A magazine where the digital world meets the real world.
On the web
- Home
- Browse by date
- Browse by topic
- Enter the maze
- Follow our blog
- Follow us on Twitter
- Resources for teachers
- Subscribe
In print
What is cs4fn?
- About us
- Contact us
- Partners
- Privacy and cookies
- Copyright and contributions
- Links to other fun sites
- Complete our questionnaire, give us feedback
Search:
Crystal ball coupons
by Jane Waite, Queen Mary University of London
Big companies know far more about you than you think. You have very little privacy from their all-seeing algorithms. They may even have worked out some very, very personal things about you, that even your parents don't know...
An outraged father in Minneapolis stormed into a supermarket chain complaining that his school-aged daughter was being sent coupons for baby clothes. The shop manager apologised ... but later they found there was no mistake in the tiny tot offers. The teenager was expecting a baby but had not told her father. Her situation was revealed not by a crystal ball but by an algorithm. The shop was using Big Data processing algorithms that noticed patterns in her shopping that they had linked to "pregnant". They had even worked out her likely delivery date. Her buying habits had triggered targeted marketing.
When we use a loyalty card or an online account our sales activity is recorded. This data is added to a big database, with our details, the time, date, location and products bought (or browsed). It is then analysed. Patterns in behaviour can be tracked, our habits, likes, dislikes and even changes in our personal situation deduced, based on those patterns. Sometimes this seems quite useful, other times a bit annoying, it can surprise us, and it can be wrong.
This kind of computing is not just used to sell products, it is also used to detect fraud and to predict where the next outbreak of flu will happen. Our banking behaviour is tracked to flag suspicious transactions and help stop theft and money laundering. When we search for 'high temperature' our activity might be added to the data used to predict flu trends. However, the models are not always right as there can be a lot of 'noise' in the data. Maybe we bought baby clothes as a present for our aunt, and were googling temperatures because we wanted to go somewhere hot for our holiday.
Whether the predictions are spot on or not is perhaps not the most important thing. Maybe we should be considering whether we want our data saved, mined and used in these ways. A predictive pregnancy algorithm seems like an invasion of privacy, even like spying, especially if we don't know about it. Predictive analytics is big; big data is really big and big business wants our data to make big profits. Think before you click!