Sunday’s Sermon: Suzuki

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My parents were born in Vancouver — Dad in 1909, Mom in 1911 — and married during the Great Depression. It was a difficult time that shaped their values and outlook, which they drummed into my sisters and me.

“Save some for tomorrow,” they often scolded. “Share; don’t be greedy.” “Help others when they need it because one day you might need to ask for their help.” “Live within your means.” Their most important was, “You must work hard for the necessities in life, but don’t run after money as if having fancy clothes or big cars make you a better or more important person.” I think of my parents often during the frenzy of pre- and post-Christmas shopping.

Read the “sermon” here.

Big Data and the Surveillance of Everything: Issues

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This is the final part of a three part series based on a talk given for the Institute of Practical Philosophy at Vancouver Island University in April 2015. 

 The series includes:

Part 1 – Introduction to big data
Part 2 – Examples of using big data
Part 3 – Unpacking (some of) the issues …

The views expressed in this series are my own. 

Unpacking (some of) the issues …

In the second part of this series, we talked about examples of how big data can be used, from credit card fraud to government surveillance. In this third and final part, let’s change gears again and look at some of the issues surrounding big data and the surveillance of everything.

Living with big data

“A surveillance society is not only inevitable, it’s worse. It’s irresistible”–Jeff Jonas

Originally made in 2011, this quote is now stale. In 2015, we are talking about a future that has already happened, and we are perhaps only now realizing that what has happened is much more invasive than we could have anticipated. The examples given here would not be possible at this scale without big data technology and they aren’t futuristic examples; they exist here and now.

Technology is changing the world, perhaps much faster than you and I can adapt. Change in this case is not about new gadgets but about a fundamental change to many facets of our lives. And yet, many of our privacy laws were written before the big data revolution. Just because you can get the data legally, does not mean it is ethical to do so if outmoded and outdated privacy laws are essentially lagging behind. The example of Target’s targeted marketing indicates even the company itself realized at some point that what it was doing was bordering on creepy. Legal yes, but also borderline Orwellian.

So why is a surveillance society irresistible? Simple:

Companies know if they can extract more insight from data faster than their competitors, they’re going to win–Bill McColl

These companies might counter any claims about becoming Big Brother by saying that they are really just creating a better internet experience for you, the consumer who prefers relevant ads related to your interests. Similarly, for governments, there is a competitive national security advantage if they gain better insights before other nations or hostile groups.

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Big Data and the Surveillance of Everything: Examples

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This is the second part of a three part series based on a talk given for the Institute of Practical Philosophy at Vancouver Island University in April 2015.   The series includes:

Part 1 – Introduction to big data
Part 2 – Examples of using big data
Part 3 – Unpacking (some of) the issues …

The views expressed in this series are my own. 

Examples of using big data

In the first part of this series, you were introduced to some of the technical background that makes the field of big data possible. Consider now examples that include an application of big data analytics in one form or another. The examples covered here include:

  • Credit card fraud
  • Prenatal monitoring
  • Targeted marketing
  • Government surveillance

There are many other examples as well, some of which you have already seem, but these examples here serve to show you the range and breadth of big data applications, which will become important when we start unpacking some of the issues surrounding big data in the final part of the series.

Credit card fraud

Credit card fraud is a good example of a perishable insight: Credit card companies buy systems to detect that what you are doing is out of the ordinary before you even finish and they will stop you if you think there is fraud involved. These companies typically know your habits and behavioural patterns better than even your close family might.

It is somewhat disingenuous to say “they will stop you,” given that ‘you’ in this case is someone else engaging in credit card fraud with your information. It sounds more sinister than it actually is. But think about the speed at which this decision making process must happen: Most credit card transactions complete in 10 seconds or less, starting from a slow merchant terminal that first has to make a connection with a host system. Your in-progress transaction has to make it to the analytics system, the system needs to determine whether or not your transaction is out of the ordinary and then has to make a decision on the fly about whether or not to let the transaction go through. If the transaction is deemed fraudulent, a stop instruction has to be issued before the transaction completes. All you get is this 10 second window; once the transaction is completed, it is too late to stop any potential fraudster. Also, you cannot flag legitimate transactions as fraudulent or your customers will hate you and will eventually move to your nearest competitor if you aggravate them enough. These are very advanced, multi-million dollar systems to combat fraud that are fine-tuned so as not to interfere with your daily life by knowing exactly what it is that you usually do.

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Big Data and the Surveillance of Everything: Introduction

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We are re-publishing this series of articles by Dr. Richers by popular demand!

This is the first part of a three part series based on a talk given for the Institute of Practical Philosophy at Vancouver Island University in April 2015.  The series includes:

Part 1 – Introduction to big data
Part 2 – Examples of using big data
Part 3 – Unpacking (some of) the issues …

The views expressed in this series are my own. 

Why talk about big data?

The topic of big data captures many of the issues we are faced with in a time of rapid technological change. In the examples shown here, some might immediately strike you as good applications of technology–they help human beings lead better lives–but others look like they infringe on basic rights without any recourse. Details about your life are now available to an extent that might make anyone concerned with individual privacy queasy. It is this range of issues surrounding big data, the presence of both good and bad issues, which makes the topic of big data such an interesting starting point.

Big data and the habitual surveillance of our lives were interesting topics in themselves before all the commotion surrounding Bill C-51 started in Canada. Proposed mass surveillance legislation like Bill C-51 would not be possible without the technology underlying big data. Around the globe, legislation like Bill C-51 fits into the framework of a larger trend that changes or even undermines some of the basic notions of what it means to have individual privacy. Bill C-51 is very likely to become law in Canada, but the discussion of this trend is not dictated by the passage of any one set of laws. It is a conversation about individual privacy which we have only just begun. 

There is also a practical aspect to all of this: Big data is not some magical black box but a very specific technology. This post covers just enough of the technology to give you an idea of how it might work and why big data lets you do things that older technology even just a few short years ago did not. Overall, the message is this: Something has fundamentally changed in the last ten years and we are very unlikely to ever go back. So the question becomes: How do we cope with this change?

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