When Teachers were human? 

The March of Artificial Intelligence: 

By defeating Gary Kasparov on May 11 1997, Deep Blue made history as the first computer to beat a world chess champion. Kasparov refused to believe that a machine could play better than him and argued that the computer must actually have been controlled by a real grand master. Somewhat like most School teachers are under the delusion that they cannot be replaced, although they are seeing “tuition teachers” and Byju teachers edging them away. 

In the year 2011, IBM Watson defeated Rutter and Jennings who  were till then Jeopardy-winning machines.

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa ( clean slate) superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go, using a novel form of reinforcement learning  in which AlphaGo Zero becomes its own teacher. 

This is therefore a further stimulus to self-learning and avoidance of “taughtitis” a collateral damage that occurs with traditional education. See Guy Claxton: https://youtu.be/JxWybvns1jg

Beyond Games: 

Going beyond games, AI is now able to perform many tasks which were done only by specifically trained humans. Work done by radiologists and ophthalmologists is now comparable to that done by AI. In fact “Deep Medicine” is a book published in July 2019 by Eric Topol that describes the impact of AI on medicine. Robot-lawyers are a reality: https://donotpay.com . Self-driving cars are also now a reality, and so will be self-directed learners : https://mmpant.com/l2sl/

AI systems will be further strengthened with the availability of Quantum Computing to accomplish Quantum Machine Learning. The real big challenges of the world for a sustainable future  are attempted to being solved through Quantum Technologies. https://youtu.be/iB2_ibvEcsE

Quantum Technologies for future readiness: https://mmpant.com/qt4fr/

AInEd Supremacy: 

The phrase ‘ Quantum Supremacy’  was coined  in 2012 by the Caltech Professor John Preskill to describe the  situation when a Quantum Computer could solve a problem that no classical computer of the day could solve in a reasonable time. In a similar spirit I have coined  the phrase “ AInEd Supremacy” to describe the situation when the AI technology of the day in conjunction with a human educator, an AI fluent SmartEducator: https://mmpant.com/aifse/ ) will achieve learning outcomes that no traditional teacher with traditional technology could achieve.

The AInEd supremacy could be achieved during this decade, with the use of Chatbots, face and emotion recognition, recommender systems, text to speech, speech to text and machine translation. And of course technologies like GPT3. 

Terrence Sejnowski, Francis Crick Professor at the Salk Institute for Biological Studies and Director of the Computational Neurobiology Laboratory, says that “ Education is going to be the killer app for deep learning”. 

Sir Anthony Seldon illustrates how the traditional roles of  a teacher will be transformed by AI over the coming decades: https://mmpant.com/2021/03/03/ained-supremacy/

The technology to deploy ‘holograms’ for professor’s presence anywhere ( watch this 4 minute video right now) already exists. With time it will become more readily available: https://youtu.be/auJJrHgG9Mc

Technology powered by AI could even help on resurrecting dead professors : https://theconversation.com/chatbots-that-resurrect-the-dead-legal-experts-weigh-in-on-disturbing-technology-155436

In addition to the help that AI will provide to facilitate the traditional tasks of a teacher, there are a few more results that learning analytics will provide that enhance the teaching quality and the learning effectiveness. For example when the learner is transacting the content, data will automatically be recorded for the time spent at various sections. With permission granted to record facial expressions, there will be very useful data that indicates the level and nature of engagement with the content. The qualities of grit, perseverance etc. referred to by Paul Tough in his seminal work “ How children succeed” can now be observed and analysed quantitatively. Drawing on groundbreaking research in neuroscience, economics, and psychology, Tough shows that the qualities that matter most have less to do with IQ and more to do with character: skills like grit, curiosity, conscientiousness, and optimism.

To help with his class the spring of 2016, a Georgia Tech professor Ashok Goel, hired Jill Watson, https://youtu.be/Y3t-3YeY0sc a teaching assistant unlike any other in the world. Throughout the semester, she answered questions online for students, relieving the professor’s overworked teaching staff. But, in fact, Jill Watson was an artificial intelligence bot, based on the same IBM Watson technology that defeated the human champions in 2011 in the game of Jeopardy. 

Ashok Goel, a computer science professor, did not reveal Watson’s true identity to students until after they’d turned in their final exams.

With more human-like interaction, we may expect online learning could become more appealing to students and lead to better educational outcomes.

Just as professors may use AI as teaching assistants, students could use a chatbot to facilitate individual mastery learning. 

AI and related technologies can help bring the Oxford/ Cambridge tutorial system to any University that chooses to adopt it. While a good deal of the teaching in Oxford is provided in just the same way as elsewhere – through lectures, seminars, fieldwork and practicals – the tutorial system is what sets Oxford (and Cambridge!) apart.

Universities in future could have a physical campus as well as a campus “in the cloud”. Former faculty and graduated students can continue to take part in the “cloud events” when they have left the Campus. 

Universities will continue to support their students with lifelong learning even after they have received their degrees so that they continue to, in the words of Alvin Toffler, learn, unlearn and re-learn. In addition to the traditional degrees, such micro-credentials may be given as ‘digital badges’, which in due course may be managed as ‘ Blockchains’. 

In about a decade from now, the impact of the science of learning empowered with Artificial Intelligence will be seen on many features of the present educational landscape that we take for granted. Every student would have access to the best education in the field of choice, in a time schedule that is optimised for the learner. It is extremely tough to determine as to which teaching method resonates with most of the students. A well designed tutoring programme, with the help of Artificial Intelligence and Machine Learning, can overcome this roadblock in the swiftest possible manner. As a matter of fact, a few tutoring programmes based on AI are already in place and they cater to students across different levels and subjects, such as science, mathematics, writing etc. Though such systems and programmes are not that effective when it comes to high-order creativity, they are extremely efficient for clarity on fundamentals and concepts.

The current state of assessment of learning:

Of the various formats of questions that are used for assessments, multiple choice questions, fill in the blank or match entries from 2 columns are easily capable of being automated and evaluated with traditional ( non AI) computers. Not only can a large number of students be graded automatically, the items can be evaluated on features such as facility, reliability and discrimination index. With good quality items for the bank of questions, it is relatively straightforward to implement an adaptive testing system.

The essay type questions are a formidable challenge to automated machine testing. But recent developments in machine learning, have made grading and assessments of essay type questions possible. 

This is also a time that shows up the irrelevance of the monolithic terminal examinations. Sir Anthony Seldon in his 2018 book “ The fourth education revolution” has analysed why such examinations will no longer be relevant. Sir Anthony, Vice-Chancellor of the University of Buckingham, added that continuous assessment would sound the death-knell for exams: “The all-conquering cumulative exam is going to die and we should celebrate its death…The monolithic exam is drawing to a spluttering end.”

Micro-credentials are one of the hot rising ideas in the education space. The root of the idea is simple–you demonstrate a very specific skill, and a badge certifying that micro-credential becomes part of your personal digital file. Some of the earliest micro-credentialing involved computer programming skills, but it has grown far beyond that. To see just how many types of micro-credentials are out there, take a look at Digital Promise :  https://digitalpromise.org.  It offers micro-credentials of its own, but it also provides a platform for other entities to offer their own sets of micro-credentials.

To answer the question of what is worth learning, we need to balance between ‘pure’ learning and ‘applied learning’. The Usefulness of useless knowledge by Abraham Flexner, founding Director of Institute of Advanced Study Princeton: https://www.brainpickings.org/2012/07/27/the-usefulness-of-useless-knowledge/. There are many reports that refer to the decreasing half-lives of useful knowledge. 

From the apparent uselessness of certain types of knowledge, Yuval Noah Harari went on to propose the emergence of a useless class, as a result of workplace automation : https://youtu.be/OMDlfNWM1fA

The antidote to becoming a part of the useless class is to become invaluable, the Ubermensch as espoused by Frederich Nietzsche . And it is indeed possible to Become invaluable , not useless : https://mmpant.com/binu/

Teacherless Learning : 

Thomas Frey, a futurist foresees an AI-enabled ‘ teacherless’ learning system in about a decade or even less: https://youtu.be/McV9AMV2LiI

But as William Gibson wrote  in the Economist in 2003: “The future is already here- it’s just not evenly distributed.” 

 École 42, is a teacher-less coding school first opened in 2013 in Paris, and now in Silicon Valley as well. The model has been adopted across the world. 

To have an experience of what AI can already do for language learning, please explore Duolingo.com. See : https://venturebeat.com/2020/08/18/how-duolingo-uses-ai-in-every-part-of-its-app/

Robots that can help you learn English : https://herobot.app/messenger-chatbot/learn-english-without-any-judgment-with-a-robot-to-talk-to/

AI for improving English : https://mmpant.com/ai4english/

When Computers were human: 

The term “computer“, in use from the early 17th century (the first known written reference dates from 1613),meant “one who computes”: a person performing mathematical calculations before electronic computers became commonly available. 

Teams of people, often women from the late nineteenth century onwards, were used to undertake long and often tedious calculations; the work was divided so that this could be done in parallel. The same calculations were frequently performed independently by separate teams to check the correctness of the results.

Computers weren’t always made of motherboards and CPUs. At one time, they were human! And at NASA’s Jet Propulsion Laboratory, human computers were a talented team of women who went on to become some of the earliest computer programmers. 

These workers were neither calculating geniuses nor idiot savants but knowledgeable people who, in other circumstances, might have become scientists in their own right. 

“When Computers Were Human”, a book published in 2007 by David Alan Grier ( whose grandmother was trained as a human computer) gives an in-depth account of this little-known, 200-year epoch in the history of science and technology.

These are already several educational applications that harness the power of AI to improve learning in students of all ages – from primary school through to college – and empower both learner and teacher with more avenues for reaching their educational goals.

These should be seen not as the best that AI can do, but as illustrations of the enormous activity in the field, and to form the view that this is not far away. A co-operative symbiotic pursuit by educators and technology developers may achieve AInEdSupremacy in a short time, possibly by July 2022, when we will be celebrating India@75. Around the same time, someone who grew up in the recent past, and whose mother and grandmother were teachers, may write a book “ When teachers were human”……or who knows it may be a successor of GPT3 that would do it, if humans begin to find such book writing not worthy of their evolved human intelligence.