce giant has even experimented with a fully autonomous delivery system using drones through their Prime Air service.

While there were only a number of other manufacturers creating smart factories — most of them being big names like Nike, Siemens, and Hewlett-Packard—experts predict that smart technology adoption will increase in demand thanks to COVID-19.

According to a report released by Research And Markets, the global smart manufacturing market is predicted to reach US$220.4 billion by 2025, growing at a compound annual growth rate of 4%. Asia-Pacific is expected to have the largest share of the global manufacturing industry as rapid industrialisation has boosted manufacturing in the region.

Schools have inevitably shuttered their doors for the safety of both students and staff. Right now, there are around 1.2 billion children out of classrooms thanks to the pandemic.

Many educational institutions in Singapore are turning to online learning to continue operations. But as many have not yet adopted education technology solutions, most are using video conferencing platforms like Zoom and Hangouts to conduct classes.

However, there is (very unironically) a learning curve to online education. After all, there’s so much more to education than just conducting the syllabus online. For distance learning to be effective, there need to be tools in place that can track student progress, share feedback, and encourage interaction among students.

“We’re investing in a lot of companies in China for online education and we’re finding that AI is very good in doing many routine things that teachers do. For example, grading and assigning homework, grading exams, giving drills and assignments in a way that’s targeted towards every student’s individual needs and trouble areas,” says Dr Lee.

Similar to how AI can emphasise the human aspects of being a doctor, it can also transform the educator’s role so that teaching is more tailored to each student’s progress. Traditional education has students grouped by age and learning at the same pace, regardless of capacity or comprehension. But by automating many manual, repetitive tasks, teachers can focus on observing each student’s progress and adjusting materials, so it suits the student’s level.

AI is already being used in schools to personalise curriculums, identify at-risk students, predicting emerging problems, and grading exams. How it will further shape the future of learning remains to be seen, but some educators are already seeing the benefits of switching to online as it’s easier to reach students more effectively and communicate online.

In any case, it is clear that COVID-19 has disrupted the educational system, and many schools will likely make e-learning a part of their new normal.

People do not normally associate AI with climate change, but there are plenty of opportunities for the two to work hand-in-hand. For example, AI can be used to make accurate climate predictions such as extreme events like hurricanes or typhoons. It can also be used to measure where carbon and various air pollution is coming from.

Another application of AI is in discovering new materials that can be used to store, harvest, and use energy more efficiently. Examples of these are solar fuels, carbon dioxide absorbents, or structural materials that use less carbon. Around 9% of the world’s global emissions and greenhouse gases come from concrete and steel production. These new materials serve as sustainable, low-carbon alternatives.

“We can use the same kind of deep learning methods to generate, synthesise, and evaluate new candidates for materials, two of which can be used in the context of climate change. One is for carbon capture and the other is for batteries. Normally the design of these materials takes a very long time—something like ten years, easily,” says Dr Yoshu Bengio, who also spoke at the SGInnovate webinar.

Dr Bengio emphasised the role of AI and machine learning in helping scientists discover these new materials. Instead of just relying on trial and error, there are now databases, computations, and algorithms that can cut down that process significantly. For example, material scientists at TU Delft University in the Netherlands were able to discover a new, super-compressible and durable material using AI. And they did so with zero experimental tests in the lab.

The sooner we can find more sustainable alternatives, the sooner we can curb our impact on the planet.

What’s more, AI’s applications in other fields also play a role in mitigating climate change as it can create more sustainable businesses. AI can be used for freight route optimisation, electrical vehicles, and energy-consumption predictions. Not only can these applications lower costs and improve efficiency for businesses, but they also do their part in lessening the load on our environment.

For a long time, technology and innovation were seen as a boon for business but a detriment to our world. Industrialisation and urbanisation are associated with images of black skies and smog. But today, we’re seeing the role of AI and technology in improving our lives—not just in making it more efficient, but simply, better all around.

Through AI, people can get better access to healthcare, manufacturers can operate more efficiently, students can have new avenues for learning, and our impact on the environment can be mitigated.

The world is already looking a lot different from 10 years ago. There’s no need to reimagine it—the new normal is here.

We launched a Deep Tech for Good initiative in June, in partnership with global organisations that include Element AI. This initiative brings together experts in science and technology innovations, and catalyses collaborations among corporates, startups and governments, to advance Deep Tech developments for social and economic good.

If you have missed this session with Dr Kai-Fu Lee and Prof Yoshua Bengio, catch it here.