The growth of the internet as an information and communications tool has always been tied intimately with the promise of connecting people beyond geographical and ideological boundaries, of expanding our knowledge through unprecedented access to multiple viewpoints.
This ideal is still embraced by some, notably in discussions of the “Twitter Revolutions”, but in a practical sense it’s as relevant as a physical Encyclopedia.
For most of us day-to-day internet use is fast moving away from providing individuals real choice, and ironically this is due to the “personalisation” of the web experience.
As most Facebook, Twitter or Tumblr users are aware, these and other social networking websites utilise complex algorithms based on user behaviour - links they click, pages they view, even research depicting eye-tracking patterns on webpages – to provide highly targeted ads, content and even friend updates which may appeal to you most.
Self-righteous non-Facebookers aren’t excluded either - Google’s search algorithm also provides similarly targeted ads and search results based on individual user behaviour.
There are, in fact, 57 elements Google uses to cater search results for individuals, so a standard Google search result simply does not exist anymore.
This point was made in a recent TED talk by former MoveOn.org director Eli Pariser, who raised the thought-provoking argument that this predictive code that personalises the web experience actually encases us in bubbles of information.
As a result, sites like Google are showing us “what it thinks we need to see, but not what we should see”.
To illustrate this Pariser showed search results from friends in different locations, all looking for information on protests in Egypt.
The screenshots showed that while one friends’ links were all directly related to the protests, other friends’ results linked to vacation and travel information.
Facebook users experience a similar effect, whereby friends whose links and posted items are clicked on frequently become more prominent on users news feeds.
Those who aren’t referenced as regularly slowly drop off the radar as the algorithm collects more behavioural data with each logon.
As an example, if a user began with friends from a wide variety of political leanings, they may click more on posted items relating to similar political preferences (because after all we like people who like people like us), and so those friends whose views may differ slowly drop down the “relevance” scale and news feed.
The overall effect is not one of expanding the boundaries to different viewpoints, but further encasing users in information bubbles deemed most relevant by “personalisation” algorithms.
To be fair, a personalised web experience does have its plus points, but most of the advantages exist for savvy advertisers, and of course the websites themselves which profit hugely from being cutting-edge marketing platforms.
So what are the possible solutions for users who want results directed (to the highest degree possible) by their own will, rather than the predictive “Minority Report”-style code of Google, Facebook, and so on?
It may be unrealistic for these companies to disclose how personalisation filters are created, but perhaps they can provide a “personalisation toolbar” where users can choose to what level they want Google’s/Facebook’s personalisation filter to apply.
Pariser’s talk also raises more philosophical points about the impact of the information age.
With the experience of “personalisation” seemingly moving towards a self-affirming loop of opinion and consumption, are we really becoming any more intelligible with the availability of all this information? Are we becoming any more tolerant or inclusive with the easy access to different viewpoints?
Or perhaps personalisation is to the Internet what the remote control was to the television – now we don’t have to think hard or do any work, just click around and we’ll always be led to comfortable happy places, like highly coordinated wedding dances or The Star Wars Kid.
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