Comment on Algorithmic Play by dyeats

Thanks Jon, very interesting artefact and the conclusion for application in education is compelling. That approach would definitely support the push for personalised learning. I wonder how much further personalisation has to go and how it will change public education? The old school might argue that reading something you don’t like or aren’t interested in is an essential part of education. If an algorithm removes those readings from a students reading list based upon what they have disliked reading before, what unforeseen results might this have?

If you ever want to revisit the chatbot stuff, there has been some progress in that area with QBot in MS Teams :
https://youtu.be/NcbQ2UK69Tc
and:
https://github.com/unsw-edu-au/QBot

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Week 10 Summary

This is a very belated week 10 summary as week 10 itself (16th-20th March) was a blur of writing and running workshops, training academic staff on how to deliver their subjects online, trying to un-buy a house and generally keep safe and prepare for the Coronavirus’ descent on Sydney.

So apart from the Google Hangout meeting we had, I barely engaged with the course in a direct way and didn’t record much on the lifestream apart from a comment on Sean’s comment on my artefact.

I also managed to upload the 2nd half of the podcast on Algorithmic Cultures. And then finally ot around to writing my summary for week 9.

In all honesty, it has been hard to maintain motivation with everything else going on and a great deal of visceral uncertainty and tension in the atmosphere.

This has been significantly ameliorated over the last couple of days by us being able to find a place of our own to stay in. We had been housesitting for the last 16 months, but that all ground to a halt very suddenly with the pandemic preventing travel.  Now, we’re settled in a what would usually be a holiday flat in South West Rocks NSW.

As we had only a matter of days to find accommodation, and Sydney’s rental market is absurdly difficult to get into, we contacted an agent here in SWR and they said they’d be happy to rent to us for a much reduced price. Renee’s family are from this area so, it’s familiar to us both and a kind of second home already.  With that decided, we jumped in a borrowed and rusty Subaru and drove the 6 hours to get here.

Working from home means that the key consideration was having a wifi connection. Getting this going was a costly exercise but the easiest choice I could think of which was a portable Wifi Modem.

Now, what does any of this have to do with Digital Cultures and more specifically this lifestream blog?

Well it’s clear that I’m in a very privileged position of being able to simply pack up and leave and still have a job while hundreds of thousands of others in my city are out of work indefinitely. Part of this is simply due to the digital nature of my work. I can consult with academics digitally, I can produce work and share it digitally, communications, digital, and the sector my job is devoted to is almost entirely based-upon digital technology.

But this digitality of my work in education belies the fact that for the receivers of this work, the ability to access the digital is not a given. The great assumption of all edtech really is the idea of equity of access.

This is particularly sharp now when the task assigned to many educators is to make their teaching fully digitally available. For many, this simply means turning lectures and tutorials into video-conferences for students to access from home. Home.

That word, that place can be taken for granted so easily. When we say ‘work from home’ or ‘study from home’ , it’s getting harder to ignore the fact that some students may not be able to afford to do that much longer. I suspect this will be the sharpest point for many international students as well, who rely on their casual employment to support themselves and can’t yet access government welfare services. The response of educational institutions will be central. We may come out the other side of this praising the work of digital education forgetting how many students were either completely excluded from studying or who had to give up some basic right to privacy to an EdTech company serving institutions.

I sure hope not.

Comment on This is my algorithmic play with youtube, I hope you all have enjoyed this activity! https://t.co/zvHmW3n2Ue #mscedc by dyeats

I really thought this point you made is very insightful:
“apopheniac results of algorithms can be seen by educators, it can create the wrong prejudice about students which makes educational decisions more difficult.”

I also like that word “apopheniac”! Will have to add it to my vocabulary.

Very interesting result with regards to the ‘zero-waste’ search. That content provider obviously has a powerful grasp of how to increase views and be put first in YouTube’s recommender system.

To you recommendation about the need to intervene in education, I would add that there is need to provide space for reflection on results and for students to not just analise the content of their work, but how they arrived at that content. There are obviously other forces at work which direct us to certain sources of information and therefore the way we acquire and build up knowledge.

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New Comment

Hi Val,
I haven’t even got past the first page of your artefact but I’m already saying YES! Exactly! right on!
Excellent way to frame the algorithmic play with all that context.

Thank you also for providing an analysis of Amazon’s algorithm. The flow chart you created effectively illustrates how it works to my understanding.
You engaged in such thorough, detailed and diverse play.

Your point that “Amazon™ can easily fit the pattern of learning platforms like EdX or Coursera” reminded me of this article in which https://nepc.colorado.edu/blog/amazon-coming-school

I didn’t get to read your Netflix piece yet, but enjoyed the response of your Google Assistant.

Great stuff!

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Comment on Algorithmic play artefact : teaching@digital podcast: by dyeats

Thanks for highlighting those points Adrienne. I still wonder whether the social network principle is merely reflecting the human social landscape or whether, as you brought out in your artefact, the entanglement and influence of the digital landscape has changed our perception of work, study and capital in more profound ways than we are aware?

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Comment on Comment on #mscedc My algorithmic play artefact: https://t.co/n2L6TTwenI by dyeats

Thanks for sharing this one Iryna! I’m glad I’ve finally been able to watch it.
Very profound findings which show just how much Google, Yahoo, Bing and Baidu (among other) search engines have become powerful advertising platforms.

The old idea that you can create amazing relevant content and it will jump to the top of the search results is well and truly dead and gone. In fact, I can’t quite remember who it was who described Google and Facebook this way first, but they a primarily advertisers. “Search” and “networking” are now not even secondary or tertiary objectives of these platforms anymore.

This marketing agency agrees: https://www.pageonepower.com/linkarati/google-not-search-engine-advertising-platform
They claim to have worked out the best formulas for getting your content out there on the search engines.

Thanks again for sharing your work. Very thought provoking and insightful!

https://edc20.education.ed.ac.uk/ialtukhova/2020/03/15/mscedc-my-algorithmic-play-artefact-https-t-co-n2l6ttweni/#comment-64

Comment on Algorithmic Play Artefact by dyeats

Hi Adrienne,
Really enjoyed how much you were able to expose the workings of algorithms across major platforms.
I think my key realisation from what you said and the references you drew on from Knox, Williamson and Kitchin was that if you really look, the work that algorithms do is clearly visible in our consumption of culture now.
The entanglement of the human and non-human in generating our own digital culture is clear to see. Even if we don’t understand the underlying science of algorithms, their behaviour and impact can’t be ignored.

You made excellent connections and analysed what you saw in your suggestions very carefully. The analysis of the impact of demographic data caught my attention too. This is where an argument can be made for the motivations behind algorithm design. On the one hand we could say, the system works to benefit us because there is just too much data for any one individual to wade through in order to find something they like or something that is relevant to them.
On the other, there is the fact that this creates an echo chamber of ideas and people who think and look like the ‘customer’ using the algorithm. Thus, as we have seen in recent history it becomes much easier to politically manipulate vast swathes of a particular demographic without any oversight or awareness from the regulatory systems.
Great artefact, I’m glad I’ve finally had time to look at it.
Thanks!

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