Truth, Lies and Enlightenment: how AI can help us to build knowledge and understanding in the echo chambers of life

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.

More relevant than ever…Information plenty, but knowledge famine: are we succumbing to an illusion?

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 wrote thsi piece originally for  Learning to Live – Creativity, Money and Love

Will Artificial General Intelligence (AGI) cope with ‘messy’ real world learning?

I was catching up with reading my weekend papers and came across the Observer Tech Monthly profile of Demis Hassabis, the founder of DeepMind. I have never met Demis, but the Observer piece echoes the descriptions I have been given by those who do know him. He is incredibly bright and also extremely modest: a nice ‘ordinary’ North London guy. I feel comforted that someone like this is at the forefront of our efforts to extend the boundaries of Artificial Intelligence (AI) and the achievements of DeepMind are certainly impressive. However I am less convinced about the real potential of Artificial General Intelligence or AGI, especially when it comes to its application to education.

download2I can buy into the vision of a world where smart people work with smart machines to solve wicked problems, such as cancer. And I can see that there is indeed too much information for many of us humans to process, so some artificially intelligent help would be great. I like the idea that AGI will “automatically convert unstructured information into actionable knowledge…. to provide a meta-solution for any problem” But that’s where it falls down for me, I can’t believe that the structured knowledge will be applicable to any problem.

IMG_8934The reason I hold this view is twofold. Firstly, much of the knowledge that helps us negotiate our way through the world is highly contextualized. There is significant evidence that a learner’s context impacts significantly upon their learning process and that in essence each individual person has his or her own individualized learning context. Secondly, teaching and learning in the real world provides extremely messy data. It’s this very messiness in teaching and learning settings that is crucially important. Partly because one never knows if what appears to be mess is actually important for learning. For example, a disagreement between two children will probably upset at least one of them and that in turn will impact on their learning. I would need to see some clear examples of contextualized AGI (is that a contradiction in terms?) and its propensity for messy real world learning settings to be convinced that AGI for education is a way forward.

hero-learning-pathsIt’s not just DeepMind whose remarkable systems are not to my mind suitable to take over education. I was on a panel with Jose Ferreira CEO of Knewton last month and it became clear that Jose believes that Knewton is smart enough to play the role of a teacher. It certainly is impressive technology. However, Knewton relies upon ‘clean’ data and that is not what classrooms are like. To my mind the most likely outcome for AI within Education is not for AGI, but for AI components to provide teachers with a selection of smart tools that teachers can use with learners as and when they think it appropriate. It really is the smart combination of Human and Machine intelligence that will win the day.

artificial-intelligence-job-killer-or-your-next-boss

Superfast Britain – buy your shiny new learning here?

The Economist Intelligence Unit releases its report on Superfast Britain? Myths and realities about the UK’s broadband future today and has selected Education as a key area of interest. This is a balanced report that does not promote an unrealistic hype about the possibilities offered by superfast broadband. With respect to Education, the report concludes that “superfast broadband can be used to support educational transformation, but will not bring it about on its own”. This is a key point – it is not the existence of super fast or super fat broadband alone that makes the difference, what matters are the possibilities afforded when such infrastructure is combined with human enterprise and a landscape of consumerized technology in which  almost everyone has a potentially sophisticated learning device in their hands or homes:TV, phone, or tablet.

Jon James MD BroadbandVirgin Media made an interesting point yesterday evening at a dinner to launch the Economist report. He noted that when selling Broadband, speed was not something that customers necessarily found enticing. He suggested that one useful way to think about what people want to buy is that they want to ‘buy the internet’. This makes one wonder then what the combined package of fast and efficient infrastructure, plus sophisticated devices for all will enable companies to sell and people to believe they are buying? Will people believe that they can ‘buy learning or knowledge’ in the same way that they can buy the internet?

This is different from buying an application to teach maths or visiting a website full of resources about science, or joining Khan Academy, it is about the extent to which people may believe that they can ‘buy learning’ as a commodity in the same way that they ‘buy the internet’.

Working out if you have been successful in buying the Internet is simple, you either have or you haven’t got on-line, and you can finesse that by noting how quickly you can stream or download those big FAT videos. But, how will people know if they have succeeded in buying learning? The key commodity we might usefully be ‘selling’ at this point in time are the skills and knowledge that will enable people to make accurate and useful assessments about what they do know and understand, and what they still need to learn.

 

Are we too disciplined to make ourselves understood?

One of the wonderful things about being an undergraduate in the School of Cognitive and Computing Sciences (COGS) at the University of Sussex was the interdisciplinary experience that was embedded within our studies. When I studied Computer Science and Artificial Intelligence I did so within a community of philosophers, psychologists, linguists and computer scientists and it was great. This has given me a particular perspective on all the work I have subsequently been involved with – all of which has sat on the ‘fault lines’ between disciplines. As I am currently pondering how best we might improve the way that we academics communicate what is valuable about the research that we have and are doing about technologies for learning I realise that the communication problem is more deeply rooted than the ‘external’ communication challenges of making our research relevant and impactful, we often don’t communicate effectively within academia across disciplines. So, if we can do better at engaging with each other outside of our disciplinary comfort zones, then maybe we can also set our minds to finding a way to help those outside academia understand the complex landscape of researchers whose work might really help to enable a step change in the quality of the technology and its use for learning.

If we take a quick look at the sorts of research that might be relevant to people working in industry to develop technologies to support learning, from smart phone apps to learning platforms and interactive whiteboards, and to practitioners and learners both within and without educational institutions, there are many different research communities who might feel they have something interesting to offer. For example, there are computer scientists who develop the algorithms that drive the software that makes a technology capable of particular behaviours and the engineers who build the hardware that enables features like touch sensitive interfaces, drag and drop icons and multimedia output. There are the interdisciplinary researchers in Human Computer interaction who understand how to design interfaces to support the optimal types of interaction whether on an interactive table top, a virtual reality or an ipad. There are research communities that use artificial intelligence methods and techniques to design computer models that can enable software to adapt to the particular learner or learners who are using it so that a game or a simulation can interact in a manner that is tailored to its users needs, whether teachers or learners. Then there are the psychologists who understand how people learn and the sociologists who understand about communities and social interactions, and the social scientists who understand about educational systems and human relationships. Here I am only scratching the surface and there will be as many research communities and disciplines I have omitted as those that I have named. These communities largely publish their work in separate journals and at separate conferences. There are attempts to develop interdisciplinary communities in order to try to encourage cross fertilisation of ideas and appreciation of the contribution that different expertise can make to shared problems, although the well documented demise of COGS illustrates the power of the bureaucratic penchant for administrative neatness. These interdisciplinary communities are not the norm and at times of austerity there is a tendency for funders to concentrate on their core disciplines, which has a knock on effect upon the extent to which researchers are able to work across the disciplinary boundaries.

Let’s talk about what the research says: Industry, Academia, Learning: 7 days to go

Vanessa Pittard DfE, Richard Noss TEL Research Programme Director, BESA, Intellect, ALT, and Demos about research inspired technology enhanced learning to tackle challenges from teenagers’ energy consumption to social communication in a multimodal virtual environment for youngsters with Autism Spectrum Disorders. What the research says event at LKL now has a waiting list for places! Clearly people do want to talk.

Speak to Me

Industry, Academia, Educators and Learners: It’s good to talk, but why are we all ‘telephobic’?

In my last post I suggested that to improve learners’ experiences we need research, industry, practitioners and learners to work in harmony, and that this is hard to orchestrate. But why is this hard to orchestrate?

A large part of the reason is that each of these communities ‘speaks a slightly different language’, because whilst they are motivated by some common interests, such as finding ways to help people learn more effectively or enjoyably, they are also motivated by different and in some ways competing factors. To be honest they don’t have a great track record of talking to each other.

Practitioners and learners are the key players in the interactions that support learning, when they work in sync with the right support from technologies developed with and by industry and informed with and by research they can achieve their best. BUT this does not happen as often as it could in the area of Educational Technology and Technology Enhanced Learning.

Why? Perhaps it’s partly because industry works in quarterly cycles with an eye on the ‘bottom line’ and a need to maintain the competitive edge over rivals in order to hold on to or increase market share. It needs to know what will sell when it comes to developing technologies to support learning and what will help to keep employees in work and products on people’s shopping lists. It would often like to develop products informed by research, but with the exception of large industries that have their own research labs, may not know how and when to find the right people to offer that research advice. Researchers are concerned with rigour and clarity, and very rarely think about a year in quarters, more likely in semesters and terms. Their eye is rarely on the bottom line and the results of their endeavour often take a considerable length or time to mature and reach fruition. With a greater imperative to demonstrate the impact of their research as part of the next REF exercise (the system for assessing the quality of research in UK higher education institutions), they may well very much like to find a way to work with industry to take their ideas into a wider community and see how they can be applied. However, who do they talk to and how do they communicate what they know? For most academics they have been well-trained in the art of writing journal articles for approval and acceptance by their peers. But, this type of output is rarely very accessible to people who don’t speak that same academic language.

So why does all this matter? It matters, because the problems we face when it comes to developing the kinds of technologies that can solve the really big educational problems and take advantage of the widespread ownership of powerful communities cannot be solved by any one community on their own, so we really do need to get together and talk about how each community can offer their own contribution to a shared endeavour. In order to do this we need to find a way to understand enough about how each other works to be able to build effective conversations.

As many a famous actor has once said on behalf of BT – “its good to talk”, but you need to know the right number to ring and the right shared language to speak if you are going to have any chance of communicating in any meaningful way. So how can we engineer the circumstances in which such vital communication can take place?

Understanding you, Understanding me: is this the best we can do?

The wide-spread ownership of sophisticated computing devices such as smart phones and ipads allows mass access to social media, augmented reality and 3D virtual world applications. BUT are we making the most of these technologies to help learners communicate using all their senses? These technologies make it technically possible for people to share information about themselves and their contexts using multiple media and multi-sensory communication. This ought to mean that learners who may struggle with traditional text and image can explore new ways to express themselves. New ways to communicate what they do and don’t understand and new ways to allow others to understand more about their particular context and perspective.

One of the essential ingredients for effective learning  where a more knowledgeable person, such as a teacher, is helping a less knowledgeable person (or people) to learn something is that both of them share some common understanding of what the less knowledgable person currently understands. The technical possibilities for multi modal communication offered by emerging technologies should provide new ways for people to share their understanding and misunderstanding and to communicate important aspects of their personal context that may help teachers, parents, and friends to  provide more effective support. But are we making enough of this potential?

I suspect we are not. To tackle challenges such as, developing a clearer understanding of how we make the most of such communication possibilities requires research rigour and energy. To develop technologies and applications that make these new formats for communication and interaction easier and effective we need industrial enterprise and innovation. To understand the needs of learners and teachers, we need to bring them into the research and design process. Most importantly of all, to improve learners’ experiences we will need research, industry, practitioners and learners to work in harmony, and that is hard to orchestrate.