Modern life is a data-driven affair. Every corner of our society is awash with machines leveraging personal information to bring digital systems closer to you.
Personalisation, or targeting, is the act of providing specific information to an individual based on their personal data.
It’s how Amazon might correctly guess that you want Mr. Bean underpants even though you only ever bought a DVD player and a tea towel. Or why an insurance company might charge you more because they’ve seen your Facebook profile.
Personalisation can happen online and offline but data cultivated on the internet is the biggest driver of this phenomenon.
In most cases, the result is a more helpful, more usable online experience. Less trawling through web sites to get what you need, less filling out forms and faffing to get things done.
Do they know you too well?
Personalisation can be extremely powerful, is usually done furtively, and has the potential for great harm. It was one of the techniques that Cambridge Analytica relied on to secretly sow hatred in electoral campaigns worldwide, by playing on people’s personal fears.
Recent research shows that the public are concerned. Polling suggests “that fewer than a third of Britons ‘trust platforms to target them in a responsible way’, and that almost two-thirds, 61%, ‘favoured greater regulatory oversight of online targeting.”
As with any technology, there will be good and bad implementations.
Here are a few case studies of personalisation in the wild to help us understand this technology and how it might affect us in unseen ways.
Online ads discriminate by design
Web advertisers, like Google, operate by promising to target adverts very accurately to people based on who they are and what they like. These automated decisions often seem to encode social biases although we almost never know exactly how they really work. Given this opacity, researchers are usually left to probe such systems with experiments to deduce how they actually function under the hood.
In a potent example from 2015 researchers reported that “female job seekers are much less likely to be shown adverts on Google for highly paid jobs than men... We found that males were shown ads encouraging the seeking of coaching services for high paying jobs more than females.”
Facebook feeds you news as “you like it”
According to Facebook, the “News Feed ranking creates a personalized and diverse stream of posts from the people, news sources, businesses and communities you’ve connected with on Facebook.”
“To see what influences the order of posts you're seeing in your News Feed: Go to the post. Click in the top right and select Why am I seeing this post?”
However, even if you try to find out, most of us will never really know why Facebook shows us what we see, and what it hides from us too. It uses so much data, and in so many ways, that a full explanation would require a short course to understand.
In cases like the Cambridge Analytica debacle, we are still living with the effects of that personalisation today. Facebook allowed political campaigners to show people problematic propaganda, segmenting users based on data gleaned via Facebook. The ads were targeted to prey on people’s fears and urge them to vote a certain way. Facebook profited and democracy suffered.
Cupid captures your soul
Tinder is one of the leading online matchmakers gathering data in the service of love. What they know about you, they use to pick potential lovers, as explained in this Guardian investigation.
“So why does Tinder need all that information on you? ‘To personalise the experience for each of our users around the world,’ according to a Tinder spokesperson. ‘Our matching tools are dynamic and consider various factors when displaying potential matches in order to personalise the experience for each of our users.’”
“Unfortunately when asked how those matches are personalised using my information, and which kinds of profiles I will be shown as a result, Tinder was less than forthcoming.”
Our matching tools are a core part of our technology and intellectual property, and we are ultimately unable to share information about these proprietary tools.
Harvesting farm data
Here's an intriguing case-study in why you should be wary of how your data could be used against you. Farmers in the USA became suspicious that offers to rent their land from a company called Tillable were being personalised using key data about their farms.
In fact, they were left wondering if their farm's own, private data might have led to specific market outcomes.
“Parker Smith, like a lot of farmers, uses equipment that automatically collects all kinds of data about his operations — like how much fertilizer he applies and how much grain he harvests from each small piece of each field. He pays a company called the Climate Corporation to manage that data and help him understand it.
“Last fall, though, the Climate Corporation and Tillable announced a partnership. And after Smith learned about Tillable's letters to landowners, Smith had to wonder: Did Tillable target specific landlords because it got access to data about how productive and profitable their land is?”
The allegations were never substantiated but the partnership ended after the furore anyway.
In this case, data from one area of life seemed to be at work in a completely different place. A letter requesting to rent your land would not immediately seem related to a data analytics service you separately use to manage the land.
Like the farmers, all of us need to be alert to how our data might be used, often without our knowledge, to gain advantages against us.
The biggest shop on earth
In notes from a 2013 interview with the firm it explained that they “help sellers identify areas where they can improve the sharpness of their pricing.” When asked if they, for example, use Facebook data
We don’t publicly discuss what kind of data we use for the recommendation but social data that’s publicly available like you are describing is certainly one of the inputs.
Unseen personalisation is everywhere
There are millions of examples of personalisation on the web and that number is growing. Society will continue to be segmented with data, treated accordingly, and in multiple ways we don’t yet know about – we must stay aware.
Citizens need to understand the power of this technology and ensure it serves rather than controls us.
If you know of any more interesting examples, please share them in the comments or to [email protected] And sign up for our newsletter to keep up with our campaign for data transparency.