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ABC logoA few weeks back, I had a conversation on Twitter with Natasha Mitchell, presenter of ABC Radio National’s Life Matters, about smartphones and just how much data they’re handing on to, well, all manner of organisations. This morning we came back to that conversation live on national radio.

Do you know what data you’re really sharing, and with whom, when you download and use smart phone apps? Companies are collecting as much as they can get away with, says Stilgherrian.

We spoke for 20 minutes and covered a lot of territory.

If you want to know more, then you can listen to my guest lecture at University of Technology Sydney (UTS), and then follow the links to more than 30 references.

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The audio is of course ©2014 Australian Broadcasting Corporation, and it’s served here directly from the ABC website.

Title card for "Algorithms and the Filter Bubble"On Monday 7 April, I delivered an updated version of my guest lecture to media students at the University of Technology Sydney (UTS), “Algorithms and the Filter Bubble”. And here it is.

What’s is about? It’s about what we now call — this year at least — “big data” and how that’s changing how the media works, just like it’s changing every other part of society.

I cruise through what all this data is, where it’s coming from, who’s collecting it and where it’s going; what advertisers and media companies and others can do with this data; and some speculation about how this might unfold in the future.

There’s links to all the references over the fold, and you can follow along with the slides (PDF). The recording picks up immediately after I was introduced by the course coordinator, Dr Belinda Middleweek. A transcript may or may not follow at some point in the future.

Some people mentioned that last time it was difficult to follow some of the slides, as the PDF file didn’t show how the builds happened, so I may add a video slideshow version at some point too.

The audience was primarily first and second year students at the beginning of their media studies degrees.

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[If a transcript ever becomes available, this is where it will appear.]

What was left out at the end

I didn’t keep a close enough eye on the time, which is most unprofessional of me, so I had to drop a couple of things at the end of the lecture. So what did we miss?

My planned closing was to speculate a little more about the implications of all this technology — essentially the material covered in references 26 through 30 below.

When advertisers and newsmakers know all about you, including where you are and what you’re interested in, and when robots become so good that they’re able to tailor news and advertising precisely for your interests and current state of mind — what does that mean for political persuasion, and other kinds of persuasion?

Watch the videos of the robots from the US Naval Research Laboratory responding to everyday human speech. Consider Apple founder Steve Job’s comment that the iTunes Store gives you “freedom from pornography”. Consider than in a world of filter bubbles, some news outlets with a political agenda might want to give you “freedom from confusing thoughts”. After all, Apple has already blocked from their App Store an app that provided information on US military drone strikes.

Just where might this go? As I told the media students at the start of the lecture, they are the ones who will be creating this future for themselves and their descendants, not those of us in the second half of our lives.

Licensing and Re-Use

This work is made available under a Creative Commons BY-NC-SA license. This presentation may be re-used for non-commercial purposes within the terms of the Creative Commons license. The non-commercial and share-alike conditions are required to adhere to the licensing of the imagery used. Please contact me if you require an alternative version. As a minimum, attribution should read: “Source: Stilgherrian.” Online versions must link the word Stilgherrian to the website at stilgherrian.com.

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Hitachi Data Systems privacy law graphic: click for whitepaperAustralia’s new privacy laws come into force on 12 March. On 12 February, four weeks before the new laws come into force, I hosted a panel discussion on dealing with these new law for Hitachi Data Systems.

The panelists were lawyer Alec Christie, a partner in the intellectual property and technology practice of global law firm DLA Piper; Jodie Sangster, chief executive officer of ADMA, the Association for Data-driven Marketing and Advertising (which used to be called the Australian Direct Marketing Association); and Adrian De Luca, chief technology officer for Hitachi Data Systems in the Asia-Pacific region.

Over the fold is the full 58-minute video. This was done as a Google Hangout, and since there were some internet glitches the video is a bit glitchy too, but the content itself is great.

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FIVEaa logoI continue to be pleased that digital privacy issues are getting more and more coverage in the mainstream media — such as the interview I did last Monday 20 January with radio 1395 FIVEaa in Adelaide.

Presenter Will Goodings had spotted the story of Turnstyle Solutions in Toronto, who can track people around town via their smartphones and use that location data for marketing.

Rather stupidly, I talk about Australia’s Privacy Act being “under review” when in fact that review is well over and the new Privacy Act comes into force on 12 March.

We also spoke about the US Federal Trade Commission (FTC) forcing Apple to refund $35 million to customers who’d had their kids make what they felt were unauthorised in-app purchases on their iDevices.

It’s something the Australian Competition and Consumer Commission (ACCC) has been concerned about too, and they have a page to explain how you can block in-app purchases or complain to Apple or Google.

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The audio is ©2014 dmgRadio Australia, but here it is ’cos it hasn’t been posted on the radio station’s website. Besides, this is a reasonable plug.

Title slide for Algorithms and the Filter BubbleAnd here’s the second version of my guest lecture at the University of Technology Sydney from Monday afternoon.

Pretty much everything I said about the morning lecture applies to this one, including the link to the slides

All of the references mentioned in this lecture are listed in the previous post.

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[When the transcript becomes available, this is where it will appear.]

This work is made available under a Creative Commons BY-NC-SA license. This presentation may be re-used for non-commercial purposes within the terms of the Creative Commons license. The non-commercial and share-alike conditions are required to adhere to the licensing of the imagery used. Please contact me if you require an alternative version. As a minimum, attribution should read: “Source: Stilgherrian.” Online versions must link the word Stilgherrian to the website at stilgherrian.com.

[Update 29 August 2013: Fixed broken link to the slides.]

Title slide for Algorithms and the Filter BubbleAs foreshadowed, on Monday I delivered an updated version of my guest lecture at the University of Technology Sydney, “Algorithms and the Filter Bubble”. And here it is.

There’s quite a few changes from the lecture I gave in March, because I wanted to update some key examples.

In fact there’s two versions of the lecture, because I presented it twice — once at 0900 and once at 1300 — and some of the content was improvised around my moderately detailed notes. So I’ll bring you both versions. This is the first, with full audio and the slides.

The repeat of the lecture later in the day was slightly different.

There’s links to all the references over the fold.

As previously, the recording picks up immediately after I was introduced by lecturer, Dr Belinda Middleweek. A transcript may or may not follow at some point in the future.

The audience was primarily first and second year students at the beginning of their media studies degrees. Again, it seems that almost all of this material was brand new to them.

Play

[If a transcript ever becomes available, this is where it will appear.]

This work is made available under a Creative Commons BY-NC-SA license. This presentation may be re-used for non-commercial purposes within the terms of the Creative Commons license. The non-commercial and share-alike conditions are required to adhere to the licensing of the imagery used. Please contact me if you require an alternative version. As a minimum, attribution should read: “Source: Stilgherrian.” Online versions must link the word Stilgherrian to the website at stilgherrian.com.

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University of Technology Sydney logoApparently I’m not scary enough for the University of Technology Sydney (UTS). My guest lecture earlier this year, Algorithms and the Filter Bubble, is now a regular fixture.

I was rather chuffed to be told a few weeks ago that the students had voted it the best lecture of the semester, and their course feedback said the material had to remain in the course. So I’ll now be delivering a similar lecture once a semester.

Well, twice this semester, because high student numbers mean that I have to give two performances, at 0900 and 1300 on Monday 26 August.

Telstra screenshot: click to embiggenWith all their constant worrying about whether people would recommend them or not, like this example from Telstra, I’m starting to think that most big corporations are paranoid psychotics — and not in a good way.

The other day I conducted a perfectly routine transaction at a Telstra Shop. I cancelled a mobile broadband service and replaced it with a different one. As with many businesses, my visit was followed up with a brief survey, “Please tell us how you feel.”

There were four questions, but none of them actually asked me how I felt:

Is your new Telstra service working? If you answer ‘no’ to this question, we will present you with options to get in contact with Telstra to resolve your issue on the next page.

OK, that’s fair enough. You need to know that the customer has a working broadband service. But the other three?

When you consider all aspects of buying and connecting your service — how likely are you to recommend Telstra to a friend or colleague?

Thinking about your in-store experience, how likely would you be to recommend the store to a friend or colleague?

What are the most important reasons why you gave us this score?

Guys, this goes way beyond “Does my bum look fat in this?” This is self-obsession. “What are you going to tell people about us? Why, what did I do?”

These constant questions about likelihood of being recommended are a sign of paranoia. I don’t care how you feel, I gave you money. Recommending you or not just isn’t a KPI for me.

How about you ask questions that reflect the customer’s needs and aspirations? Or even just concrete questions about how long I had to wait, whether staff were polite, or whether the service meets my needs?

ABC logoOn Wednesday night I ended up having a long, rambling chat on the radio about Twitter’s new advertising deal and the arrest of an alleged hacker who apparently claimed to be the leader of LulzSec.

This conversation was broadcast on ABC Local Radio around NSW, the presenter was the redoubtable Dom Knight. We begin with Twitter, and then move on to the alleged-hacker’s arrest at around 12 minutes 50 seconds in.

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The audio is of course ©2013 Australian Broadcasting Corporation, archived here because it isn’t being archived anywhere else.

Title slide: Algorithms and the Filter BubbleHere’s the guest lecture I delivered at the University of Technology Sydney on 25 March 2012, “Algorithms and the Filter Bubble”. Full audio and slides for now, a transcript to follow in the next few days.

You might want to read the background material first. You’ll definitely want to look at the slides while listening to the audio.

The recording picks up immediately after I was introduced by lecturer, Dr Belinda Middleweek, using the opening paragraphs of my about page.

The audience was primarily first and second year students at the beginning of their media studies degrees. It seems that almost all of this material was brand new to them — though I did notice one geeky-looking lad nodding enthusiastically at mention of some of the more pervasive tracking techniques.

Play

[When the transcript becomes available, this is where it will appear.]

This work is made available under a Creative Commons BY-NC-SA license. This presentation may be re-used for non-commercial purposes within the terms of the Creative Commons license. The non-commercial and share-alike conditions are required to adhere to the licensing of the imagery used. Please contact me if you require an alternative version. As a minimum, attribution should read: “Source: Stilgherrian.” Online versions must link the word Stilgherrian to the website at stilgherrian.com.

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