The Education and Digital Cultures 2015 course has finally come to an end and I would like to take this opportunity to look back at the last 12 weeks and thank my colleagues and my tutors Sian and Jeremy for this highly interesting journey into the land of cyborgs, algorithms and artificial intelligence.

Keeping a lifestream blog has been a new experience for me and while it did take some time, effort and, dare I say, frustration to set it up correctly, over the duration of the course it has grown into an excellent collection of resources for me to come back to.

Adding tags to every post was an incredibly helpful way to organise my lifestream according to different parameters such as source, type or topic. The tag cloud on the right shows a nice visual representation of this endeavour and gives us plenty of insights into the lifestream as a whole.

As we can see IFTTT is the biggest tag, meaning that around 3/4 of my posts were automatically populated from social media sites like Twitter, YouTube, Vimeo and Pinterest with the help of the IFTTT service.

In terms of types of content I shared a variety of videos and articles that I thought were really interesting and relevant to the discussions we were having during the course. In addition to the weekly recaps and my comments on my peers’ and my own blog I also posted two how to guides to help my fellow students set up their lifestream. Furthermore there are one-off postings like the digital artefact from block 1, the mooc ethnography from block 2 and my reflections on the tweetorial from block 3 of our course.

I didn’t really know a lot about the topics covered in this course before the semester started. It was therefore a very pleasant surprise for me that the themes we discussed were extremely fascinating and they challenged me to think about issues I had never considered before. I’ve been hearing about artificial intelligence all my life but I had never actually contemplated how vast its implications are going to be, not just in the field of digital education but for humankind in general and society as a whole.

This course has made me think about what it means to be human in an age where the lines between biology and technology are being increasingly blurred with biohackers substituting and even adding new senses to our biology. We are living in a time where computer algorithms are not just taking over more and more tasks that humans used to do (such as trading in the financial markets) but thanks to big data are now able to do things that weren’t even possible before, like personalised search results and video suggestions based on profiles of people similar to you.

Technology does an exceptional job in connecting people and I see a lot of potential in it to facilitate education for everyone, as shown by the development of MOOCs. Moreover, thanks to learning analytics algorithms could uncover as of yet unknown patterns in how the mind works. All this, however, comes at a hefty price: Privacy. The more information we are willing to quantify about ourselves the more we allow certain entities to know about us. If we don’t ever want that knowledge to be used against us we have to become much more conscious about the issue of privacy and data security going forward. How we will react to these issues will be one of the defining moments of the 21st century.

Now that the taught section of the course has come to an end my main objective for the last two weeks of the course is to clean up the lifestream blog for final submission and coming up with a research question for my final essay.

Although I hadn’t planned to add additional content this week I couldn’t pass up on the opportunity to share this excellent TED talk on YouTube by Stanford professor Fei Fei Li on the newest advancements in machine learning, an overarching theme in this course and one of the most exciting topics I’ve learned about in a long time. All throughout this course I’ve been wondering if once artificial intelligence surpasses our own where this will leave us humans and our human education. Might such a takeover happen before education (at least in its institutionalised form) even embraces some of the radical changes promised by Technology Enhanced Learning? Will there even be a need for education in a world where all important cognitive tasks are performed by sentient machines or will education be an optional activity for those so inclined similar to what learning a musical instrument is in today’s society?

I’m currently in the process of going through every post of my lifestream, fixing links, embeds and tags. Once I am finished with that I will be posting a final summary by the end of next week.

Another week has gone by far too quickly and looking at  the content in my lifestream this week the main theme “putting it all together” seems rather fitting as I’ve been collecting interesting material that covers not just block 3 of algorithmic cultures but topics from the whole course.

The first post this week was an incredibly well done sci-fi short film I saw on Vimeo, called “Sight” on how augmented reality and gamification might drastically change the way we live and interact with each other in the future.

Next I linked to an interesting article I found on Twitter in the International Business Times that discusses the influence of content-curation algorithms and their inherent biases. It shows that people are often unaware of algorithms working in the background and when learning about it they often exhibit quite “visceral” reactions, followed by a change in their behaviour to accomodate for the algorithms.

Another great longform article I found on the Verge discusses the possibility that memories might be able to survive outside of the brain which reminded me of the discussions we had when we explored posthumanism in the earlier weeks of the course.

The following post was an in-depth reflection on last week’s tweetorial where I looked at what we can learn from tools like Tweetarchivist and Keyhole which algorithmically analysed the conversation we had on Twitter.

This week a couple of new talks from the latest TED conference showed up in my YouTube newsfeed and one of them in particular caught my attention as it was a new talk by neuroscientist David Eagleman whom I had previously talked about in this post. While his main talking points were the same as in his previous video he offered some new results that look very promising. His sensory substition vest, for example, seems to work very well in teaching a deaf person to hear. I am still just as excited as the first time I heard about this research. Maybe sensory addition really is just around the corner.

Finally I linked to a short animated TED-Ed video on whether robots can be creative. This video explores algorithms that to come up with pieces of music which they then iteratively compare with music that humans consider to be “beautiful”, discarding the patterns that do not match and keeping the patterns that do. The results are remarkable to say the least. To an outsider the music these algorithms create sounds very much like it has been composed by a human being.

Now that the end of the course is drawing closer it is time to turn my attention to the final assignment. In the meantime I would like to say thank you to our exceptional course tutors Sian and Jeremy and my wonderful colleagues for the many thought provoking and highly engaging discussions I’ve been blessed to be a part of over the last 3 months.

Week 9 has ended and we have continued exploring the world of algorithms and turned our attention to the specific applications of algorithms in education in the form of learning analytics.

It was fascinating to see what my colleagues came up with for last week’s exercise in exploring the algorithms used by internet companies to give their users individual suggestions and recommendations. Following up on my own explorations I delved into some issues raised by Jeremy, especially concerning privacy implications – in my mind the most pervasive and pressing issue surrounding the growing use of algorithms in our lives.

Later in the week I turned my attention to Twitter, reading and replying to my colleagues’ tweets as well as participating in this week’s scheduled EDC tweetstorm.

One particular question we were asked was what we give to algorithms and what they give us and I tweeted “We give them our history, they give us our future.” This statement was on purpose meant to be ambiguous. On a more surface level one could interpret it as us giving algorithms our search history or watched videos history and they recommend to us sites or videos we will watch in our future, thus shaping our future. In my opinion this goes even deeper however. Algorithms that predict the weather include not just historical weather data but also our own  current understanding of maths, systems dynamics and meteorology – all developed in time. Especially in light of artificial intelligence it seems more and more likely to me that we are soon to be passing on the torch of knowledge creation to entities that will not be limited by their phyical and biological boundaries.

Considering the issues of learning analytics I see that in the future they will be able to considerably help people in their learning endeavours in a variety of ways. My prediction will be that models based on biofeedback, like heart rate, skin conduction, pupil dilation, blink frequency, brainwave measurements etc will be one day used to guide the student to maximise learning, perhaps by signalling perfect learning window times. As previously mentioned, such massive tracking carries its own set of problems, particularly with regards to privacy and data security.

To round things up this week I stumbled upon a new fun little game by Google that lets you play around with its autocomplete suggestion engine, scoring points for correctly guessing its guesses.

The first week of block 3 on algorithmic cultures has ended and as expected it was a very informative experience delving into the depths of algorithmic cultures.

To finish up last week’s ethnographic song I started this week’s lifestream with some more detailed observations about the songwriting MOOC’s community culture.

Next, I dove right into this weeks topics of algorithms with a fantastic talk by Kevin Slain on how algorithms shape our world. Mr Slain shows the fascinating world of financial algorithms that have largely taken over control of the global financial system in the last decade. Expanding on this trend I can wholeheartedly recommend last year’s bestseller book “Flash Boys” by Michael Lewis.

Staying on the topic of algorithms and the financial sector I started to explore the topic of cryptocurrencies such as BitCoin which is based on the blockchain algorithm, a cryptographically protected trustless accounting ledger that many people see as one of the biggest revolutions of the 21st century. Building on the principle of the blockchain developers have already started to expand the framework to not only include currencies but also social contracts, financial markets, property rights and e-government. A truly fascinating Harvard lecture on Ethereum, the platform on which these blockchain contracts are being executed, shows the dangers and possibilites of these brand new developments.

The following day I once more turned my attention to this exceptionally well written and thoroughly researched longform article about artificial intelligence – an incredibly long, but nonetheless fascinating, thought provoking and even frightening elaboration on the implications of artificial superintelligence. Expanding on that, I posted a video by Nick Bostrom, one of the more prominent thinkers in this field.

Finally, I posted my findings on this week’s task of exploring and playing around algorithms employed by technology companies in their web offerings. I used the YouTube recommendation engine to examine this topic, finding plenty of evidence for the often cited “filter bubble”.

It will be interesting to see next week how algorithms can be used to specifically improve education outcomes.

Block 2 has come to an end and I am currently admiring the amazing ethnographies my colleagues have put together over the last few weeks.

While further delving into my songwriting MOOC and internet communities culture I found a very interesting article in The Telegraph about the different “laws” that govern internet culture. In addition to classics like Poe’s Law, Godwin’s Law or Rule 34 the article describes some highly amusing ones like Danth’s Law or The Law of Exclamations. A blatant omission (which was thankfully added by a commenter) is a favourite of mine – Cunningham’s Law: The best way to get the right answer on the Internet is not to ask the question, but rather to post the wrong answer.

Staying on the topic of artificial intelligence which has been following us throughout the course and has recently been present in the media I stumbled upon this speculation about what will happen when the Internet of Things becomes artificially intelligent. It is a fascinating thought to think that  instead of machines having their own individual intellectual capacities (like humans do) the connectedness of all things digital will create one global artificial consciousness. The internet as we know it might very well be the brain of this operation, the underlying infrastructure. It just takes a decade or two more until its consciousness switches on.

Talking about artificial intelligence, DeepMind, a machine learning company owned by Google has anounced this week that its AI has learned to play 49 Atari games from scratch through trial and error. In 29 cases it performed even better than human players. At this pace of development this technology is likely to disrupt society faster than we will be able to react to the changes.

Finally, I posted my micro-ethnography about my songwriting MOOC, fittingly in the form of a song.

Next week we will start a new block on algorithmic cultures. Considering the buzz that machine learning has generated lately I’m sure it will be highly topical and I’m very much looking forward to it.

Another week has ended and we are three quarters through the second block on MOOCs and community cultures.

My course on songwriting is going really well and I have started writing my first lyrics according to the structural framework provided in the course. It will be interesting to see how the elements will come together further down the line.

My lifestream this week once more had a focus on MOOCs. After last week’s news that the tech industry is accrediting Coursera courses I was drawn to this article via Jin’s tweet which is a fascinating in-depth analysis of the MOOC industry from a couple of months ago. While the jury is still out on whether MOOCs can create a sustainable business and stay relevant in the marketplace, it is great to observe the creativity with which this nascent industry is coming up with experimental business models.

As my previous how to manual was well received by my colleagues I followed it up this week with another little guide on how to make your lifestream more effective with the help of tags which I also announced on Twitter. As the lifestream grows it can look a little cluttered at first sight after a little while. Tags can help to put some order back into things.

Lastly, my colleague Ed tweeted a fascinating network analysis of reddit which analysed 84 million comments by 200 thousand people. It gives a very real overview of what topics are of interest and are being discussed within the reddit community.
Analysing large datasets to generate understanding is one of the main approaches in artificial intelligence and this topic ties really well into our first block and likely the third one too. I’m already looking forward to it.

Week 5 of our EDC course has  ended and we are well on our way exploring MOOCs. In my case, I’ve been developing ideas for my course on songwriting. So far I’ve been learning about a variety of tools I can use to write a song in a very structured process. As the course progresses people are using the discussion boards more and more which will be interesting to see over the following weeks as I work on my ethnography.

In our Hangout this week we discussed the ethics of researching within MOOCs as well as the chapter on netnographies by Kozinets  which I found particularly useful as reading it somehow felt like I was seeing knowledge I had intuitively gathered from my own experience verbalised in a very distinct fashion. My classmate PJ developed an excellent summary of Kozinets’ main talking points which I’ll gladly use as a reference in developing my netnography.

Considering the wider issues of the future of education I stumbled upon three interesting pieces online which I felt were worth sharing on my lifestream. One was a TED talk by Brazilian entrepeneur Ricardo Semler who has chosen to use wisdom has his guiding force in life, running his company very successfully with a radical focus on participation and transparency. With this democratic ethos in mind turned his attention towards education to improve the way schools are run and children are taught. The results so far seem to be very promising.

Another article I stumbled upon was about how Coursera has recently started to collaborate with tech industry giants Goolge and Instagram as accreditors for their online courses. While there are reasonable objections to be raised here – the most striking one being that the tech companies are essentially outsourcing business projects to students and paying with their good name. They’re profiting heavily from the vast problem solving capacity of crowdsourced MOOCs while the students are merely rewarded with an “accredited by Google” stamp they can put on their CV. Nonetheless, it is good to see MOOC providers finding revenue models to sustain their business without resorting to tuition.

Finally, I found a guest editorial by Bill Gates on The Verge about the future of online courses and their possible effects on the developing world – a well rounded analysis of the promises and challenges that lie ahead in trying to educate students in the third world by means of educational technologies.

This week we started exploring block 2 of our course on community cultures.

My first lifestream entry this week was a tweet that I signed up for MOOC on Songwriting by the Berklee College of Music which just happened to begin on Feb 4 and runs over the course of six weeks. Ideally, at the end of the MOOC I will have written a song – a challenge I set myself for new year’s and which I’m also documenting in my Understanding Learning in the Online Environment course of this MSc programme.  Over the following few weeks I will be exploring this MOOC’s community as part of my ethnography assignment for block 2.

While technically still related to the last block (and possibly the next one) I also posted an extremely fascinating video by Ray Kurzweil in which he talks about his preditctions for the future and how it will likely change society.

Regarding last weekend’s visual artefact, I was very impressed with my colleagues’ creative works such as Jin’s artefact on Pearltrees. I furthermore elaborated my thoughts on my own visual artefact in this comment.

Covering this week’s topic of MOOCs, I found a great TED talk on Twitter by Daphne Koller, founder of Coursera – one of the most successful of these platforms. Her bold vision for the future is truly captivating but this profile on Sebastian Thrun, a competitor of hers, shows that reality has not quite matched the founders’ initial expectations.

Finally, my last post was a wonderful video I found on Twitter – a digital ethnography by Michael Wesch summarising the characteristics of students in today’s system of higher education.

The first block on cyberculture is concluded and it’s once again time to look back on what items have popped up on my lifestream.

A lot of my reflection this week happened while reading and commenting on my colleagues’ blog posts. Issues contemplated were filter bubbles resulting from increased algorithmic personalisation, the problematic nature of ideology laden terms or the changing nature of learning in the future, from an active model of understanding to a passive model of information download using technology.

This week I continued bugfixing IFTTT to work out ways to populate my lifestream from different sources. I created this guide to help my fellow colleagues automatically post blog comments to their lifestream.

A very interesting video I saw this week was this TED talk by Ray Kurzweil, a famous futurist and current Director of Engineering at Google, on the future of the human brain. In full transhumanist fashion he describes a future where the brain’s biological neocortex will be connected to a synthetic neocortex in the cloud through nanobots in our bloodstream, allowing us to no longer be constrained by our bodies’ physical limitations. As elaborated in this comment of mine such a hybridisation of the biological and the technological would finally warrant the as of yet problematic terminology of ‘Technology Enhanced Learning’.

The ongoing discussion in the media about whether artificial intelligence will be the harbinger of humanity’s doom inspired me to create this week’s visual artefact. My intentions were to present a dire vision of the future with black humour using memes, the epitome of digital culture.