Global Inequality in Tech

After my last blogpost, I started reading up more on technology and global inequality. How much of a divide is there in the world? Is it such a serious social issue?

It turns out that the answers are ‘A very big one’ and ‘yes.’

Many of the issues stem from lack of internet access for a large proportion of the world’s population, which denies them access to education and training needed to socially advance or improve their communities. This is an issue that is being worked on through many angles (including the wifi drones that I wrote about last year) although there are plenty of other problems than just the hardware – including fair access under corrupt administration, and cultural issues or actually using it.

But in high and middle-income countries, lack of access is less of a problem, but technology is actually making equality worse over time. This article from the World Economic Forum explains it best, basically as jobs have become more automated, the world starts to become divided into those who still have marketable skills and those who don’t. Those who do can afford more personal technology, more education to develop those skills (and their children’s skills) and so the divide grows. Even with programmes to bridge that divide and ensure that everyone has access to useful job skills, countries are reaching a point where productivity can be high but there simply aren’t enough jobs for everyone to have one. I remember being amazed at this video of robots moving stock around an Amazon warehouse (exciting futuristic stuff!) and then quickly realising that this is a job that used to be done by people… and it isn’t just factory jobs either. Recently a Japanese Insurance firm began using a computer system that calculates customer payouts for them, making 34 employees redundant.

The scary thing is that the WEF article above (which it should be noted was written a year ago) both calls for a quick response to the issue but is unable to provide clear answers, only ‘innovative thinking’ to solve the problem. Clearly, we didn’t start solving it in 2016, and I have to wonder how many more robots will enter the workforce before we do.

Blaugust 30: The Internet is Really, Really Big

Sometime around Friday night, I was reading an article on Mashable about Weather Data and problems with social media, which I started and then abandoned a blog post on due to not feeling like I had a good angle (it’s a good article though and I recommend it). However, before I deleted the draft, I had been researching some data on how big the Internet is, and I found a fair amount of amazing information which I wanted to share in a post.

I assumed that the Internet is expanding at an exponential range, like of like the Universe really, and I was looking for articles to support this.

Image from gizmodo.com

But according to World Wide Web Size, a site which tracks the number of indexed pages, the number of indexed pages doesn’t necessarily go up consistently and even goes down at times. This is because individual pages and whole sites are constantly going up and down. This gives the impression that the Internet isn’t expanding all that quickly despite the amount of content on it, but then you get this quote from Websitemagazine.com.

As of 2014 Google has indexed 200 Terabytes (TB) of data. To put that into perspective 1 TB is equivalent to 1024 Gigabytes (GB). However, Google’s 200 TB is just an estimated 0.004 percent of the total Internet.

That linked article above also has a genuinely fascinating infographic which tries to put in perspective how we use the internet as well as it’s sheer size in data.

This article also notes that a lot of the unindexed web is the Dark Web. So if you look at the galaxy image above, and imagine that each of those stars is a website, all of the space in between them is the Dark Web (sorry, that’s a rough analogy! It’s kind of the easiest way for me to understand it though!)

Blaugust 28 – Using Padlet

During my Future Learn Smart Cities course, we used a system called Padlet to upload image and make notes on activities. I’d only used it in the browser version (there is a app, which I’ve been using since.)

It did feel slightly like a virtual classroom environment, as people chose a space on the pad, and wrote in a text box and/or added links and images which the rest of the users could see, as if they were all displayed on a classroom table (without the potential peer pressure and judgement of being around actual other people) but I didn’t expect to need to use it outside of Smart Cities or other similar courses.

However after glancing through some of the emails I’ve had from Padlet (see, email advertising – it does work!) I’ve not only discovered plenty of free and potentially useful content, I’ve also realised how it could be useful to me as a note-taking and sort-of rough blogging platform in the future.

I’ve been reading some live blogs that have been end via Padlet from conferences, where one person is writing up the content and others have been able to pop in and make comments or suggestions. As I (hopefully) move back into more formalised learning, I will be able to put up rough lecture notes – the stuff that I probably wouldn’t put up here without serious revision.

Blaugust 24: Crowdsourced Citizen Science with Crickets

During my Smart Cities Future Learn Course, the difficulties of getting getting people involved in data collection involved came up several times, and I even discussed gamification for projects in this post earlier in August.

So I wanted to share a university project I’ve found where the researchers gamified their data collection in order to deal with a massive amount of data – about crickets!

The Unviersity of Exeter are currently performing a vast, long-term experiment on a population of Field Crickets in Northern Spain, in order to study their evolutionary biology. This involves tagging crickets with numbers and setting up a network of cameras to cover every burrow they can find to collect data on the cricket’s daily habits. Of course, this has produced hundreds of hours of video, much of which is useless if the crickets aren’t around, and a small group of researchers don’t have time to watch all of it. So how to find the important parts?

This is where Cricket Tales comes in.

This website provides you with a virtual meadow marked with burrow locations and ‘houses’ which players can build by watching and tagging a certain number of videos, sort of like FourSquare in which you can make yourself the ‘owner’ of a certain spot. I haven’t played for very long, but it also seems like the longer you play at a certain burrow, the more elaborate your ‘house’ becomes.

After a short tutorial, you can then choose any burrow to watch short videos from. As you can see in the screenshot below, you can choose a particular button on the side to note an action at a certain point in the video. Many of the videos have little to no action in, so this is an effective, gamified way for the researchers to identify behaviours more quickly.

Pressing buttons when you see an action allows you to tag the video. This shows up in a newsfeed that all players can see

Blaugust 21: Big Data Week Two – Programming and Conclusion

The second section of Big Data Week Two focused again on the more practical aspects of working with software. I’ve increasingly realised that I’m following along with this course rather than trying tasks that are probably aimed at someone with a little more prior experience, but that’s okay, I’m still learning some things!
I read through the it all anyway, I feel like some of it will stick. The data that the tasks use for analysis was interesting to me in light of having looked at open data in Smart Cities, because it provided by the Australian Bureau of Meteorology, so kind of what I discussed in this post.

After tasks on Hadoop and MapReduce, which we learned about last week, the course went on to talk about Apache Pig, which improves the output of Hadoop, using HDFS and MapReduce. From the course material, it has:

  • Faster development, increases productivity 10x and is very flexible.
  • Expresses data transformation tasks in just a few lines of code.
  •  Doesn’t reinvent the wheel: 10 lines of Pig Latin = ~200 lines of Java!

(The previous couple of tasks provided linees of Java to execute tasks which is why it’s mentioned.)

Other important facts: Apache Pig runs on a language called Pig Latin, which is very unlike other programming languages including the bits that I am familiar with from the course:

Pig Latin script describes a Directed Acyclic Graph (DAG) where the edges are data flows and the nodes are operators that process the data. Pig Latin has no if statements or forloops, and focuses purely on data flow.

Instead it relies on commands such as ‘store’ or ‘dump’.

Conclusion

Overall, this might have been a less useful course for me simply as I was less interested in the practical coding aspects and more in the theoretical application, which is partly why I’m putting the conclusion here instead of in a separate post. However, even the coding info gave me a basic overview of how people work with large-scale data sets, and the case studies did link in well to my other courses.

I’m not exactly sure where to go next with online learning and finishing off Blaugust. I do have some ideas in exploring online learning outside of Future Learn for a little while, which I’ll be talking about tomorrow.

Blaugust 20: Big Data Week Two – Telescopes and Data Rage

Week Two of Future Learn’s Big Data course started with a pretty cool example that I already knew something about – the Square Kilometre Array Radio Telescope. With telescopes in more than twenty countries being used to study the signals from the Big Bang, entirely new methods of data collection and analysis have had to be developed for this project.

Square Kilometre Array Artist Impression – From https://www.skatelescope.org

The next section discussed the issues of managing big data. I actually followed this part much better than the practical software work last week, as it was closer to some of the discussion on the Smart Cities course about project management. It discussed how to store the data, secure it and back up it for maximum efficiency.

I also followed the next section quite easily, it was about the applications of big data in marketing. It all made total sense to me, but apparently a lot of people don’t consider how marketing and data actually work. Any marketing service needs to collect a lot of data on its clients in order to offer the best deals and services, and this has always seemed obvious to me, even before I started on my current career. But there was serious outrage from some people in the comments, on discovering that their buying habits and behaviours are stored away for the clearly immoral practice of trying to sell them more stuff!

Maybe this section of the course needed to go further into the details of data protection laws (my previous courses provoked similarly ridiculous comments when discussing data, and I do have a draft of a separate post on this topic).

Tomorrow I’ll be covering some more of the course content from week two.

Blaugust 17: Google Small Business Video – Customer Loyalty

Over the past few weeks, I’ve watched a number of videos from the Google Small Business YouTube channel to improve my commercial awareness and made short posts (here and here) with my notes, thoughts and comments – this latest one is about how to retain customers.

The first point made is that learning who your customers are is key, which was also stressed in the previous Google for Small Business videos that I’ve watched.

Frequency is a very important metric to focus on in looking at customer loyalty, and existing customers can often be more valuable than new ones, because the more positive they are about your brand, the more custom you will attract (both through word-of-mouth and through positive online reviews.)

When starting up, most businesses focus on customer acquisition and slowly switch to retention later on – the longer a small business has been going, the more important retention becomes for it. So as a business owner starting out, it’s important to get ahead of that by focusing on both acquisition and retention from the start. This involves making the customer experience the best it can possibly be.

The point about the cost of customer acquisition versus retention was really interesting. I don’t necessarily think that you need a specific customer loyalty programme, and I also think that even if you do, not all of your regular customers will want to use it or fit into it well, but it is good to keep in contact and do offers (especially seasonally as discussing in one of the last Google business videos I talked about) so that your customers feel like they are appreciated for frequent business.