The title of this article is inspired by a self-help book from the 1990’s called ‘Who moved my Cheese: An Amazing Way to Deal with Change in Your Work and in Your Life’. I have blogged about this book before and this motivated me to write this piece for WISE. Despite significant criticism, this book became a best seller and a popular tool in any change manager’s back pocket. The implications of Artificial Intelligence (AI) and automation for change in the future workplace is the subject of much current debate. But how should educators respond? How can they ensure that they benefit from AI?
AI refers to the capabilities of computers to perform intelligent behaviours that we would think of as essentially human. Most readers will be familiar with a practical application of AI, the sort of technology we use to navigate information on the internet, find our way around our environment or enter a country with our e-Passport. But what does the increased popularity and the increasing sophistication of AI technology mean for education?
To answer this question, I focus on two interpretations of the question: ‘Who moved my Intelligence?’. Interpretation 1 considers how we need to ‘move’ our students’ intelligence beyond the routine cognitive processing of academic subject matter. Interpretation 2 will consider what ‘moving’ certain intelligent workplace behaviours from human performance to AI performance means for educators, including for the job of teaching.
Developing the uniquely human abilities of students
Education and training organizations need to review what and how they teach to ensure that AI is designed and used as a tool to make our students and trainees smarter. We do not want AI to be used as a technology that takes over human roles in a way that ‘dumbs us down.’ We therefore need to concentrate on designing and implementing teaching and schooling that develops the uniquely human abilities of our students and instills within them the requisite subject knowledge in a flexible, interdisciplinary and accessible manner.
The human capability for Metacognition, both in terms of self-understanding so that each of us has an accurate knowledge of what we do and do not understand; and self-regulation so that we can all plan and monitor our learning effectively, will be at a premium in the future workplace. This is because metacognition is not something that AI can achieve, and because we will all need to be lifelong learners flexibly developing our knowledge and skills to meet the demands of the future, we will all therefore need to develop better metacognitive skills.
The use of teaching approaches such as Collaborative Problem Solving (CPS) will become more essential. CPS has been shown to have the potential to provide learners with an understanding of key subject knowledge synthesized across disciplines that they can apply in a flexible manner to real world problems. Collaboration and problem solving are also among the key 21st century skills demanded in the modern workplace, because routine cognitive skills and knowledge are easy to automate with AI.
The curriculum will also need to include AI as a subject, not merely to teach a small sub set of the population to design and build AI systems, but to teach the whole population what AI is and what it can and cannot do. Everyone needs to understand enough about AI to be able to use it effectively in their lives at work and at home, to be able to contribute to important decisions about what is and is not ethical and permissible for an AI to do, and to be able to make decisions about the division of labour between artificial and human intelligences.
Re-imagining teaching and schooling
There is no doubt that there will be a shift in the distribution of intelligence within the workplace, including classrooms and schools. In order to extract the most benefit from this redistribution, we need to ensure that the most automation-appropriate activities are done by the AI, and likewise that the most human-appropriate activities are done by people.
Re-imagine teaching and schooling with AI assistants to provide intelligent analysis of multiple data sources about learners, from sleep sensors, library usage and e-learning resource interactions, to social media activity. This analysis will illustrate how learning is progressing to support ongoing detailed formative assessment. AI assistants could also relieve teachers from the routine automatable parts of their job, and enable teachers to focus on human sensitive support and communication.
 (2005). ODE: The Oxford dictionary of English (Oxford dictionaries online). Oxford: Oxford University Press. AND Russell, S. J., Norvig, P. & Davis, E. Artificial intelligence: A modern approach. Upper Saddle River: Prentice Hall.
Who could be anything but delighted to see this headline? A-level results: Malala Yousafzai gets a place at Oxford, this is excellent news and a great boost for those campaigning for equal education. In fact, the publication yesterday of A level results in the UK has spurred me to take a slight diversion from worrying about who is moving my brain or my cheese. I certainly would not want to detract from the hard work that any students have put into their A level studies or to take the shine off their success. It is wonderful to see the smiling faces of successful students across the newspapers.
However, success does not come to all and even on a celebration day, or perhaps I should write especially on a celebration day, I think we need to consider alternatives to the stressful stop and test regime that pervades most education systems. I wrote about this in Nature Human Behaviour earlier this year under the heading: ‘Towards artificial intelligence-based assessment systems’ and it looks like it has been read a few times because it is ranked 5,746th of the 237,966 tracked articles of a similar age in all nature journals which puts it in the 97th percentile. This does not seem bad given that it was only a ‘comment’ piece and not a full paper. On a less positive note in an internal REF assessment exercise it was only ranked as 2*, which is not great and probably reflects the difficulty for academics in publishing more popular style articles. However, the modest success of the article in terms of the altometrics that Nature run encourages me to believe that there is some interest in exploring the possibilities that the intelligent design and application of AI could afford for National assessment systems. I therefore draw attention to this possibility here and hope to encourage further debate. The key point I wanted to convey in the Nature Human Behaviour article was that there are alternatives to exams, that are less stressful, less expensive and that allow teachers and learners to spend more time on teaching and learning (shouldn’t this be the point of education?).
This message may not be what others have selected to focus on, but for me, the most important thing is that we have an assessment system that is holistic, fair and that let’s all students evidence their knowledge, skills and capabilities.
I’m pleased to report that my ankle is progressing well and I am now once again able to achieve my ‘misfit‘ challenge of 1000 activity points per day: clearly it is a good job I was only mildly curious. However, I want to be more than mildly curious when it come to my intellect, and I want to do this without injury. I had therefore better take care, both of my own intellect and of the intellect of those I am trying to encourage to be appropriately curious. I therefore return to my thoughts about what a useful self-help book to prepare people for their AI augmented futures, might be like. To this end, I also return to ‘The AI Race‘ and specifically to the man behind the survey that was used to calculate how much of different people’s jobs are likely to be automated.
Andrew Charlton is his name and he is economist and director of AlphaBeta, an economics and strategy consulting firm. He did not beat about the bush! AI will impact on ALL jobs and he encouraged the TV audience to embrace AI. His ‘top tip’ was that we must carefully manage the transition from now to the situation when widespread AI augmentation will be common place.
He was clear that we must take advantage of what AI has to offer by increasing the diversity of our own skills sets. He saw AI as an “Iron Man Suit” for humans. This suit would transform us mere humans into super humans. This is a great analogy, who would not want to be super human? BUT embracing AI augmented working is not as simple as putting on a new outfit – especially an iron outfit. And increasing the diversity of our skill sets requires educators and trainers who are themselves skilled and trained in developing these new diverse skill sets. BUT where are these educators and trainers to be found? Who is helping the educators and trainers to gain the skills and expertise they will need to train their students in?
Andrew has little comfort to offer here. His next comment about education is that 60% of the curriculum that students are studying at school is developing them for jobs that will no longer exist in 30 years-time. We need to re-design the curriculum he advises. So educators need to re-skill themselves as well as their students, and they need to revise the curriculum. Clearly educators will be busy! And clearly there will also be a significant job to be done in (re-)motivating all those students who discover that they have been learning stuff that nobody will want them to know by the time they are looking for a job.
Now we hit the nub of the matter, education and educators must prepare students for the new AI order of things. Educators lives are going to change in significant ways NOT because their roles are likely to be automated away BUT because they will need to teach a different curriculum and probably teach in a different way. To make matters worst: there is no clear consensus from the experts about exactly which jobs educators will need to educate people for. I think educators may be the most in need of a good self-help book to help them cope with the inevitable changes to their lives.
The original book called ‘Who Moved My Cheese’ was a story featuring 4 characters: two mice, called “Sniff” and “Scurry,” and two little people, called: “Hem” and “Haw.” These 4 characters all live together in a maze through which they all search for cheese (for cheese think – happiness and success). Their search bears fruit when all of them find cheese in “Cheese Station C.” “Hem” and “Haw” are content with this state of affairs and work out a schedule for how much cheese they can eat each day, they enjoy their cheese and relax.
“Sniff” and Scurry” meanwhile remain vigilant and do not relax, but keep their wits about them. When horror of horrors there is no cheese at Cheese Station C one day, “Sniff” and Scurry” are not surprised: they had seen this coming as the cheese supply had diminished and they had prepared themselves for the inevitable arduous cheese hunt through the maze and they get started with the search together straightaway. In contrast “Hem” and “Haw” are angry and annoyed when they find the cheese gone and “Hem” asks: “Who moved my cheese?” “Hem” and “Haw” get angrier and feel that the situation they find themselves in is unfair. “Hem” is unwilling to search for more cheese and would rather wallow in feeling victimized, “Haw” would be willing to search, but is persuaded not to by “Haw”.
While “Hem” and “Haw” get annoyed, “Sniff” and “Scurry” find a new cheese supply at “Cheese Station N,” and enjoy a good feast. “Hem” and “Haw” start to blame each other for their lack of cheese. Once again “Haw” suggests they go and look for more cheese, but grumpy “Hem” is frightened about the unknown and wants to stick with what he knows, he refuses to search. However, one day “Hem” confronts his fears and decides it is time to move on. Before he leaves “Cheese Station C” he scribbles on the wall: “If You Do Not Change, You Can Become Extinct” and “What Would You Do If You Weren’t Afraid?” He starts his trek and whilst he is still worried, he finds some bits of cheese that that keep him going as he searches. He finds some more empty cheese stations, but also some more crumbs and is able to keep hunting. “Haw” has realized that the cheese did not simply vanish, it was eaten. He is able to move beyond his fears and he feels ok. He decides that he should go back to find “Hem” equipped with the morsels of cheese he has found. Sadly, “Hem” is still grumpy and refuses the cheese morsels. Undeterred, though somewhat disappointed, “Haw” heads back into the maze and a life of cheese hunting. He continues to write messages on the wall as a way of externalizing his thinking and in the hope that “Hem” might one day move on and be guided by these messages. One day “Hem” finds Cheese Station N with all its lovely cheese, he reflects on his experience, but decides not to go back to “Hem”, but rather to let “Hem” find his own way. He uses the largest wall in the maze to write the following (original to the left, my re-interpretation to the right):
Who move my cheese?
Who moved my brAIn?
Change Happens: They Keep Moving The Cheese
Computers keep getting smarter and intelligent tasks are moving from human to machine
Anticipate Change: Get Ready For The Cheese To Move
Prepare for some of your intellectual activity to be taken on by AI
Monitor Change: Smell The Cheese Often So You Know When It Is Getting Old
Keep checking in on your own intelligence and make sure you are really using it and keeping it fresh
Adapt To Change Quickly: The Quicker You Let Go Of Old Cheese, The Sooner You Can Enjoy New Cheese
Adapt to change thoughtfully (quickly is not necessarily right here), make sure you offload intellectual activity carefully so that you maintain your human intellectual integrity
Change: Move With The Cheese
Move with the intelligence (both human/natural and machine/artificial)
Enjoy Change!: Savor The Adventure And Enjoy The Taste Of New Cheese!
Enjoy intelligence and the experience of your developing greater intelligence – being smart ‘tastes good’!
Be Ready To Change Quickly And Enjoy It Again: They Keep Moving The Cheese
Never feel you are intelligent enough and keep striving for intellectual growth
“Haw” is never complacent and continually monitors his cheese store and searches through the maze and hopes that one day his old friend “Hem” will find his way through and that they will meet again.
Whilst the book “Who moved my cheese” was extremely popular, it was also the subject of considerable criticism. For example, that it was too positive about change, that it was patronizing and compared people inappropriately to ‘rats in a maze’. BUT can I learn anything from this as I try to encourage people to want to understand themselves and their changing intellectual capabilities?
I think there is still value in “Haw’s” writing on the wall and I have tried to clarify this nee value for AI in the right hand column of the table above. I also think perhaps that my original revised title of: “Who moved my brAIn?” is not quite correct. The more important question is “Who moved my intelligence?”.
As a child I was always frustrated by the phrase: “curiosity killed the cat”. This was a frequent retort when I was trying to understand how things worked. Well, I am not reporting any cat killing incidences here, but my curiosity about myself driven by my new ‘misfit’ may have been a primary factor in my newly sprained ankle!
Over enthusiasm to meet that target of 1000 activity points motivated me to get walking and launched me down some steps in a most ungainly and unfortunate manner. No broken bones, but some swelling and plummy bruising have resulted in my needing to rest up for a few days. Resting up in a Sydney winter is hardly a chore, the sun is out and the sky is blue and I indulged in exploring the ABC TV channel and in particular a great program called The AI Race.
The program presented data from a study into the risks to Australian jobs from AI powered automation. I was relieved to see that professors are only likely to have 13% of their job automated, whilst carpenters are predicted to have 55% of what they do done by smart technology. Might this be the same in the Uk, or different I wondered? The ABC reporter explored various jobs and met up with employees. For example, Frank: a truck driver, was not persuaded that autonomous trucks would be able to replace his experience and intuition about the behaviour of other humans whether pedestrian or driver. The autonomous vehicles would not be able to help out other drivers stranded on the roadside or provide human customer service on delivery of a load either. He was definitely not convinced that AI was going to replace him any time soon.
Further jobs were explored: the legal profession for example where law students were stunned by an AI para legal that could search through thousands of documents to find a specific clause in no time at all. The law students berated their education for not preparing them for a world of automation.
On the one hand we have Frank, who does not believe that AI can replace him, and on the other we have a group of law students who are persuaded that AI can already do a lot of what they are studying to be able to do. Nobody seems very curious about how they might better prepare themselves for AI’s onslaught on their workplace. So, how might I persuade them that understanding more about their own intellect could help them work more effectively with AI? The key to future success has to be that people need to focus on developing the expertise that AI cannot achieve: the still unique human qualities that will be at a premium. Self-knowledge and Self-efficacy are important elements of this expertise, but how do we motivate people to develop themselves? To start answering this, I looked at the best selling self-help books for guidance. People buy these so maybe I can learn something about how to appeal from their sites – which of these might work best?
It is far too long since I last posted to this blog: too many jobs and too little time would be my fist attempt at an excuse. But, perhaps it is just that I am not effective enough, that I need better self-regulatory skills, more intelligence and a better understanding of my own strengths and weaknesses. I talk quite a lot about intelligence and about how AI developers have not yet designed artificially intelligence systems that understand themselves and have metacognitive awareness, but maybe I too lack these abilities? So, how might I become more self-effective?
This thought is one that I intend to worry at while I am completing a research trip to the University of Sydney to work with my colleague Judy Kay. We are working on Personal Analytics for Learners (PALs), or more precisely interface designs for PALs (or iPALs).
In order to help me thing this through I wanted to learn more about some of the work that Judy and her colleague Kalina Yacef have been doing in collaboration with medics and health professionals to develop better data analytics and interfaces for personal health information for education. For example, the iEngage project provides a digital platform for children with information, education and skills to help them to achieve their physical activity and nutritional goals. It connects with ‘misfit‘ activity trackers to provide continuous feedback and summarise the daily activity on a dashboard.
To this end, I bought myself a ‘misfit’: a somewhat cheaper version of a ‘fitbit’ with a great name :-). I am now tracking my sleep and my pulse as well as my physical activity and diet in order to try and understand more about my personal wellbeing. This is nothing new and millions of other people do this too. I notice that popular technology stores stock a good range of fitness tracking devices and increasingly more reasonable prices.
So, in order to also help me be better at understanding my mind and my cognitive progression and metacognitive skills and regulation, I now need a ‘mindset” to help me track how well I am thinking, learning and regulating my working and learning. The interface to such a ‘mindset’ is the idea behind the iPAL that Judy and I are currently designing. I find it interesting to speculate about the kinds of data that we could collect about our intellectual and social interactions that would help us track and better understand our intellectual mental wellbeing as well as our physical welding and fitness. This kind of ‘fitbit’ for the mind might help me to be less distracted by non-priority activities and spend more time on priorities, such as writing.
A search for ‘fitbit for the mind’ yields some hits, though not terrifically interesting ones. There is an article in new scientist about eye-tracking to tell you more about your reading habits, and a mindfulness app that can be linked to fitbit data. The problem here is that we are being offered some automatic tracking of just one type of mental activity – reading, or mindfulness and actually we need something way more sophisticated to tell us about how we our intelligence and self-awareness is progressing. Perhaps something that looks at multiple data sources and provides us with an overview of our activity in a way that motivates us to want to know more about our intellectual fitness in the same way that activity trackers help us understand more about our physical fitness.
Earlier this month, there was a more interesting article in Newsweek that talks about ‘iBrain’ and the possibility for us to be able to track our brain’s electrical output and see markers for the likely occurrence of a range of mental health disorders from anxiety, depression, and schizophrenia, to dementia and Alzheimer’s before symptoms appear. Such information might help early intervention and monitoring. This reminds me of the rise of personal DNA services, such as 23 and me. If people are interested in their DNA and what it might tell them about how they should adjust their lifestyles to avoid certain conditions that they look to be susceptible to, then maybe people are also curious about their intelligence and how they can understand it better.
Over the next few blog posts I plan to explore what such a device might be like, what data it might collect and how I might best benefit from the sorts of information it could provide.
AI is both a cause and a solution to the problem of a world where there is far more information than any one person can possibly effectively process to construct their own understanding about what they believe and what they don’t. AI can amplify the echo chamber by promoting the most believed over the most evidenced. BUT it can also help us to recognize valid information from noise, IF we know the right questions to ask and IF WE KNOW HOW TO WORK WITH OUR AI we can develop deep understanding and escape from the maze of invention…
Early in my career I was advised that if I wanted to get a point across when teaching, during an interview, as part of a presentation or when debating, I must repeat the point I wanted to make three times. There is an empirical basis for this advice: something eloquently explained my Malcolm Gladwell and the motivation for my blog identity: The Knowledge Illusion. Put simply, when people are provided with more information about X, they believe that they know more about X, when in fact they often know less about X. I wrote about this many blogs ago (transcribed below for ease of reference) to draw attention to the essential need to help people decipher the huge volume of information that comes their way so that they can discern what is genuine from what is fake.
I still follow the “say things three times” advice in my endeavour to communicate what I consider to be valid, some might say truthful, information. My objective is to persuade people that my perspective, opinion, or information presentation is the stuff to be believed. However, I accept that it is entirely up to my audience to decide whether or not they are won over. The importance of this subjective experience and the belief that an audience are actively analysing the information that comes their way is ever more important. In a world of echo-chambers and deluge of social media, we need people to be able to look at a stream of data and information and make intelligent decisions about what they believe to be the stuff of knowledge.
The problem is not new. It was JFK who once observed that “No matter how big the lie; repeat it often enough and the masses will regard it as the truth.” This is an enormous insult to the intelligence of the “masses”, but unless we pay attention to helping these “masses” to navigate through the morass of mediocracy that social media precipitates, proliferates and perpetuates then we will return to the pre-enlightenment era when the world was flat and knowledge was the privilege of those who knew how to decipher the written word and who acted as the mouth-piece for and the collective intellect of their communities: the “masses”.
The word “masses” is no longer widely used so let’s just refer to the “masses” as the people: the global human race whom education is intended to equip with the skills and abilities to think and make sense of the world and the information others produce about it. To consider what it is we need to do to help people to make sense of the world it is worth travelling even further back in time to the views of Roman Emperor Marcus Aurelius that: “Everything we hear is an opinion, not a fact. Everything we see is a perspective, not the truth.” We need to encourage a nuanced belief system where people are provided with the skills, confidence and resources to construct their own understanding from the tidal wave of data and information that threatens to engulf them.
Again, history can help to inform us. The scientific revolution set the stage for the age of enlightenment that transformed the human race and promoted the importance of reason. Influential thinkers like Bacon, Locke and Descartes paved the way for the likes of Voltaire, Kant and Smith. Life was so much simpler then of course, but the huge increase in what it is possible for an individual to try to understand and know does not discount the important role that influential thinkers can play.
The birth of the www and social media represent a new generation of publications that play the role of the encyclopedias and dictionaries in the age of enlightenment. BUT who are the key philosophers and scientists who can catalyze the popular debates in the way that the philosophers of the enlightenment did? Stephen Hawking would probably be high on the list of influential thinkers who many people (the “masses”) might be able to name. Who else?
Whilst the volume of information and data about the world has ballooned, the number of influential thinkers who can help people find their way to knowledge and understanding has may not have kept pace. Technologies that harvest the ‘wisdom’ of the crowd often promote the loudest shouters and the most-followed, rather than the considered and grounded reasoning of the real intellectuals. The demise of expertise has exacerbated the problem as professional predictions have failed to materialize…. Let’s just stop there for a moment.
Could the real problem be that we, the people, don’t know how to interpret expertise? We want simple answers when there are none to be had. In schools we still encourage the belief that rote learning and subject specific information of the type that can be reproduced by a single person when challenged with a standardized test sufficient. This outdated approach gives the impression that knowledge and understanding are way more simple than they really are. They encourage people to believe that there is a body of stuff that they need to learn and reproduce, and that if they can do this they will be knowledgeable. However, what we should be doing is ALSO encouraging people to constantly probe, prod, compare and conclude for themselves their understanding of the world so that they can apply this knowledge to solve the problems they encounter every day.
The surge of tweets that give the impression that meaningful things can be said in 140 characters is not always helpful either. There is certainly something to be said for trying to distil understanding into a short text — it is difficult and can test how much we really understand. However, the believe that a tweet can be the whole story in and of itself is misguiding. Knowledge and wisdom need to be worked at, by questioning, analyzing, aggregating and synthesizing to reach our own evidence-based beliefs about what we know and what we understand. Someone else’s tweet might start this process, but we have to finish it for ourselves.
Ai can help us to do the work here. AI can analyze and visualize complex data and information in order to literally help us see the ‘wood from the trees’. AI can be built to model human understanding and to justify the decisions and predictions that it makes. AI can explain to us how to complete complex activities, such as solving mathematical equations or managing a complex power plant. BUT Artificial and Human Intelligence must work together to help people extract the truth from the lies. We as humans must ensure that we know enough about what AI is capable of doing to ensure that we ask the right questions. We must learn to be discerning enough to challenge the AI when we are not convinced by what it is telling us.
This means that now more than ever we must educate the educators. Because educators must instill in us, the people, the investigative skills that we need to ask the right questions so that we can differentiate evidence from falsehood. Educators must encourage the confidence and self-efficacy in us that will help us believe our own minds. Educators must engender the perspective taking and integrative thinking that will enable us to work together to solve problems and to develop the influential thinkers we need now more than ever to enlighten us.
I am curious about knowledge, not in philosophical sense, but in a practical one. I worry about what it means to know something in a world that is increasingly complex, ill defined and interconnected: a world that demands that we develop, and that we ensure that our children develop, the knowledge capacity to solve the problems it manifests and those that we create.
The first recollections that I have of my own curiosity about knowledge date back to 1966 when I was eight years old and growing up in Manfred Mann’s semi-detached suburbia: dad, mum, older brother and me. My father was an aircraft engineer and my mother taught typing and shorthand to women whose working lives were about to be dramatically changed by the word processing power of the digital computer. My brother was 3 years older than me, and his lack of interest in formal education was causing my parents some concern. Their reaction was to invest in ‘knowledge books’, or at least that’s how they saw the children’s book of knowledge and the encyclopedia that now filled up the bureau bookshelf. To keep us up to date, there was also the weekly general knowledge magazine that plopped on the doormat with a reassuring thud: the weight of its knowledge there for all to hear.
I suspect that my parent’s reaction to their son’s educational malaise was not an unusual one amongst the aspiring middle class families of our neighbourhood. My brother’s reaction to the new literary arrivals was cool; he was far more concerned with exploring the world of the woodland around our housing estate, than with sitting at home and reading about it. My father however, became quite addicted to the weekly general knowledge magazine. He did not have a great deal of time to read, but each evening when he went to bed he would sit in his paisley pyjamas and thumb through the pages. The stock of copies soon grew on the nightstand as his pace of reading failed to match the frequency of their arrival. The corners became slightly curled as the months and years passed and the dust gathered in and around the pile that now extended from the nightstand to the floor. His interest never waned and I do believe there were a pile of old issues by his bedside when he died many years later.
Forty years on and it’s a sunny day and I’m walking along the Euston Road in London. I pass the entrance to the British Library and a sign catches my eye, the sign says: “Step inside – Knowledge freely available”. I dislike the suggestion that one can walk into the British Library and just pick up some knowledge like going into Tesco and buying some bananas. I can relatively quickly formulate an explanation for myself about why the sign irritates me, because I have a clear idea about what I believe knowledge to be. I have moved on from the conception of knowledge loved by my father and represented by the pages of his books and articles. I know that I have to construct knowledge from the evidence available to me, that it is not handed to me by others, though they can certainly help me along the way, and that I can aspire to continually increase my knowledge by weaving together the information resources distributed throughout my world.
This is not the case for many of the youngsters who attend our schools and colleges. For them knowledge is still to be found in the dusty concepts in the out of date magazines on my father’s nightstand or on the shelves of a library they never visit.
“But what of the internet and world wide web?” I hear you wonder. These technological masterpieces offer information resources wherever we are and whenever we need them. These must surely pave the way for us to become more knowledgeable, both personally and as a human community?
The sheer abundance of this information has thrown into sharp relief our understanding of the relationship between information and knowledge. It makes my modest collection of childhood encyclopedias and my father’s overflowing magazine collection look like a speck of dust on the library shelf. I fear however that our understanding of what knowledge is and what it means to know something has not progressed in tandem with this technological progress. This puts us at risk of succumbing to the illusion that we know more than we actually do, because the more information we have the more we become certain that we know something.
Without helping young people to develop an understanding of what knowledge is in a digital age they cannot progress beyond the well meaning, but limited conception of knowledge promoted by the books and magazines that appealed to my parents. Those of us who understand what we mean by knowledge can indulge ourselves, as my father did with his magazines. But, without actively engaging people in the excitement of connecting the knowledge construction process to their own particular context, we merely encourage them to pass the opportunity by in the same way as my brother did all those years ago.
In a time of information plenty we are at risk of a knowledge famine.
I was struck yesterday by the juxtaposition of the Economist’s dubbing of Theresa May as “Theresa Maybe“and the Telegraph article authored by the PM about her desire for a shared society that will tackle “everyday injustices”. How exactly will the shared society work, and in particular in what ways will education be changed in order to achieve the worthy goal of a fairer society for all? I feel there is already a lack of decisiveness in the lack of detail about what kinds of policy will deliver this solution to the everyday injustices faced by many learners across all ages and sectors of education. (From an interesting article in the Huffington Post)
Education can change lives for the better, but sadly it often does not and those who are privileged are able to benefit from better opportunities for learning. So here is a suggestion for unlocking some of this inequality.
My colleague, Wayne Holmes and I were asked to write an article for ‘How we get to next‘ and we used this article to pitch the benefits of an AI classroom assistant to help and motivate teachers to ensure that all learners are involved in activities that meet their needs. We tell the story of Jude, a teacher in the year 2027.
“And at Jude’s side, there’s her AI Teaching Assistant, Colin, whom she’s named after a childhood friend. In fact, so many aspects of how Jude understands her students’ learning are different now, thanks to her machine aide.
Through working with Colin, she has become somewhat of a metaphorical judo master, harnessing the data and analytical power of AI to tailor a new kind of education to each of her students. Her role at the helm of the classroom, however, is fundamentally unchanged.
Since Colin makes ongoing assessments based on daily student performance and engagement in the classroom, there is simply no longer any need for what were often inaccurate and stressful evaluations. The AI aide’s primary task is to build and maintain learner models for each child based on a combination of data gathered over time with things like voice recognition (which identifies who is doing and saying what in a team activity) and eye tracking (to note engagement and focus). The profiles are updated continuously, monitoring students’ progress against analysis of their emotional and motivational state.”
I know that well designed AI can help us build a much fairer education system in which all learners benefit and prosper, and that we have the technical and human capacity to create the right type of AI. A better educated population would then surely help us to tackle some of the other major challenges that a shared society agenda might face, such as inequalities in the health system and problems related to immigration.