■ Thinking about education in the age of AI
There was a symposium called “Thinking about education in the age of AI.” So, what is education in the age of AI? Japan’s best researchers and members of the business community came together to exchange opinions on this question.
Three participants were luminary leaders in the field of AI research.
One was Dr Inui, Team Leader at RIKEN and Professor at Tohoku University.
Another was Dr Saeki, NICT Center Leader.
Another was Dr Takamura, Team Leader at AIST and Professor at the Tokyo Institute of Technology.
Dr Inui commented that he would like to contribute to education by creating AI technology that can understand language. Fostering intellect, judgment and expressiveness requires revisions through feedback. AI technology that can automatically revise and grade will give students more opportunities to write. He says that a workable technology that could support lessons and homework may be available within several years.
Dr Saeki commented that it is possible to develop education-oriented AI that can, for example, assist listening skills to distinguish between the pronunciation of R and L, produce automatic translations or conduct conversations on social media. However, this requires learning data, human resources and funding. He hopes his research output can be proactively harnessed.
Dr Takamura said that it should be possible to apply AI to detect mistakes and provide corrections, create problems and educational materials as well as create automatic explanations. Technology to automatically correct grammar in English essays has been achieved and it is possible that this could be expanded to other subjects. This requires a massive amount of data and verification is important. For this reason, he has asked for the cooperation of educators and learners alike.
However, for AI researchers, research on education seems to have been a lower priority than applied research into automobiles, manufacturing and finance. Reasons for this include a separation between researchers and educators as well as a lack of data. However, we are beginning to see the usage of AI falling behind in the same way that the education sector fell behind when it came to usage of IT and digital technologies. This is something the education system must be aware of.
Conservative educators are likely to say that AI and big-data are unnecessary for education (in fact some do actually say this). This is the same argument that was made in the recent past that IT and digital textbooks are not required.
This has led to Japan’s usage of information in the education sector being at the level of a developing country and the educational environment for children falling behind. I do not want to see this situation repeat itself.
With this in mind, there has been an active exchange of opinions regarding issues and possibilities for using AI in the education sector. Problems that remain with collecting data on educational activities include the disclosure and distribution of research data conducted nationally, standards and skills of educators and the protection of private information.
Others voiced the opinion that we must come to a common and clear understanding of the definition of the term ‘AI’ as well as a clarification of what it can and cannot achieve. Furthermore, others have pointed out that we must develop technologies in consideration of how they will be introduced to areas other than adaptive learning and based upon how we want to teach children in our ideal education system.
Many have expressed their hopes for the promotion of open innovation such that schools are not merely conceived of as limited communities, but rather as an attractive field of research in which industry, governments and academia can collaborate and push forward technological innovation.
Japan, which has come late to the party in terms of use of IT in the education sector, is running a serious risk of being left behind in terms of AI as well. We would not be able to recover should this happen. The time for action is now.
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