Education in the age of Intelligent Machines:
Our future is being shaped by two major forces: the 4th Industrial Age driven by Artificial Intelligence, Machine Learning, Quantum Computing and allied technologies like the Internet of Things, Blockchain, 3D Printing, AR and VR, and the 4th education revolution which is disrupting the traditional education model, propelled by the same technologies.
The WEF 2020 meeting at Davos just concluded on the 24th January 2020. One of the panel discussions was on the Reskilling revolution with the theme “Better skills for a billion people by 2030”. Link to the video of panel discussion on the topic : https://youtu.be/mlpMomsOWxA
The complete failure of the AICTE to project and anticipate the future of technology has led to the absurd situation of our freezing down of technical education at a time when explosive developments in new technologies such as protein engineering, Biomanufacturing and quantum technologies are offering trillion dollar economic opportunities. . Here is a link to the AICTE appproach and vision ( or rather lack of it) : https://timesofindia.indiatimes.com/home/education/50-seats-vacant-no-new-engineering-colleges-for-2-yrs-aicte/articleshow/74108434.cms
Without beating about the bush, I wish to suggest that it is Artificial Intelligence and allied emerging technologies that provide the answer to the upcoming challenges.
The term “artificial intelligence” has been around since its introduction at a science conference at Dartmouth University in 1956. But only in the past several years have we started seeing theory put into practice the way those researchers imagined. We now have machines that can translate languages, compose music, write novels, and operate vehicles.
The key constituents of an AI-empowered educational ecosystem are the following:
- The AI-fluent SmartEducator ( machine teaching is an important ability, to which attention was drawn by Microsoft in 2017)
- The AI powered autonomous Learner ( the future of education will be led by the autonomous learner)
- Recommender and content personalisation systems
- Chatbots to assist both educators and learners ( building on the Jill Watson experiment of Prof. Ashok Goel)
- Co-learning spaces and emerging technologies experience centres ( the viable alternative to AICTE approved programs)
- AI enabled assessment systems ( that are a death knell to CBSE and other Board exams)
- Blockchain for academic credentials ( MIT Edublocks and SONY Global Education models)
The rapid progress in Artificial Intelligence can be appreciated from the flow of the sequence of events from IBM Blue defeating the human chess champion Gary Kasparov in 1997 to Google’s AlphaGo zero defeating the world’s Go champion in December 2017. In between IBM Watson defeated the reigning human champions in the game of Jeopardy Champions in the year 2011.
Even as we prepare ourselves for the age of Artificial Intelligence, the era of Quantum Computing is upon us and it could eventually revolutionize the way medicines are developed, financial options are priced and climate change is managed, experts say. It’s been lauded for its ability (or, at least, its potential) to complete complex calculations in a fraction of the time that it would take even the fastest traditional computers today.
The big news on 23rd October 2019 was the demonstration of Quantum Supremacy by Google, meaning thereby that their 54 Qubit Sycamore Quantum Computer could do a calculation in 200 seconds, that the fastest classical super computer, the Summit would have taken 10,000 years. This event has probably a much greater significance that a man landing on the moon.
Education in the age of intelligent machines will be AI-enabled and will be in really 3 stages. The first of pre-school learning facilitated by the parents. The School stage may extend for about 10 years during which the new learning dispositions of curiosity, autonomous learning, mastery learning and achieving the higher levels of Bloom’s taxonomy of learning objectives are developed and finally the third stage of lifelong learning. In terms of domains of knowledge, President of NorthEastern University, Prof Joseph E Aoun has advocated teaching ‘humanics’ to create a robot-proof education. Perhaps above all, Aoun says humans need to focus on skills that are harder for artificial intelligence to replicate. Specifically, that means taking knowledge from one context or discipline and applying it to another. Humanics itself is about combining three separate disciplines.
“We humans are creative, innovative, entrepreneurial. We are able to interact with other people, work with them, be empathetic. We are able to be culturally agile, work with people with different backgrounds. We are able to be global,” he said.
It is often said that evolutionary changes happen in response to the pressures of the external environment. Sometimes it is simplified to “ necessity is the mother of invention”. The AI powered autonomous learner , is a result of this evolutionary learning process to cope with the situation when there is no teacher.
Autonomous learning is clearly a very critical part of the above mission and an important element of the strategy to reach the goal by 2030.
So what might the implications of these developments be for educators and students?
The primary goal of AI research may be to teach machines how to learn, thereby automating some of the tasks that complicate our everyday lives, but brain scientists are saying it goes both ways: We now know more about human learning as a result of machine learning, and it has some exciting implications for the classroom. What does machine learning tell us about human learning ?
One very important learning from ‘ overfitting to the test data’ is that too much emphasis on getting more marks in the monolithic summarise assessments at school or University is counter-productive. Rather continuous swift feedback on multiple dimensions helps in progress of learning, through re-enforcement learning. We also know that more training data leads to better model of predictions, and so instead of limiting the set f courses a student can take, a learner should be allowed to pursue as many courses as the learner finds interesting. Finally recursive learning inspired by Artificial Neural Networks with forward and backward propagation, help learners have a method and approach towards becoming autonomous learners.