Two days after landing in Hong Kong, I had the opportunity to attend AI & Education, a conference organised by EdTech Asia. I was immensely curious to hear how EdTech is talked about in this part of the world.
While Finland was (inevitably) mentioned a couple of times, Singapore is considered the clear model to follow. The Singaporean government is seen as leading the charge in matters of education reforms, giving clear directions on how AI should be integrated and taught in schools, as well as encouraging public/private partnerships.
What I found particularly interesting is how AI should be implemented in the classroom. While the opening speaker Duc Luu (Chief Strategy Officer, RISE Education) listed 8 uses of AI in education (supporting teachers, predicting student performance, grading students efficiently, customising learning, organising content effectively, improving retention, connecting students & teachers and predicting learning modalities), the conversations focused largely on one specific use case: using AI to track, measure and report user engagement and performance.
Products demonstrated on the day include a brain development monitor for babies, a brainwave-measuring headband to check the student’s attention level, and software that uses face and expression recognition to check whether employees actually pay attention during the boring compliance videos.
The focus is on tracking (at all times and all ages) how engaged the learner is, and on boosting the performance of their brain.
To me, this leads to larger questions regarding the ethical use of AI in education. How much data do we want to track? Where do we draw the privacy line, especially with underage users? How do we ensure that the data is used to improve the learning experience, rather than to push students even harder?
Lamont Tang (CEO of Oyalabs), explained that each country should decide what level of privacy they are comfortable with. At one extreme, Germany bans smartwatches for children out of concern for their privacy. On the opposite side, China continuously tracks the engagement levels of students. From a scientific perspective: if you do not track any data, you cannot know how to improve the learning experience.
Raphael Nolden (CEO of Jaipuna) further argued that while students in Asia currently do an insane amount of studying, most of that learning is very ineffective. AI should therefore help students study less and take more breaks, in order to enable a more productive learning process (as proven by their brain scan, facial expression or test results).
Another way AI can hugely help students is by reducing the pressure caused by exams. Assignments are currently still prohibitively expensive, argued Rachel Brujis (Head of International Market Development, Pearson). If assessments become cheaper, students get tested more regularly and get more nuanced results, rather than having their entire academic year rest on one annual exam (or in the case of the Gaokao, their entire career). Schools can move from single summative exams to continuous formative assessments.
For AI to have a positive impact in education, transparency is critical, explained Chris Geary (CEO, BSD Education). Every company should know what they are measuring, and communicate that clearly with their users. And most importantly, teachers are the only ones who really understand education — and therefore need to have a voice in the application of AI in the learning environment.
What do you think of the use of AI in education? Is this discourse any different from the debates taking place in Europe or America? Please leave a comment, I would love to know your thoughts!
Over the next two months I will collaborate with EdTech Tours and travel across China and Hong Kong to make education innovations more visible. If you know of any initiatives that we should explore, can introduce us to local innovators, or want to support this project, please get in touch: firstname.lastname@example.org