Thursday, December 30, 2021

Part 1: Philosopher of the Multiverse - Baudrillard

I have expressed scepticism around the relevance of Foucault, Lyotard and Derrida. Oft-quoted and rarely read, they are plucked from the Postmodern Hall of Fame and used by many to fashionably deanchor us from people in the past and present. But there is one French philosopher I have read all my life, who is very much an outlier - Jean Baudrillard (1929 - 2007). He has proved far more relevant as a philosopher, cultural theorist and prophet. Following on from my last piece on the Multiverse(s)...

How Metaverses develop

Neo, in The Matrix, carries a copy of Baudrillard's Simulacra and Simulations (1981) to make the point that the film is grounded in and a commentary on simulations. 

But The Matrix scene with its old-school computer discs inside the book seems rather dated now. The Multiverse(s) is a far more significant move towards the Baudrillian world of what he called hyperreality. As face-to-face and print media moved towards film and television, then online worlds, Baudrillard redefined media in terms of simulcra, or created entities that are no longer just representations but created realities in themselves, de-anchored from reality. These are not just digital media but worlds divorced from reality. He is, the philosopher of virtual reality, the man who envisioned and defined the Metaverse in its infancy, knowing what was to come.

Rather than seeing the world in terms of the old binary oppositions of appearance and reality, subject and object, oppressors and oppressed, he sees us as increasingly being in a world of Simulacra and simulations (1981) – ads, TV news and soap operas. With the Metaverse, we are literally moving into those worlds, inhabiting them, creating new economic models and economies within them.

He maps out the way in which this develops. Metaverses start first to reflect a reality, they then mask and pervert that reality and increase the absence of that reality, then finally bear no relation to reality. There is a brilliant passage in this book on Disneyland. You will never see that place in the same light after reading this critique of the US ‘embalmed and pacified’.

Astonishingly, all of his work was written in the era of broadcast media, before the internet. Now that his simulacra are being realised in computer games, social media, virtual reality, artificial intelligence and now Metaverses, he is more relevant than ever. 

Metaverses and meta-narratives

He rejects what other Postmodernists called meta-narratives, the Marxist and Freudian ideas of the free agent. But where he differs is in positing an alternative, replacing it in Consumer Society (1970) with a more complex agent as consumer and consumption,  not production, as the new locus of economic activity. The areas of economic activity are now simulated environments in the real world, in malls, with their perpetual springtime and shopping. We even buy these simulated ‘experiences’ even in what appears to be the physical world, such as Disneyland.

These new drivers have made us not producers but consumers, with a huge capacity for consumption. Credit literally fuels this excessive consumption by making the satisfaction of these desires easy and immediate. He goes much further in The Mirror of Production (1973), where the major elements in Marxism are demolished. Turning Marxism on its head, he restatess it as a justification for the very system it claims to destroy. With its focus on labour, production and value it lacks distance from the system, working within the mechanics of production. This focuses on the free economic agent rather than that of the consuming agent.

Baudrillard is also the philosopher of ‘consumerism’ which he thinks is now a refutation of ‘communism’. Rejecting the economic explanations of traditional Marxism, the actual world is now a complex nexus of consumerism, communications and commodities. Cryptocurrencies, NFTs, tradable digital entities in games worlds free float beyond Marxist materialism. People are no longer economic agents with a process of production, they are agents who consume and occupy hyperreal worlds. The fact that one of the largest, most valuable and globally pervasive companies on the planet has adopted this as their brand and goal confirms his view that physical production is no longer the essence of capitalism.

Metaverse and history

In The Gulf War Did Not Exist (1991) he shocked many, claiming that the war, as re-realised through media, had created a reality separate from the actual war. His deeper meaning was that when events become dislocated in this manner, history itself collapses through dilution. It moves us beyond an ‘event’ based culture to a non-historical state. Being stuck in the ever-present spectacle, we forget the past.

It is not just that such wars are now filmed, tweeted and YouTubed, many are almost immediately turned into movies and computer games. Dozens of movies now exist and I know of at least 18 computer games based entirely on, or containing, Gulf War events. Revolutions are no longer televised, they’re gamified.With 9/11 we saw this happen with even more intensity and reach, where the two perspectives of the event result in the clash of two separate and global worldviews.

Baudrillard’s position on all of this was brave and honest. He thought that this was almost inevitable. That we as a species will drown ourselves in our own simulacra, its all-consuming nature will smother and consume us. His only reaction was Nietzschean - silence. Baudrillard really (or unreally) is the philosopher of the age of Multiverses.


Baudrillard, J., 1995. The Gulf War did not take place. Indiana University Press.

Baudrillard, J., 2019. Simulacra and simulations (1981). In Crime and Media. Routledge

Baudrillard, J., 2016. The consumer society: Myths and structures. Sage.

Baudrillard, J., 1975. The mirror of production (Vol. 17). St. Louis: Telos Press.

Baudrillard, J. and Singer, B., 1990. Seduction. New World Perspectives.

Baudrillard, J., 2005. The conspiracy of art. New York

Monday, December 20, 2021

Part 2: 20 reasons why the Metaverse may not work out as we think it will

Watching Nick Clegg being interviewed by Horaah Hendry of the FT was embarrassing. Two old men with teenage avatars talking to each other was creepy enough but when they back-slapped each other about being anti-Establishment, it all got a bit arse about facebook. This was facebook PR puff, not journalism. The awkward, missed fist-bump and Clegg holding and drinking an invisible coffee cup, all added to the Pythonesque weirdness. This nonsense aside, we do need to ask some serious questions about this proposition - the Metaverse.

Baudrillard, the prophet of such simulated worlds and their effects on humanity, sees such worlds as being more than extensions of humanity. They capture our attention and hold us hostage. As the world has become de-anchored as God's creation, we began to build our own worlds. It is not yet clear where all of this is going, or more accurately, taking us.

I have been involved with VR for some years, had both the early Oculus kits, written tons about virtual worlds and demonstrated it to many hundreds of people all over the world, including Africa. I have a whole chapter on this in my book Learning Experience Design (2021). These worlds are not new. We know a lot about them and can start to speculate about their future. 

1. Facebook’s landgrab

One worry that most people should have is that this is Facebook. Rebranding the whole company as Metaverse, or Meta, is a huge leap but the Metaverse brand is just flying a marketing kite. It is not really a rebrand - we, and they, still call it Facebook. What we need to question is their move towards total ownership of such virtual worlds. By owning the world, you own everything; the who, what, where, when and how. As a landgrab on the internet, it needs to be treated with due suspicion.

2. Data on everything

Then there’s the data collected within the Metaverse. Facebook want to do a Microsoft and own the OS for virtual worlds by market dominance. At the moment data is distributed, do we really want a centralised place where data can be harvested, not only social data, what is said, but also physical, behavioural data? The opportunities fro extreme forms of surveillance are obvious, so I think not.

3. Metaverse as an economy

Most metaverses, even Second Life, but mostly large-scale games, create worlds in which people want to buy and sell virtual stuff. That's fine on a small scale. When you have a world that is the size of a small, even large, country, you have an economy. But economies are regulated. Do we want facebook to be a regulated economy, like a country? There are already serious concerns about Facebook’s role as a supranational force. One can see the time when such virtual worlds have the status of a country but not for now, and not ones where Billionaires are kings, no matter how benign the PR says they are.

4. Metaverse crypto

Notice how Facebook dabbled in cryptocurrency recently? In 2019 it created Libra, rebranded in 2020 as Diem. This created such a backlash that it has all but disappeared. That doesn’t mean it has disappeared. Facebook as a central bank controlling a cryptocurrency is a frightening thought. Remember, Facebook is not creating a Metaverse as a charitable act, they want to make money... lots of it. Allowing them to create a global virtual world with a virtual cryptocurrency and economy is being touted. This is truly frightening.

5. 2D to 3D problem

3D movies and 3D TV bombed. Sure we like 3D but desirable experiences are not all about 3D fidelity. Even stereo is no longer a big deal in listening to music. Media rich is not mind rich. We love a good podcast precisely because it is a stripped down, single media experience. It feels intimate, like being in that conversation. Turns out that for entertainment and much else, we like just enough to do the job well for immersion (big 2D TV) and no more. The Metaverse may be piling on the pixels but it is not clear that this is what consumers want.

6. Communications

The Metaverse has problems when it comes to communications. It is not so much the high fidelity expectations of the avatars but the communications within a group. It is difficult to get turn taking and the real dynamics of a real meeting going in such environments, especially when they are in a 2D representation. We have two ears, two eyes and a brain that has evolved to monitor around us. Our ears are the shape they are, with folds, as a form of sterescopic radar for listening to others around us. Our eyes are stereoscopic and on the top of our swivelling necks and bodies. Take any of that away and you have a problem. Interestingly Zoom solves that by taking a 3D world and tiling it in 2D. The Metaverse may therefore have a worse group dynamic than Zoom, a lot worse.

7. Turn taking

In a fascinating piece of research by Carnegie Mellon, it turns out that turn taking and problem solving went better when learners turned OFF their video cameras. It would appear that not seeing others in a group is sometimes a lot better than full visibility, as one can focus on the task, not the people.

8. Appearances matter

The Carnegie Mellon study surprised a lot of people who had turned to teaching online during Covid, where the general advice was to keep students’ webcams ON. Counterintuitive though this may be, it seems that students are concerned about how they and their home environments look online. This says something about being careful about true needs in full-blown online environments. That's why most existing Metaverses are chocked full of bizarre avatars.

9. Avatar narcissism

In most virtual worlds, weird avatars are the norm, as people don’t really want to show their true age, weight and looks online. It is all colour, costumes, animals features, weirdness and cartoon fun. How people represent themselves online is far from what they look like in the real world. Will we have a parallel world where people are perennially young, good looking and thin or look like oddballs to mask their ordinariness? It promotes exaggeration of social norms around what one should look like on one hand and freakshows on the other. 

10. Meetings

In a sense, Zoom meetings have accelerated the experience and demand for virtual worlds. Yet there are real doubts about the Metaverse as meetings' technology. Meetings need to be real. We have meetings because we want to have real discussion and make decisions. Is this helped by another layer of representation - avatars? Maybe not. We want to hear real voices and see real faces. The key is not actually the tech but how the meetings are set up and run. They need a good Chair, clear agenda and proper turn taking, along with a movement towards decisions and actions. Having a cartoon, avatar layer may not help one bit. In fact, it may distance you from, or smother, the event.

11. Overstimulation

A surprising finding in VR research was its of lack of efficacy in learning. This is partly to do with the poor design of learning experiences and the focus on creating worlds, not actual learning experiences. But there are lessons to be learnt. Overstimutaion is clearly a problem. People are overwhelmed, and get a sort of stage fright or wonderment in fully immersive online environments. They also get obsessed with detail. This can hinder, rather than help with other tasks, such as efficient meetings and learning. There seems to be a form of uncanny valley effect going on here, where the technology captivates but doesn't relax you.

12. Playworlds

What happens when you build such worlds. Turns out most people muck about a lot. They have fun. It is not as conducive to serious endeavours as you would think, such as collaborative brainstorming and design, even meetings. In fact, it is often a bit anarchic. In VR open worlds, you get people donning full body suits and doing gymnastic moves (and more). It’s showtime! That's why most Metaverses are actually in the games world, something that seems to have passed everyone (apart from gamers) by.

13. Policing

I had a female avatar in Second Life and used to recommend this as the best form of sexual harrassent training you’ll ever receive as a man. It was relentless. There is a real problem in policing this sort of behaviour in open worlds. It is not like the real world where norms are accepted, rules and laws implemented and agreed. It is all a bit Wild West.

14. Fakery

Fakery is the norm in terms of appearance but there is also the problem of fraud and fakery on scale when such a world becomes a phishing ground for scammers and scams. It is bad enough with email and the simple telephone without full-on people talking, charming and defrauding you into doing things that are harmful. The potential for bad actors doing bad stuff is immense.

15. VR shutout

Note how we go full screen when screensharing, that makes sense in terms of focus. There is nothing worse than using 3D VR then seeing 2D video and PowerPoint inside that environment. The problem with VR is that it stops you from using keyboards, taking notes by pen and generally seeing and dealing with the real world. VR is a new medium and not a gadget, yet has not taken off as a mass medium. Even when untethered, it is still largely a niche gamed device. That tells us something.

16. Tech not invisible

Good technology is increasingly invisible. The Metaverse, especially if it involves headsets, makes the technology incredibly tangible, visceral and obvious. It may be that the invisible tech, powered by AI and data, such as IoT, voice assistants and AI as the new UI, will win out and not Metaverses. People want solutions not clumsy tech and the Metaverse is all too visible and clumsy.

17. 90:9:1  consume:comment:create

Most people online are lurkers who consume (90%), a small percentage comment (9%) and 1% create. You can play around with these figures but you get the point. The Metaverse may be just another playground for the 1% of extroverts and narcissists. Most people are reluctant to expose themselves and engage with strangers in such environments, so we may be looking at yet another niche world.

18. Build

Another problem associated with the 90:9:1 problem is who will build these worlds? Fine in Minecraft but the idea that adults will be able to handle the tools and have the time and inclination to do this is ambitious, if not utopian. It is not just the tools, it is the skills. Giving someone a copy of Word does not make them a novelist and giving someone a 3D builder does not make them an architect. Sure there may be pre-built environments. But this is a gargantuan task. 

19. Social engagement

Do people really want to engage with strangers like this, as avatars in a virtual world? It is not clear that they do. The reluctance to engage in this form of communication is interesting. Low-fidelity, social media may actually be better as there is less reveal of the self and more control of exposure. We still use texting, messaging and voice calls - a lot. Virtual worlds give immediate and total exposure that can be unsettling. People may not be as openly social as the extroverts think.

20. Breakout problem

We have a differentiation of media. While the Metaverse is being touted, we have the rise of the audio-only podcast, the inverse of the Metaverse. Philip Rosedale the chief architect of Second Life gave up on High Fidelity, a VR version of Second Life, to focus on spatial audio technology. Second Life is still a million people and a $650 million transactional environment but, as Rosedale says “it didn't break out, it didn't become a billion people. And the hope that Facebook has is that there'll be a billion people using a metaverse”. Maybe, maybe not.


Technology surprises and I have no doubt that Metaverse-type tech will do just that. It may be in speaking to our future or past selves, learning languages, political engagement, dating, porn - no one really knows. But of one thing I’m sure, it will happen, just happen differently from how we envisage.

Monday, December 13, 2021

Wittrock Generative learning

Merlin Wittrock (1931 - 2007) worked at the University of California and saw good learning as a generative process. In a series of papers over two decades he saw 'generative' learning as the key to creating a shift in education towards more efficient learning. 
It has its roots in Bartlett (1932) and Piaget (1926) who both saw learning as acts of construction and, for Piaget, fitting knowledge into existing schemas. But for Wittrock, generative learning theory was built on the idea of learners integrating new knowledge and skills into what they already know though generative activities, where effective teaching facilitates leavers to construct meaning from various generative experiences.

Generative theory of learning

Wittrock not only developed his generative theory of learning, he also researched its effectiveness and applied it in practice. Learners, for Wittrock, are not passive receivers of knowledge, they are active reorgansisers of knowledge, creating meaning from their own generative activities. His generative learning theory was built on the idea of learners integrating new knowledge and skills into what they already know through generative activities. Effective teaching must therefore facilitate learners to construct meaning from various generative experiences.

His model encourages learners to generate meaning and understanding from instruction through effortful, generative activities and has four major processes:

(a) attention - directing generative processes on relevant incoming material and stored knowledge

(b) motivation - willingness to invest effort to make sense of material

(c) knowledge and preconceptions - prior knowledge, experiences, and beliefs

(d) generation - sense making

For Wittrock all four have generative components, what some would describe as constructive, where the learners control and build their own models, rather than interpreting taught content. Teachers must therefore learn to lead learners towards learning by encouraging generative activities. 

Generative activities

The generation of notes in one’s own words, use of analogies and effortful activities are all generative. Summaries and analogies in reading, for example, is an effective learning strategy, Wittrock & Alesandrini (1990). 

Fiorella & Mayer (2015) recommend eight types of generative strategies:

Summarizing: Create a written or oral summary of the material 

Mapping: Create a concept map, knowledge map or matrix organizer 

Drawing: Create a drawing that depicts the text

Imagining: Imagine a drawing that depicts the text 

Self-testing: Give yourself a practice test on the material 

Self-explaining Create a written or oral explanation of the material 

Teaching: Explain the material to others 

Enacting: Move objects to act out the material

Problem solving

With Richard Mayer, Wittrock also contributed to research on problem solving in order to identify the best way to teach it, with three main findings:

  1. Domain-specific principle - teach problem as a domain specific skill not as a general skill

  2. Near transfer principle - accept that problem solving skills work across a limited range of applicability

  3. Knowledge integration principle - use guided problem-solving tasks to teach knowledge

Wittorck was heavily involved in teacher training and his generative theory was not just about what the learner did, it was also about appropriately generative teaching strategies. Problem solving was one such strategy.


Generative learning has been criticised by some as swinging the instructional pendulum too far towards discovery or exploratory learning, diminishing the role of direct instruction. Its singular focus on the generative processes, some think are partial, with other processes involved in learning.


Wittrock’s work on generative learning has not had as much influence as the topic and his work deserve. As technology has developed and social media normalised, the creation of text, images and videos have become common online, generative activities.


Wittrock, M.C., 1992. Generative learning processes of the brain. Educational Psychologist, 27(4), pp.531-541.

Wittrock, M.C., 1989. Generative processes of comprehension. Educational psychologist, 24(4), pp.345-376.

Wittrock, M.C., 1974. Learning as a generative process. Educational psychologist, 11(2), pp.87-95.

Fiorella, L. and Mayer, R.E., 2016. Eight ways to promote generative learning. Educational Psychology Review, 28(4), pp.717-741.

Wittrock, M.C. and Alesandrini, K., 1990. Generation of summaries and analogies and analytic and holistic abilities. American Educational Research Journal, 27(3), pp.489-502.

Mayer, R.E., 2010. Merlin C. Wittrock's enduring contributions to the science of learning. Educational Psychologist, 45(1), pp.46-50.

Mayer, R.E. and Wittrock, M.C., 2006. Problem Solving In P. Alexander, P. Winne, & G. Phye.

Education during COVID debate in Berlin

The UK Government has announced an acceleration of the booster programme, as they know a huge wave of infections is coming based on Omicron's infection rate (high). Although the variant is less lethal, when you have so many people infected, the strain on hospitals will be intense and people will die.

Yet the Government (and opposition) completely ignores the fact that schools and Universities are two massive vectors for infection. They are basically wheel and hub networks designed to optimise viral spread. Schools bring huge groups of people, a thousand and more, from every street in the community, to sit in small cramped rooms all day, then send them back to their homes, five days a week. With Universities you do this on a national scale with longer distances. These vast networks basically boost infection by forcing millions into close contact wil Amazon levels of distribution reach.

I took part in The Big Debate in Berlin this month. The motion was “This house belives that Education has failed to learn the lesson of Covid19”. I was up against the head of the NUS, who thought that “poor students who had to study in their pyjamas and dressing gowns” were “suffering badly from mental illness and loss of social contact”. Not only was this a caricature of education, as most people being ‘educated’ were in schools or the workplace, it was the usual placing of students on a social pedestal.

My retort was that viewing students as victims was an insult to the front line workers who had no choice other than to risk their lives, and sometimes die doing so, to keep us fed, supplied and safe - the delivery drivers, lorry drivers, paramedics, care home workers, police officers, bus drivers and factory workers - almost none of whom went to ‘Uni’.

I did argue that educators did a good job, many raising their skills as online educators under immense pressure. It was also good for both teachers and learners to raise their digital skills and literacy. Like Eric Mazur at Harvard,, I argued that it would be "almost unethical" to go back on those gains,

Rather than build on the advances we’ve made on Blending learning, the education system seems to be defaulting back to their old model. Why? Lecturing is easy, teaching is hard. We have a chance to make Higher Education cheaper, more accessible and efficient. We may blow it.

Saturday, December 11, 2021

Tales of the absurd from Berlin

It was my first live conference for eons and the final session was a L&D roundup which was a bit of fun but two odd things happened. It was one of those bingo word events, where someone in the audience chooses a word from the screen and someone else stands up to say something for five minutes on that word. I can’t remember all of the words but they were things like ‘resilience’ and ‘curiosity’ and ‘obstacles’. When asked about ‘obstacles’ I put my hand up and said that I thought faffing around with abstract words in L&D had become an ‘obstacle’ to progress. 

BIG mistake, as I then heard the words ”Next we have (can’t remember their names) who will speak on ‘Resilience’”. To be fair the whole room laughed. If I’m resilient, it’s on one thing, trying to stop learning people rattle on about grit, resilience, or any other obscure, abstract noun, that no real people ever actually utter. We’ve only just put ‘mindfulness’ to bed, when a new one appears. I’ve had a bellyful of the stuff and lost interest when they were describing their ‘resilience meter’. It really is a thing. It just wasn’t my thing. Actually they were lovely people.

My SECOND mistake was to drift off, then coming round to hear “ turn to the person next to you and give it a try” a phrase that makes my heart sink. I missed the first part of the sentence and on turning round, I said something and the person, who is a good friend of mine, started to object to what I said. She was repeatedly abrasive. My responses, at first polite, became angier and then I got obstreperous. Turns out it was a role-play, the key piece of information that had failed to register . A third person turned to me and said “You do know it’s a role-play?”. I apologised and all was fine. Again we had a bit of a giggle.

I suppose I’m just weary of this stuff, the idea that L&D is some sort of pop-up therapy service. Is this resilience thing much more than HR once again ticking people off for having a perceived deficit, a weakness, a flaw? Then there’s that old-school performative ‘turn to the person next to you’ BS. Are we really going back to that after Covid?

Sunday, November 21, 2021

Stickgold & Walker Sleep and learning

Robert Stickgold is a US Professor of Psychiatry at Harvard Medical School, whose sleep research looks at the links between sleep and learning, especially sleep deprivation. He was a colleague and mentor to Matthew Walker, an English sleep researcher, now Professor of Neuroscience and Psychology at the University of California, Berkeley. His research is on sleep and his international bestseller Why We Sleep (2017) contains much that is relevant to the topic of sleep, memory and learning. His 2019 TED talk Sleep is your Superpower was also hugely popular, watched by millions.

Sleep and memory

Walker has written about the effects of sleep on student learning and recommends a rethink around the idea of end-of-semester exams that encourage cramming, even all-nighters. He has changed his own teaching to avoid final exams, splitting his courses up into thirds to spread the assessment load. 

Sleep before learning

Sleep is an active process that improves memory. When we are awake the hippocampus experiences and learns things in the real world, as a short-term location for new memories. It is also limited in capacity. It deals with this by shifting memories into other locations, namely the cortex, during sleep. You can test this using daytime naps and Walker compared a 90 minute ‘nap’ with a ‘no-nap’ group, after they performed a taxing 100 face-name pair task. Later that day, another intense learning task was performed, to see if learning had declined. Those that napped actually increased their ability to learn, while those that stayed awake showed a decline, the difference being a staggering 20%. It would appear that light, Stage 2 NREM sleep and short sleep spindles led to greater retention. It would appear that sleep refreshes our ability to learn, especially the later period of a night’s sleep. Getting up too early and shortening your sleep period seems to be deleterious to learning. This seems to decline with age.

Sleep after learning

What about after one has learnt something? Consolidation of memories has been posited for 2000 years, but it was Jenkins and Dallenbach (1924), who tested forgetting of verbal facts over eight hours, either awake or asleep. This has been replicated many times and forgetting in the group that was awake is greater, the benefits of sleep being 20-40% greater for the sleep groups.

REM and NREM  sleep was then discovered in the 1950s and the link between consolidation of memory and deep NREM was established, with MRI evidence indicating that memories literally move from the hippocampus to the neocortex during sleep. It would appear that your cache of memories gets cleared and stored every night, leaving  you ready for the next day’s learning. Sleep can also improve learning by recovering memories you lost while learning. It seems to rescue memories. Motor skills are also consolidated and enhanced during sleep.

Stimulating learning during sleep

Sleepers stimulated by electrical voltage pulses during deep NREM. The sleepers felt nothing but doubled their ability to recall facts learnt just before going to sleep. Quiet auditory tones synchronised with brain waves, from speakers next to the bed, have also been found to have an effect, namely a 40% improvement on recall. 

Sleep to forget  

When two groups were presented with words to remember but told to remember some (tagged R) and forget others (tagged F), the group that had a 90 minute nap had actively remembered more R words and forgotten more F words. It would seem that sleep is quite intelligent or active in what it selects as memories to be stored.

Sleep and emotions

Emotions or the affective side of learning are also influenced by sleep. The brain does reprocess or modulate emotions through sleep. Sleep deprivation encourages high emotional responses including aggression, bullying and behavioural problems in children.


Walker has been criticised for being slapdash with his data and references in his book. He has responded and apologised for some of its weaknesses.


Walker’s book and TED talk popularised sleep research and although he has been criticised for some inaccuracies, the benefits of sleep are now well known, especially among teachers and parents, worried by the rise in late night screen time.


Walker, M., 2017. Why we sleep: Unlocking the power of sleep and dreams. Simon and Schuster.

Stickgold, R. and Walker, M.P., 2013. Sleep-dependent memory triage: evolving generalization through selective processing. Nature neuroscience, 16(2), pp.139-145.

Walker, M.P. and van Der Helm, E., 2009. Overnight therapy? The role of sleep in emotional brain processing. Psychological bulletin, 135(5), p.731.

Walker, M.P. and Stickgold, R., 2004. Sleep-dependent learning and memory consolidation. Neuron, 44(1), pp.121-133.

Walker, M.P. and Stickgold, R., 2006. Sleep, memory, and plasticity. Annu. Rev. Psychol., 57, pp.139-166.

Jenkins, J.G. and Dallenbach, K.M., 1924. Obliviscence during sleep and waking. The American Journal of Psychology, 35(4), pp.605-612.

Vannevar Bush Internet visionary

Vannervar Bush (1890 - 1974) was the Dean of the School of Engineering at MIT, a founder of Raytheon and the top administrator for the US during World War II. He widened research to include partnerships between government, the private sector and universities, a model that survives to this day in the US. He claimed that his leadership qualities came from his family who were sea captains and whalers. He was also a practical man with inventions and dozens of patents to his name. In addition to his Differential Analyzer, he was an administrator and visionary who not only created the environment for much of US technological development during and after World War II leading to the internet but also gave us a powerful and influential vision for what became the World Wide Web.

Differential Analyzer

Bush built his analogue Differential Analyzer in 1931, arguably the first computer. It was an analogue electrical-mechanical device with six disc integrators . The size of a small room, it could solve equations with up to 18 variables. By the late 1930s the digital mindset and technology began to emerge with the English engineer Tommy Flowers, who built vacuum tube switches as binary switches in electrical circuits. A century after Babbage the concept of the modern computer was established.

Innovation and the internet

When World War II came along he headed up Roosevelte’s National Defense Research Committee and oversaw The Manhattan Project among many others. Basic science, especially physics, he saw as the bedrock of innovation. It was technological innovation, he thought, that led to better work conditions and more “study, for learning how to live without the deadening drudgery which has been the burden for the common man for past ages”. His post war report saw the founding of the National Science Foundation, and Bush’s triad model of government, private sector and Universities became the powerhouse for America’s post war technological success. Research centres such as Bell labs, RAND Corporation, SRI and Xerox PARC were bountiful in their innovation, and all contributed to that one huge invention - the internet.

As We May Think

Bush was fascinated with the concept of augmented memory and in his wonderful 1945 article As We May Think, described the idea of a ‘Memex’. It was a vision he came back to time and time again; the storage of books, records and communications, an immense augmentation of human memory that could be accessed quickly and flexibly - basically the internet and world wide web.

Fundamental to his vision was the associative trail, to create new trails of content by linking them together in chained sequences of events, with personal contributions as side trails. Here we have the concept of hyperlinking and personal communications. This he saw as mimicking the associate nature of the human brain. He saw users calling up this indexed, motherlode of augmenting knowledge with just a few keystrokes. A process that would accelerate progress in research and science.

More than this he realised that users would be able to personally create and add knowledge and resources to the system, such as text, comments and photos, linked to main trails or in personal side trails - thus predicting concepts such as social media. He was quite precise about creating, say a personal article, sharing it and linking it to other articles, anticipating blogging. The idea of creating, connecting, annotating and sharing knowledge, on an encyclopedic scale anticipated Wikipedia and other knowledge bases. Lawyers, Doctors, Historians and other professionals would have access to the knowledge they needed to do their jobs more effectively. 

In a book published 22 years later, Science Is Not Enough (1967), he relished the idea that recent technological advances in electronics, such as photocells, transistors, magnetic tape, solid-state circuits and cathode ray tubes have brought his vision closer to reality. He saw in erasable, magnetic tape the possibility of erasure and correction, namely editing, as an important feature of his system of augmentation. Even more remarkable was his prophetic ideas around voice control and user-generated content, anticipating the personal assistants so familiar to us today. He even anticipated the automatic creation of trails, anticipating that AI and machine learning may also play a part in our interaction with such knowledge-bases.

What is astonishing is the range and depth of his vision, coupled with a realistic vision on how technology could be combined with knowledge to accelerate progress, all in the service of the creative brain. It was an astounding thought experiment.


Some, such as Eisenhower, argue that the Military-Industrial complex became, and continues to be, too large and powerful, no longer serving its original purpose of innovation, although DARPA may be a counter-argument to that thesis.


Douglas Engelbart, the visionary for the modern computer, was profoundly influenced by Bush’s vision for man-machine and quotes Bush repeatedly as the inspiration for his ideas and practical inventions such as the mouse, computer screen, and personal computer. It was Bush who inspired the ‘Mother of all demos’ the manifestation of a vision that was to be eventually realised through the personal computer and the internet. The vision was not just technological, it continued Bush’s idea of the augmentation of human capabilities for the common good, something Engelbart was to call ‘collective intelligence’. Ted Nelson, who invented ‘hypertext’, also acknowledged his deep debt to Vannervar Bush, as did Tim Berners-Lee, who specifically mentioned Bush and Engelbart and As We May Think as an inspiration for his development of the World Wide Web.


Bush, V., 1967. Science is not enough.

Bush, V., 1945. As we may think. The Atlantic Monthly, 176(1), pp.101-108.

Houston, R.D. and Harmon, G., 2007. Vannevar Bush and memex. Annual review of information science and technology, 41, p.55.

Saturday, November 20, 2021

Engelbart Collective intelligence and IQ

Douglas Carl Engelbart (1925 – 2013) was instrumental in establishing human-computer interaction as an area of technical and psychological research, playing an instrumental role in the invention of the computer mouse, joystick and tracker-ball, also bitmapped screens and hypertext. These and other prophetic features were shown in the famous ‘Mother of all demos’ in 1968. He also put forward an early and full vision of collective intelligence and the idea of collective IQ. He envisioned much of this before the advent of the internet but foresaw the importance of networked knowledge and the networked organisation.

Collective intelligence

While in the Navy he read Vannevar Bush’s article As We May Think and saw the possibility of a shared network being able to be more than the sum of its parts.

We need to get better at getting better. To do this we needed to augment our individual intellects with techniques that leverage collective knowledge. He saw this as the solution to solving complex problems. He called this Bootstrapping and at the heart of the Bootstapping Paradigm was his Dynamic Knowledge Repository (DKR) which allowed a process called the  Concurrent Development, Integration and Application of Knowledge (CoDIAK). This DKTR is also subject to the CoDIAK process.

There is, of course, the human activity with tools and within networked technology but Englebart’s focus was on

A-level, core business as usual activities

B-level improvements on that process, such as quality control

C-level improving on the improvements. 

This C-level is the most im[ortant for exponential improvement. It is what he meant by getting better at being better and is an iterative process where lessons learnt are included in the process of improvement.

Collective IQ

Beyond the mere qualitative description of the web being a place where collective intelligence could flourish, in 1994 he proposed a measure for such intelligence - collective IQ. It measures ‘effectiveness’ or how well groups work together to anticipate and respond to problems and situations. 

This could be a product, service or research goal. Whatever the goal, Collective IQ determines the effectiveness of the response. Speed and quality of response are the key measures, along with development and deployment. It is not an abstract measure of reason but a measure of getting things done and completed, to meet the goal.

Complex goals need more collective IQ, so it is challenging projects, such as the Moonshot or Manhattan project that are often quoted as examples, where collective efforts resulted in goals being met faster and more effectively than they would have been, on the basis of a less collective effort.

The components of Collective IQ are, unlike the brain and individual IQ:

  1. Group process - collective ability to develop, integrate and apply knowledge to a goal

  2. Shared memory - gained, captured, accessed as a shared resource

Collective IQ can be raised or lowered through ignoring, obstructing the bootstrapping process.


The measurement of individual intelligence is hard enough, the measurement of collective intelligence that much harder, not only in terms of how one combines the individual inputs but also any additional value that images from it being a collective. It is not clear that any general measure could be possible.


Engelbart’s invention of the mouse and initalm work in envisioning the internet is reason enough to see him as an influential pioneer. His further work on collective intelligence saw the start of serious analysis of networks in terms of their emerging features as forms of collective effort and intelligence.


Boosting Our Collective IQ, by Douglas C. Engelbart, 1995