From summary

The tweet storm exercise

The dashboard analyses from Social Monitor and Tweet Archivist present the statistics in a nice visual manner. But I am not sure that they tell me anything I didn’t know, however, if I was presenting this information to others then they would be very useful.

The busiest time was Friday 13 March; certainly true for myself as I was able to participate on this day.  The topics under discussion, and the sites linked to, kept very closely to the course themes of algorithms, learning, education and data; this is not surprising as the questions we were primed with revolved around these. The hashtags look slightly different with #codeacts and #learntocode featuring very heavily;  I wonder if this was because most of the conversations did not use hashtags so when one was introduced it quickly made an impact on the statistics.

There were a similar number of original tweets and replies which imply that conversations were brief. However, it is also likely that because we were using Twitter synchronously people were not using the reply button in the conversations; possibly because they take up valuable characters. From my point of view, as a participant, it did feel that there were lengthy conversations with several participants taking place.

@SianBayne features as the most influential tweeter with the most mentions and the most klout.

 

 

Round up of week 9

Algorithms are everywhere; we depend on them to filter information for us.  There is so much information produced every day on the internet that we need help to sort through it, to find the important information and bring it to our attention.  Every time we install a new app on a device or sign up to an email list we are activating an algorithm and giving it permission to send us information often based on preferences we assign.

When we use an app we also give it permission to collect data on us. Spitz (2012) advises us that mobile phone companies collect data on us, such as phone logs, location based data, contacts etc. all of which could be used to create a profile of our daily lives and movements and networks.  In essence, it is a trade – our data in exchange for filtered information.

Algorithms do more than just filter data. There are learning algorithms (Zarkadakis, 2015) that are teaching the next generation of robot to become smarter. They can be creative – write poetry and stories (Podolny, 2015), or play music and dance (Bretan, 2015).  They are even giving us, humans, cause to make physical changes to the environment so that they can work more efficiently (Slavin, 2011).

But is the field of education keeping up with the rest of society in its use of algorithms?  Or are educators ‘behind the times’? (Selwyn, 2011).  With the relatively recent advent of MOOC style courses we now have a resource of ‘big data’ that can be used to identify and categorise student behaviour (Knox, 2014).

MOOCs are generating vast databases of information for researchers to interrogate, but inevitably, anything new has ethical implications that need to be dealt with.

References

Bretan, M. (2015) “What you say” – A robot and human musical performance. Available from: https://www.youtube.com/watch?v=O-bjTfYILPs [Accessed 15 March 2015].

Gillespie, T. (2012) The Relevance of Algorithms. In: T. Gillespie, P. Boczkowski, & K. Foot (eds.). Media Technologies. [online]. Cambridge, MA: MIT Press. Available from: http://www.tarletongillespie.org/essays/Gillespie – The Relevance of Algorithms.pdf.

Knox, J.K. (2014) Active Algorithms : Sociomaterial Spaces in the E-learning and Digital Cultures. Campus Virtuales. 3 (1), pp. 42–55.

NYTimes.com (2015) Did a Human or a Computer Write This?. Available from: http://www.nytimes.com/interactive/2015/03/08/opinion/sunday/algorithm-human-quiz.html [Accessed 13 March 2015].

Podolny, S. (2015) If an Algorithm Wrote This, How Would You Even Know?. Available from: http://www.nytimes.com/2015/03/08/opinion/sunday/if-an-algorithm-wrote-this-how-would-you-even-know.html [Accessed 13 March 2015].

Selwyn, N. (2011) Does technology inevitably change education? In: Education and technology: key issues and debates. London: Continuum International Pub. Group. pp. pp. 20–39.

Slavin, K. (2011) How algorithms shape our world. Available from: http://www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world [Accessed 16 March 2015].

Spitz, M. (2012) Your phone company is watching. Available from: http://www.ted.com/talks/malte_spitz_your_phone_company_is_watching [Accessed 13 March 2015].

Zarkadakis, G. (2015) Games Arcade Spurs Robot Evolution. Available from: http://www.huffingtonpost.co.uk/george-zarkadakis/garobot-evolution_b_6837378.html [Accessed 13 March 2015].

Show and Tell: Algorithmic Culture

My puppy dog Google Instant search results:

puppy dog search   bitch dog search

As expected.  Coincidentally, I came across a list of blacklisted words during another exercise – this list was held by Shutterstock who explain how / why they use a list: “Miscellaneous caveat: Clearly, what goes in these lists is subjective. In our case, the question we use is, “What wouldn’t we want to suggest that people look at?” This of course varies between culture, language, and geographies, so in the end we just have to make our best guess.”  

I also completed the Facebook challenge which did show different results but due to my almost total lack of use/interest in Facebook I was unable to determine why the results differed.

So on to the final challenge – Google Ads. I was under the mistaken impression that I had turned Cookies off, but then I remembered that I had turned them back on to use the Collusion app (a cookie tracking app).  Anyway I had 20 results. Not surprised by the ISPs and Phone Service Providers as I have a very troublesome broadband connection.  But what on earth is Executive Branch?  The Dictionaries entry made me smile as I regularly use the Define or Synonym keyword on Google when I need help :)

interests (Click on the picture for the full list)

My immediate response to this exercise was to opt out of interest based ads on Google.  I really don’t like these; I find it very invasive when these ads appear, I much prefer the random ads.

 

 

Week 3 overview: globalisation

Technically it is true that the internet allows digital artefacts to be everywhere (Hand, 2008) , however, in practice, it is only ‘there’ once it becomes part of a ‘node’ in a network and is discoverable.  That is, the internet contains a vast amount of information, most of which, I could access. But it is only after it has been indexed by a search engine that it becomes discoverable to me, or after it has been shared with me through a personal network such as Twitter. Even then, there are other factors affecting discoverability, such as the algorithms used by search engines.

Mind also raises the issue of communities arising around shared concerns through the power of the internet, and influencing governmental or political authorities. An example of this is a recent, national, news story involving an Academy applying a rule to a pupil who had contravened it. The story got out on the internet and traditional paper based media, and a community formed against the school decrying the indiscriminate application of rules; the Academy has since reconsidered its stance (The Independent). Authoritative bodies, including educational institutions, are now having to consider how they apply their policies more carefully, as they are more likely to be held to account.

Mind considers the vertical structures of organisations to be in the past, with a progression towards networked structures. Information will flow through these networks in many directions.  Potentially anyone could become part of a network and be empowered by the information they access, and in turn, influence the network, creating a feedback system.

To my mind, there is a flaw in this type of reasoning. Information is disseminated freely to all; informed debate may occur but this could be overshadowed by the vast majority of uninformed commentary.  On the other hand, any discussion is better than no discussion at all.

Hand, M. (2008) Hardware to everyware: Narratives of promise and threat. In: Making digital cultures: access, interactivity, and authenticity. Aldershot: pp. 15–42.

 

Week 2 overview: Ethics

The more I look at ethics the more fascinated I become.

The world is changing at such a pace that the law just isn’t keeping up, and we desperately need a moral imperative to keep us on the right track. It’s easy for a company to keep on designing and building new tech without any regard for how it will be used in the future. This has become apparent with the recent stories of drones being used to smuggle drugs and other contraband across prison walls and borders.  And the companies that are replacing their human workforces with computers.

But can we just stop developing new technologies because it could have a negative impact on humans. What about the good it can do? Such as robots that can be sent into disaster zones that are unsafe for humans to enter.

Fortunately, some governments are beginning to take notice of the new technologies and their ‘downsides’, and are proposing new legislation or ‘ethics frameworks’.

 

 

 

Anon (2015) Drone carrying drugs crashes near US-Mexico border. Available from: http://www.bbc.co.uk/news/world-latin-america-30931367 [Accessed 23 January 2015].

Gillmore, D. (2013) With robots and data, can Google keep to its promise not to be evil?. Available from: http://www.theguardian.com/commentisfree/2013/dec/19/google-robots-data-boston-dynamics-possibilities [Accessed 25 January 2015].

Lo, A. (2015) Debate over artificial intelligence raises moral, legal and technical questions | South China Morning Post. Available from: http://www.scmp.com/lifestyle/technology/article/1690723/debate-over-artificial-intelligence-raises-moral-legal-and [Accessed 25 January 2015].

 

 

 

My early reflections on the module

I am going to reference a post here from another student, Katherine Firth, because the video came from here: http://edc15.education.ed.ac.uk/kfirth/2015/01/19/bayne-2015/.  I did consider posting this as a comment, but it didn’t really follow the ongoing conversation.

Anyway, this was a new video to me, and gave me food for thought. It highlighted, for me, the importance of the social element in learning. How the teacher not only imparts knowledge to their students, but also attempts to “inspire, challenge and excite their student to want to learn.”  And how we learn as a group, not as individuals.

So some observations about how I feel about this module:

I miss having forums in a course.  If I want to say something that is off-topic but related, I can start a new thread, or just reply, and the replies can branch but still be followed.  Not possible here in a linear commenting interaction.  Each conversation is discrete; it’s very hard to link conversations together.

I miss hearing the voice of the tutors. I know they are active in each person’s lifestream but I have to look for them. It’s disjointed, like an unstarted jigsaw puzzle. All the pieces are there but I haven’t worked out how to put them together to see the whole picture.

I don’t feel as connected to the other students and the lecturers as I did in other modules.

On the positive side I am enjoying the lifestreaming; it’s new and I love having the finished blog pages with all of my thoughts and research together in one place.  And I am starting to find new ways to listen to everyone – e.g. following the ‘recent comments’ block on the main course page.  I also need to start using Twitter to hold conversations.

Overall, I like it.  It’s just going to take me a while to get used to the new style of interaction.

Review of week one

I remember watching the film about memory, and the one with the robots in the car, but for the life of me, I can’t remember the third video! My memory is unreliable; I do rely on technology to remember things – calendars / tasks. This week, I have been trialling a Livescribe Echo pen which has been recording meetings for me, word for word, but in a way that I can instantly access (remember) a particular part. Already I am missing the pen and my enhanced memory after having only used it for a few days. memory1

But in a few years time, we will be able to do so much more. Jason Sosa (2014, 7m50s) demonstrates that technology has now reached a point where our memories can be reconstructed, erased and/or implanted by artificial means; potentially useful in treatments for post traumatic stress, alzheimers or dementia. He also demonstrates images that have been reconstructed using MRI scans of brain activity – we can actually see what another person is experiencing / thinking. Imagine if we could record these on a memory stick? We would never have to take notes in a lecture / meeting again. We would have perfect recall.

memory3

This week has also introduced me to concepts new to me, transhumanism and posthumanism, and I am looking forward to examining these in more depth.  I am particularly fascinated by the ethical dilemmas surrounding the introduction of new technologies and how they are integrated into our society.

Spooky happenings – just published this blog and checked in on Twitter to find that Google have patented an AR device using some very odd gender stereotypes (O’Kane, 2015).

Magic leap

O’Kane, S. (2015) See the beautiful, nightmarish patent illustrations for a Google-funded augmented reality device. Available from: http://www.theverge.com/tldr/2015/1/17/7559473/google-magic-leap-patents-drawings [Accessed 18 January 2015].

Sosa, J. (2014) The coming transhuman era. Available from: https://www.youtube.com/watch?v=1Ugo2KEV2XQ#t=478 [Accessed 16 January 2015].