Identity from the perspective of authentication

In this video Stephen Downes, convener of the E-Learning 3.0 MOOC explains that in the future our safety and security online will be managed through the use of identification keys. We will each have a private key and a public key, which we will plug into our computers instead of signing on with a password.

Source of  image –  Yubico.com

In the future everyone will be logging in like this and passwords will become a thing of the past.

Why do we need two keys? This is to ensure maximum security and encryption.  The two keys act like a two-way security system. We can think of our private key as our ‘key’ and our public key as the ‘lock’, i.e. the one won’t work without the other. You can only get through the door if you have the right key and the right lock.

So, an example found on Quora  explains how you can use private and public keys to send and receive encrypted messages like this:

Robert wants to send Katie a file. Robert would request Katie’s public key to encrypt the file and then encrypt it with her public key. Robert would then send the file to Katie. Katie would then decrypt the file with her private key.

In this way, Katie’s public key is only used to encrypt but can never be used to decrypt, keeping the data safe. And Katie can only decrypt the data with her private key and would never exposes her private key to anyone, keeping her private key safe. (Source: https://www.quora.com/profile/Ken-Mafli-1)

Stephen in his video (starting at about 7.00 minutes in) explains this in more detail and makes it very clear that a signature on the sent encrypted message would be needed to make it absolutely secure, otherwise you couldn’t be sure who had the public key. The point is to be able to prove who you say you are and keep your communications online safe, without the use of passwords. Your digital identity (based on your identity graph/s) becomes your public key, which is unique to you, and your private key keeps you safe.

Stephen believes that in ten years’ time this is how we will all be accessing the internet. I wonder how straightforward this will be for the average user. I will be in my 80s in 10 years’ time. Will this make it easier for me and people like me, or, as Stephen asks elsewhere on the E-Learning 3.0 course site,

“Will we be lost in the sea of possibilities, unable to navigate through the complexities of defining for ourselves who we are, or will we be able to forge new connections, creating a community of interwoven communities online and in our homes?”

Hopefully there will be more courses like this one which will help us to keep abreast of developments and where we are headed.

This is only a brief summary of the key points in Stephen’s video, as I see them. You need to watch the 25 minute video to get a more complete picture.

And have a look at the Resources – provided by Stephen which I have copied below:

FIDO U2F
Yubico, 2018/11/15

As explained on the Yubico website, “U2F is an open authentication standard that enables internet users to securely access any number of online services with one single security key instantly and with no drivers or client software needed.  FIDO2 is the latest generation of the U2F protocol.”

Public-key cryptography
Wikipedia, 2018/11/15

Public-key cryptography, or asymmetric cryptography, is any cryptographic system that uses pairs of keys: public keys which may be disseminated widely, and private keys which are known only to the owner. This accomplishes two functions: authentication, where the public key verifies that a holder of the paired private key sent the message, and encryption, where only the paired private key holder can decrypt the message encrypted with the public key.

Keybase.io – Downes
Stephen DownesKeybase, 2018/11/15

This is my Keybase page. Here’s what Keybase says about itself: “Keybase is a new and free security app for mobile phones and computers. For the geeks among us: it’s open source and powered by public-key cryptography. Keybase is for anyone. Imagine a Slack for the whole world, except end-to-end encrypted across all your devices. Or a Team Dropbox where the server can’t leak your files or be hacked.” See also (very technical) Keybase for Everyone. And Keybase writing to the blockchain.

E-Learning 3.0: The Human versus the Machine

This post is a response to a challenge set, as a result of Task 2, by Frank Polster, a fellow course participant on Stephen Downes’ MOOC, E-Learning 3.0.

Here is my challenge to all the E-Learning 3.0 cohort and a task associated with course module E-Learning 1 and 2 Conversation with George Siemens. Please comment on what fields, skills, talents, and education that you think are unique domains of humans like Stephen’s “kindness and compassion” and the skills, talents, and education required for the “ghost in the machine” that provides that alternative view.

I have given this post the Title, E-Learning 3.0: The Human versus the Machine, because that is how I have interpreted this challenge.

My response to the challenge is based on what I have learned from reading the work of Iain McGilchrist,  author of The Master and his Emissary: The Divided Brain and the Making of The Western World. McGilchrist’s writing focusses on the differences between the ways in which the left hemisphere and the right hemisphere of the brain view and attend to the world. For example, the left hemisphere’s view of the body is as a machine. The right hemisphere’s view of the body is as a living whole in nature.

I have heard MGilchrist talk about the difference between living things and machines and have written about this before – see my post Skills for ‘Being’ in a Digital Age where I listed the differences he discussed. I will copy them here for ease of reference. According to McGilchrist these are the things that differentiate living things from machines:

  • An organism cannot be switched off. There must be an uninterrupted flow from the origins of life.
  • A machine is at equilibrium. An organism is far from equilibrium. A cell carries out millions of complex reactions every second. Enzymes speed these up to a thousandth of a second.
  • The relationship between steps and an outcome are different in machines and living organisms. In an organism there are no steps – there is a flow of process.
  • In living things there is no one-way step. Interactions are complex and reciprocal.
  • The parts of a machine are static. The parts of an organism are not static, they are constantly changing.
  • An organism is aware of the whole and corrects for it in its parts (see the work of Barbara McClintock)
  • Organisms have no precise boundaries.
  • Machines don’t generate other machines from their own body parts.
  • Machines’ code is externally generated. Organisms manufacture their own instructions.

But what is it that makes human beings unique and different to machines? My response to this (again informed by McGilchrist) is that a human being is able to relate to something ‘Other’ than itself that exist apart from us, beyond ourselves and may be ‘new’ or to some degree ‘unknown’. (A machine can only relate to what is already known.)

Priests, teachers, doctors, and similar professions do this as part of their jobs, through care, empathy, trust, altruism, kindness and compassion. They are able to put themselves in the position of the ‘Other’ and experience their experience. Human beings can experience not only their own pain, but also the pain of others. Human beings can love. We can also see all this in family relationships.

Other characteristics unique to humans are the ability to recognise and experience beauty, awe and wonder, in art, music, dance and nature, and to value wisdom, intuition, metaphor, ambiguity, uncertainty, flexibility, the implicit and the spiritual. Human beings experience emotions such as humour, fear, anger, anxiety and sadness, and affective states such as hope and optimism; they have a sense of self, an understanding of the uniqueness of the individual, and search for meaning and truth in life. They do this through embodied engagement with the world, not detached abstract contemplation of it or separation from it. Human beings can imagine, wonder and dream.

An education which values the uniquely human is one that focusses on learning the meaning of ‘Other’, recognising the value of living things, nature and the unknown, learning how to think in an embodied way, and acknowledging that thinking and feeling can’t be separated.

To think is to thank. Thinking is not made up by reason. It is not certain, unidirectional and detached. Thinking is receptive and grateful. It is relational. Mind relates to ‘to mind’, which relates to ‘to care’ again suggesting a relationship. Thinking is deeply connected with feeling (feeling probably comes first) and is an embodied way of sensing……… All thinking is dependent on the body. (From my blog post The Divided Brain – What does it mean to think?)

The second part of Frank’s challenge is – comment on the skills, talents, and education required for the “ghost in the machine” that provides that alternative view.

‘Ghost in the machine’ is not an idea I am very familiar with, but what I have read seems to imply that it questions whether there is a ghost in your machine making it work and whether you can put a ‘non-physical mind’ into a physical machine.

This of course relates to Descartes’ argument that mind and body can function separately. My understanding is that this idea of body/mind dualism has long been discredited, so I’m wondering if it is worth taking the idea of ‘ghost in the machine’ seriously, although there are scientists working on trying to understand what’s unique about humans and to replicate this in robots.

If Frank is asking what human-like skills could be adopted by a machine, then I would say only those skills that can be programmed by a human being, and that there are unique qualities of humans, as discussed above, that are immeasurable and cannot be programmed. A machine, if programmed correctly, can perform many of the tasks a human can do, but it cannot do or be programmed for the important, immeasurable tasks and qualities that are so essential for a meaningful life.

And if I am wrong and machines will ultimately be able to replicate humans, then, as I think Frank is asking, what checks should be put in place in a machine to ensure that the machine always has access to an alternative perspective. If we value what is unique about humans, then machines should be programmed to ensure that human beings are never prevented from experiencing the ‘Other’, or thinking and feeling in an embodied way.

Source of image here.

Update 11-11-18

Frank Polster has replied to this post on his blog. See http://frankpolster.com/blog/elearn30/a-response-to-jennys-e-learning-3-0-the-human-versus-the-machine/ 

See also Laura Ritchie’s response to Frank’s task and the conversation there – https://www.lauraritchie.com/2018/11/10/what_makes_us_human/#comment-57854 

And see Matthias Melcher’s post which informs this discussion – https://x28newblog.wordpress.com/2018/10/24/el30-alien-intelligence-ai/ 

E-Learning 3.0: Cloud Computing

The second topic in Stephen Downes’ E-Learning 3.0 MOOC, bears the title ‘Cloud’. Stephen has provided a good synopsis of the week’s content on the course site, where he starts by saying:

The joke is that “the cloud” is just shorthand for “someone else’s computer.” The conceptual challenge is that it doesn’t matter whose computer it is, that it could change any time, and that we should begin to think of “computing” and “storage” as commodities, more like “water” or “electricity”, rather than as features of a type of device that sits on your desktop.

Stephen provided some easy to read introductory articles to Cloud Computing which I have copied under the heading ‘Resources’ at the bottom of this blog post. In the first article in the resource list Bojana Dobran defines cloud computing as follows:

A simple definition of cloud computing involves delivering different types of services over the Internet. From software and analytics to secure and safe data storage and networking resources, everything can be delivered via the cloud.

You probably use different cloud-based applications every day. You are benefiting from cloud solutions every time you send a file to your colleague via the web, use a mobile app, download an image, binge a Netflix show, or play an online video game. All these services are stored in the cloud and exist in some digital space.

Storing your information on OneDrive, SharePoint, or an email server is much different from keeping that data on a desktop hard drive or a USB stick. You can access it from just about any computer that has internet access.

For businesses, cloud computing means improved collaboration and productivity, as well as significant cost reductions. It means better data protection, improved availability, and expanded access to cutting-edge technologies.

All this will be familiar to the average computer user, even if they haven’t thought much about Cloud Computing – and it is not new. Dropbox, a personal cloud storage service used for sharing and backing up files, has been around since 2007. I don’t remember The Cloud being mentioned when I first signed up to Dropbox.

But, the focus this week has been on the next generation of Cloud Computing for virtual learning rather than for storage and file sharing. The invited guest speaker was Tony Hirst from the Open University. Whilst I appreciate that he is way ahead of the game in the work he is doing on Cloud Computing, it turned out that the gap between his technical understanding and mine was, for the most part, just too great to bridge. Here is a link to the video, and Stephen’s description of it, for those less technically challenged than me: URL: https://www.youtube.com/watch?v=mjGyVXI2zFA

Conversation With Tony Hirst Oct 31, 2018 video We covered server virtualization with an in-depth look at using Docker to launch full web applications in just a few moments, and then looked at embedded programs in Jupyter notebooks, tying it all together with a discussion of how these might be used in the future.

But it was interesting to hear why the Open University (OU) is working on this. Students at the Open University, UK, are distance learning students who bring their own device. The OU has no way of controlling the devices that the students bring, apart from stipulating a minimum specification. The issue for the OU is that they want students to run a complicated software environment, so the OU has had to find a way of delivering the software to students so that they can manage this and the students can run it. To do this they use virtual machines which the students download and run on their own computers. These virtual boxes contain all the applications that students need. All this was interesting and made sense, but I got left behind when the discussion went ‘under the hood’ and delved into the technicalities of doing this. Docker and Jupyter notebooks are new concepts for me.

For anyone who is in a similar position to me, I would recommend that you watch Stephen’s own video first, before watching the conversation with Tony Hirst.

Applications, Algorithms and Data: Open Educational Resources and the Next Generation of Virtual Learning Oct 29, 2018 video Using examples such as virtual containers and actionable data books, I sketch the future for the next generation of OERs as a distributed and interactive network of applications, algorithms and data. My presentation starts at 1:18:00 in the video. URL: https://www.youtube.com/watch?time_continue=4680&v=MotTQd9U0sY

And here are the slides that accompany this talk:

In the first part of this talk Stephen explains that Open Educational Resource Repositories are fairly well developed; open pedagogy is beginning to change our practices as open resources are increasingly produced not just by educators and institutions, but by the students themselves. But he pointed out that we have only recently begun to think of data as open educational resources that will be very useful for learning. For this we will need to aggregate distributed data and resources. We have already been encouraged to do this, on this course. Stephen then went on to explain how he does this in his own work, and where he thinks the next generation of virtual learning is going. From this point there was overlap with the conversation he had with Tony Hirst and again it mostly went over the top of my head. He talked about:

  • i-Python – an interactive programming shell for the Python programming language
  • Jupyter Notebooks – an open-source web application that allows you to create and share documents that contain live code
  • Actionable Data Book
  • XAMPP
  • Spoodle – Spoodle is an up to date portable moodle / ‘moodle on a stick’ solution for learners to access Moodle courses without requiring constant internet access
  • gRSS hopper in Vivaldi
  • gRSShopper as a Firefox Sidebar
  • Research and References in an MS-Word Plugin
  • Server Virtualization
  • Virtualization Platforms – Vagrant
  • Docker
  • Cloud Infrastructure Providers …. and more

Being very familiar with Moodle,  ‘Spoodle’ caught my attention, but I did wonder how, if you had your Moodle course on a stick and were not connected to the internet, you could be sure you were looking at the most recent version of the course. Courses are not static. They change from day to day (i.e. the course site changes), just as this one is doing.

Whilst there is still a lot here that I don’t understand, it has been very useful to get a glimpse of what the future might entail. But I think Stephen and Tony both agreed that it will be a while before your average single user has all this at their fingertips.

Update: For a very good explanation of this topic see Stephen Downes’ summary – https://el30.mooc.ca/cgi-bin/page.cgi?post=68440 

Resources

What is Cloud Computing in Simple Terms? Definition & Examples
Bojana DobranPhoenixNAP, 2018/11/01

“Did you know that the monthly cost of running a basic web application was about $150,000 in 2000? Cloud computing has brought it down to less than $1000 a month. For businesses, cloud computing means improved collaboration and productivity, as well as significant cost reductions. It means better data protection, improved availability, and expanded access to cutting-edge technologies.” Web: [Direct Link] [This Post]

Cloud Computing 
2018/11/01

Describes cloud computing and explains the benefits, concerns, types of cloud computing and what to consider when moving your business to the cloud. Part of Ontario’s E-Business Toolkit. Web: [Direct Link] [This Post]

Cloud Adoption Strategy: 2018 update 
Government of Canada, 2018/11/01

Cloud computing can be compared to public utilities that deliver commodities such as electricity. Instead of buying and running infrastructure itself, an organization buys computing power from a provider. Much like electricity in a home, cloud computing is on-demand and the consumer pays for what they use. The cost of the infrastructure used for delivery (storage and services in the case of cloud computing, hydro poles and power lines in the case of electricity) is covered by the charges to the consumer. Web: [Direct Link] [This Post]

Data, personal learning and learning analytics

This week’s topic for Stephen Downes’ E-Learning 3.0 MOOC is Data.   From the synopsis that Stephen provides for the week we read that…

…. there are two conceptual challenges associated with this topic: first, the shift in our understanding of content from documents to data; and second, the shift in our understanding of data from centralized to decentralized.

The first shift allows us to think of content – and hence, our knowledge – as dynamic, as being updated and adapted in the light of changes and events. The second allows us to think of data – and hence, of our record of that knowledge – as distributed, as being copied and shared and circulated as and when needed around the world.

To try and make sense of this topic I have watched three videos this week.

Personal Learning vs Personalized Learning: What Needs to Happen Oct 24, 2018 Online Learning 2018, Toronto, Ontario, Contact North. This special briefing explores personal learning as the future of learning, explores why it’s important, the tools which enable personal learning and the significant potential of personal learning as a key to life-long learning and the skills agenda. URL: https://www.youtube.com/watch?v=mVnjet3cKfU

This was the video that most resonated with me and related most to my personal interests. What I like about Stephen’s work is that he doesn’t forget to ask the question ‘why’, i.e. the ‘why’ of learning analytics for learners, rather than just the ‘what’ and ‘how’. In this video Stephen tells us that there are two approaches to learning, personalized (formal learning, which accounts for about 20% of our learning) and personal (informal learning, which accounts for the rest). This slide (7) from his presentation ( https://www.downes.ca/cgi-bin/page.cgi?presentation=497 ) provides a clear overview of the differences.

Stephen then considered how we can support an approach which promotes personal learning through discussion of three major themes: choice, ownership and community. In this video Stephen says of learning analytics that it should be for learners so that they can track and understand their own progress. This would mean, in terms of the three major themes, that we can choose what to work on (create our own learning paths), where to store our data and what data to store; that we own all our data and have control over how it is used; and that we are free to work openly and create our own learning communities with whom we can share our data and from whom we draw support. Learning analytics will help us to keep track of our data (which will be distributed over various locations on the web) and self-monitor our personal progress. Personalized learning, whilst still useful and necessary in certain contexts, does not allow for the autonomy necessary for personal learning. The big question raised by Stephen was ‘how can we make this happen?’ i.e. how can personal learning be promoted and recognised in today’s education contexts.

AI in Education Symposium – Introduction: Oct 24, 2018 Artificial Intelligence and 21st Century Education in Ottawa, my brief introduction and posing of a problem. URL: https://www.youtube.com/watch?v=WENb9N2gnpQ

In this 6-minute video, Stephen introduces the AI in Education Symposium in Toronto. He asks can AI solve the problems of society, since society has now become too complex for its problems to be solved by a few elite, privileged groups? He says that as society gets more complex it becomes increasingly difficult to govern. In the future we will need to teach each other and govern ourselves as a society. We will have to move from a society based on identity, nationalism, religion and language to a society based on consensus and collaborative decision making. The question posed was – Does AI offer us lessons into how to do this? I can see how this is related to the themes developed in the ‘Personal Learning vs Personalized Learning: What Needs to Happen’ video.

Conversation with Shelly Blake-Plock Oct 24, 2018 Week 1 of E-Learning 3.0 with Shelly Blake-Plock, Co-Founder, President and CEO – Yet Analytics. URL: https://www.youtube.com/watch?v=dsmdwnUwKkA

This third video was the E-Learning 3.0 MOOC course video for the week. In this conversation Shelly Blake-Plock described his work in Yet Analytics, a company which focusses exclusively on learning analytics and works with the K-12, corporate and military sectors in the US, to help improve learning content and instruction, and improve the management of data. The system they have developed for tracking learning experiences and performance is known as Experience API (xAPI). Shelly claimed that this system goes beyond how a traditional LMS is able to analyse content and activity. xAPI is able to pull data from the physical world (sensors etc.), mobile devices, games, etc. This data is stored in a secure Learning Record Store, which can then provide automated data visualisations to support learners in understanding their progress.

In watching this third video, it seemed to me that there is a mismatch between Stephen’s aspirations for learner autonomy and the learning analytics systems being developed by Yet Analytics. Questions that were asked by Stephen and others on the course, were:

  • How would this work with distributed data (remembering that distributed data allows for choice, ownership and community, as well greater security)?
  • Who owns the data/records?
  • What are the ethical implications of these developments?
  • What are the privacy and governance issues?
  • How will the data tell us what learners have learned/understood, as opposed to what they have ‘done’, in terms of number of views, clicks on documents etc.

These are important questions for Yet Analytics to answer if they are really going to provide a system that goes well beyond what a traditional LMS can do and recognises a ‘personal’ learning approach to education.

Finally, as a result of watching these videos and thinking about learning analytics this week, I have wondered what might be the implications of measuring and monitoring everything we do. Is there a danger that it could be taken to excess, such that we treat our bodies like machines, become super-competitive, self-centred and self-absorbed?

Update 31-10-2018

Shelly Blake-Plock has pointed out that there are some errors in what I have written about his work, and has responded to the questions listed above. Please see his comment below.

Related blog posts

There have been some interesting posts from other course participants related to all this. See for example:

Geoff Cain – Week 0: Seimens and Downes on AI – http://geoffcain.com/blog/ai/week-0-seimens-and-downes-on-ai/

Roland Legrand – An Experience API for learning everywhere (also in virtual worlds) – https://www.mixedrealities.com/2018/10/25/an-experience-api-for-learning-everywhere-also-in-virtual-worlds/

Matthias Melcher – #EL30 Alien Intelligence AI – https://x28newblog.wordpress.com/2018/10/24/el30-alien-intelligence-ai/

Laura Ritchie – #el30 Notes Week 1 – https://www.lauraritchie.com/2018/10/25/el30-notes-week-1/

What is uniquely human?

In this first week of the E-Learning 3.0 MOOC, Stephen Downes has shared a video introduction to the course (see https://el30.mooc.ca/course_activity_centre.htm ) and also recorded a video of a conversation he had with George Siemens. This was really enjoyable to watch.

It has been ten years since Stephen and George offered the first ever MOOC on connectivism, which for me (without wanting to sound too dramatic) was a life-changing experience. On the back of that course I established myself as an independent education consultant and researcher, which ultimately led to a PhD by publication. More important than this was that it led to connections with people with whom I am still in contact and who are now personal friends. As George said, that first MOOC, CCK08, The Connectivism and Connective Knowledge Course came at a time of mass explosion of technology, extensive innovation and the emergence of shared intelligence. But, as George said, after this initial excitement, the last five years has felt a bit like a wilderness and many of the initial aspirations for a democratic open web have not been realised.

However, neither George nor Stephen has given up on their initial aspirations to democratise learning. Both think we are now entering an era of deepening understanding of learning. Each has approached this differently, although they both feel that connectivism continues to be relevant, if not even more relevant, to how we learn in a technological age, as technology becomes more prominent.

Stephen asked George to tell us what is his current work focus. What are the issues that concern him? This was where the discussion became fascinating. It centred around what it means to be human and what is human intelligence in a world where machines can learn just as we do. For Stephen there isn’t anything that is uniquely human. Anything organised in the right way can learn. If we can learn, machines can too; if we can come up with ethics so can computers. Computers can always learn more than we can. Unlike us, they don’t get tired and improve with more data. Machines are equally as smart as us. So, George asked, why are we teaching in a counter-intuitive way when systems/machines can do it so much more efficiently and in 50 years time we will all be working with robots?

Grappling with these questions, George is looking for what is uniquely human. He sees this as ‘being-ness’. I have heard him talk about this before to Neil Selwyn, and earlier this year wrote a blog post about their discussion  – Skills for ‘Being’ in a Digital Age . Stephen thinks ‘being’ is too fuzzy a concept to be useful, although ‘being’ seems to have exercised the minds of many a past philosopher, not least Heidegger. Despite this, I think Stephen nailed it when he said, ‘the most consequential things can’t be measured’. Perhaps, as Stephen suggested, ‘being’ can be recognised (without being measured, defined or articulated) in such qualities as ‘goodness’. We can probably think of similar qualities that it is hard to imagine a machine learning. George suggested that to understand ‘being’ we might need to return to traditional contemplative practices.

My current thinking is that ‘being’ is one of those ideas that cannot be made explicit without losing its meaning. It is something that we ‘know’, intuitively and empathically, without having to articulate it, and this knowledge is unique to each and every one of us. It is this that makes us different from machines.

This was a great discussion to have at the start of the course.

E-Learning 3.0 : some initial thoughts

This is the topic of a 10-week MOOC being offered by Stephen Downes, which started this week. For the course outline see – https://el30.mooc.ca/course_outline.htm . Stephen said somewhere that he was trying to create an elegant site for the course. I think he has succeeded. I love this simple image and title.

On this site Stephen writes:

The premise of this course is that we are entering the third major phase of the world wide web, and that it will redefine online learning as it has previously. The first phase of the internet as it was originally developed in 1994, based on the client-server model, and focused on pages and files. The second phase, popularly called Web 2.0, created a web based on data and interoperability between platforms. In what is now being called web3, the central role played by platforms is diminished in favour of direct interactions between peers, that is, a distributed web.

I missed the beginning of the course (I’m not even sure which day it did begin), being away on holiday in the Trossachs, Scotland, where ironically it was very difficult to get an internet connection and was impossible to stream anything. Whilst we might assume that everyone everywhere is connected all the time, my experience this week suggests otherwise. Nevertheless, given the influence of Web 2.0 on what we understand by ‘truth’ and how to live ethically in this post-truth world, it seems important to me to ensure that we at least have an inkling of the developments which will lead to Web 3.0.

I am now back from the beautiful wilds of Scotland and connected again and have watched Stephen’s video introduction to the course, in which he provides an excellent overview of what the course will cover.

He told us that the course would be structured around the outline depicted in the figure below and then talked briefly about each element of the diagram.

The basic premise is that because we are moving from a world of documents to a world of distributed dynamic data, Web 3.0 will be based on a linked open data cloud. This means that the approach to learning will change. It will no long depend on remembering, but instead on pattern recognition. In this model, knowledge is pattern recognition.

So far, so good. Stephen then went on to discuss the significance of the Cloud and Graph elements of his diagram. Here he lost me. He told us that anyone could learn this if we put the effort in and that through this we would learn how to create new types of distributed and connected learning resources. I found myself thinking that I have always like driving; I know how to change a wheel, and when opening the bonnet where to top up the screen wash and oil. I can even jump start another car if necessary, but beyond this I am not interested. I take the car to the garage and let someone else with years of experience sort it out. Similarly with technology. I am simply not sufficiently interested to get into the nitty gritty. I am not interested in learning how to programme or learning different computer languages. I think there will probably be more people like me than technical experts (although maybe not on this course!), so I wonder what the implications of this are for a distributed model. Further, I like the fact that I can come to this course and know that Stephen has the experience, has done all the work and is willing to share this. I am grateful to him for this and his generous openness, but it does not make me want to learn programming 🙂

To return to his presentation, I was more interested in what he had to say about identity and community. I agreed of course that in social networks we are the product and that we are being exploited by large corporations such as Facebook and Twitter, who are selling and making a profit from our data, and I was encouraged by Stephen’s suggestion that in Web 3.0 the quantified self will give way to the qualified connected self, not measured by numbers but by our properties, affinities and things we have created. Our identity will be the thread that runs through an otherwise distributed, disconnected set of data.  This made sense to me and I was intrigued by the idea that we will each have a private key to access the web. No more passwords!

I also appreciated his discussion about community, which he suggested will no longer be based on sameness, but on consensus and being able to make decisions together. This seems such an important point for education and for this to be able to function, as informed citizens, we will need some fundamental critical literacies, which he suggests are:

  • Syntax – the ability to recognise patterns
  • Semantics – the ability to assign the meaning, importance and value of something
  • Context – being able to identify something in relation to its environment
  • Use
  • Cognition – inference, deduction, induction, for the best explanation
  • Change – processes of change, regressions, cyclic change etc.

There was more about each point in his diagram, and there will be even more as the course progresses, but the key point is that a decentralised system is needed – a system which focusses on consensus and being able to make decisions together.

Having first heard Stephen’s and George Siemen’s ideas on the need for a decentralised, distributed, connected web ten years ago, when they ran the very first MOOC on connectivism in 2008, it is great to see how these ideas might be developing ten years on.