Noted speakers at the Singularity University Summit last week included Sutapa Amornvivat (second from left), author of this article and a regular Bangkok Post contributor. (Photo via SCB Abacus)
Author: Sutapa Amornvivat, Ph.D.
Published in Bangkok Post newspaper/ In Ponderland column 27 June 2018
Last week, at the SingularityU Summit in Bangkok — a two-day event that comprised a series of talks by visionary technologists inspired an audience who were mostly business leaders and key policymakers, I was honoured to join Dr Vivienne Ming of Socos Labs and Dr John Jiang of CP on stage to discuss Artificial Intelligence (AI) and its impact on Southeast Asia.
The recurring theme throughout the event was the concept of “exponential” technology. This term emphasises the rapid growth of impact from breakthrough technologies. By nature, humans are linear thinkers. We often (mistakenly) over-estimate the impact of technology in the short run, but underestimate its effects in the long run. As a result, we can dismiss new technology prematurely, and thus forgo what could become the next big thing.
With such an exponential trajectory, especially in AI development, the future of work is changing rapidly. Many fear that AI is a very real threat to our job security. As a parent of two preschoolers, I have always pondered what skills our children will need in the next decade.
It would have been similarly difficult for our parents to guess that AI technology would become such an integral part of our present everyday life. My fellow speaker, Dr Ming, advocated that we should not be guessing at all. Instead, she suggests that the best way to prepare our children is to train them to embrace the uncertainty of the future — to be creative, adaptive and problem explorers. This requires a different kind of learning experience than the current education system offers.
Can AI, despite posing a risk of job losses, also enrich education for the future?
The answer is yes, as we have seen tremendous progress in AI that can play an important role in solving pain points of students and educators.
Market research by TechNavio forecasts that the use of AI in the US education sector will grow 48% annually from now until 2021. Tech giants like Facebook, Microsoft, IBM are also paying attention. Last year, Facebook, in support of the Gates Foundation, announced a partnership with a charter school network, Summit Public Schools, to develop a learning platform powered by AI algorithms.
Currently, the most prominent use case of AI in education technology is to create a personalised learning experience.
The idea behind personalised learning is that individuals develop at different rates, with varying proficiencies and interests. In Thailand, the effort to “personalise” has led some schools to sort students into classrooms based on performance. There is a downside to this policy. Those with poor performance could continue to spiral downwards when they are grouped together. Research shows inconclusive evidence whether this initiative positively impacts a student’s academic achievement.
This issue is particularly important in Thailand where educational inequality is high. According to the Thai Office of the Basic Education Commission (Obec), the average size of a public secondary school classroom is as large as 50 students. For OECD member countries, the average class size is 24 — less than half of Thailand’s.
This is where AI can come in.
Based on a student’s own pace and interests, AI systems can custom-design individual learning experiences, so that each student can find the most optimal path towards their own learning goals.
Imagine a classroom where each student can move through class materials at their own pace. UCL Knowledge Lab in London built a software called AIAssess. The system assesses a student’s understanding of a concept, and dynamically adjusts practice problems to match that level.
During the class, Lenovo’s virtual classroom uses computer vision to help teachers interpret students’ gestures to identify those lagging behind and in need of special attention. Facebook built an app that helps student create course plans to best achieve their learning goals.
After class, a new teaching assistant, Jill Watson, who shares the same name as IBM’s AI platform, helps teachers respond to student questions. A team of scientists at the Georgia Institute of Technology built this machine using data from online discussion forums. Using advanced Natural Language Processing algorithms, it can identify common questions and mistakes that students make.
At home, students can read a personalised textbook created by Deep Learning algorithms. A startup company, Content Technologies, uses algorithms to condense books into short summaries and identify key materials. In digital format, we can track individual student interaction with books such as time spent reading each paragraph, or whether they are stuck on difficult topics. Given such data, AI can help identify students’ pain points and appropriately respond to help improve learning.
The use of AI in education is still at its early stage. Personalisation by AI combined with online open course platforms like Khan Academy, Coursera, and EDX will create a truly customised experience. We might see an entire degree composed from online materials from different sources.
By adopting AI technology to personalise the education system, we will be able to shift the focus from students aiming for standard degrees towards a more wholesome learning experience. This will make our children better equipped for the unknown future.
While AI does indeed offer limitless potential for human progress, we should be conscious of its impact on our mentality. One of the many things that keeps me up at night is how AI technology can weaken the human mind. For example, we can no longer remember many phone numbers, directions, or even tomorrow’s calendar. The argument goes we are then free to engage our minds in other creative pursuits or solving more complex problems. But do we really?
The last chapter of Jerry Kaplan’s book, Humans Need Not Apply, suggests that the future might not be such a dramatic humans-vs-machines scenario. Humans are already ceding control to machines willingly. Nowadays, many decisions are automated; drivers trust Google map for directions, and doctors depend on machines to test, diagnose and treat patients. That’s the benign-looking threat Kaplan speculates will happen. We will welcome computer colonisation.
Let’s not allow our laziness to be our downfall!