Personalization on the web is becoming increasingly more sophisticated. What used to be as simple as a user checking a few boxes to self-determine their interests, is now being translated into detailed algorithms that parse through a user’s clicks, preferences, personal information listed on their Facebook page, and even items left in shopping carts on online shopping websites such as Amazon or Target.com to determine what a user might be interested in.
While these features may prove useful while shopping or searching for recipes online, the filtering and personalization of news and political information carries its own implications on democracy and the political sphere. Though some scholars argue that personalization does too much thinking for the user and risks damaging the democratic system by only showing readers what they want to see, others argue that there is simply too much information, leaving it up to editors and ultimately programmers to improve the online news experience by helping readers easily and efficiently find exactly what they’re looking for even if they don’t directly have a hand in the selection process. I argue here that news personalization is not only an effective method of disseminating important information, but also an unavoidable advancement that has been around since the early days of the Internet and isn’t going away anytime soon.
There is a severe inequity between the amount of attention a reader is willing to give to the news, and the amount of news is actually out there to read. The idea of everyone seeing the same news has become a nostalgic relic of the past. Between the tens of thousands of stories produced daily by media giants around the world, plus the millions of individuals contributing to the cacophony by adding their own stories, videos, and pictures to the web, how does an individual reader decide what is important to them as a citizen and what is just noise? Editors as well as programmers are now left to answer these questions by determining who reads what when.
Jonathan Stray outlines three factors that ultimately determine whether or not a reader should read a story. The first of these factors being if the reader specifically goes looking for it, second if it affects you or any of your communities and third, if there is something you might be able to do about it. In essence, a reader should be exposed to what he or she cares about, if it directly will affect you, and if you can even do anything about it (Stray, 2012). It would be impossible for a reader to sift through every bit of news that could potentially be relevant to them or could contribute to their ability to act as a completely informed citizen, so readers are depending more and more on algorithms and editors of news publications to help them get the information that matters to them quickly and easily.
On the other hand, Eli Pariser, the co-founder and CEO of Upworthy and the former executive director of MoveOn.org argues the damaging effects personalized news has on political communication and journalism as a democratic institution. A critical element to democracy, Pariser notes, is citizen engagement with multiple viewpoints. Pariser believes that programmers who create algorithms that filter the information a user sees to just what the algorithm thinks they want to see are committing a severe disservice to the democratic system by ignoring the journalistic ethical value of facilitating the exposure of citizens to the news- whether they want to read it or not (Pariser, 2011).
What Pariser neglects to acknowledge in his argument, however, is that many of today’s programmers creating these algorithms are, in fact, journalists themselves who are just as passionate about the role of journalism in the democratic process as any other reporter in the field. Skills in web development are becoming increasingly marketable as news organizations change their models to adapt an audience that is becoming increasingly difficult to capture.
Personalized news and intimidating algorithms have hid behind the HTML and CSS of web pages since the very early days of the Internet, and the skepticism surrounding it is not new. An article written in 1997 by Christopher Harper details the first instances of personalized media when only nine percent of the American population had Internet access. The article cites many of the same concerns scholars have today, primarily that of the implications on democracy as each member of the electorate is exposed to different things. Even in 1997, there was uncertainty in what direction the nature of personalized news is going (Harper, 1997).
If nothing else, this should comfort critics of personalized news outlets. Twenty years ago caller ID was seen as an intrusive and intimidating form of technology- today, it has become absolutely essential. In effect, we need to become more comfortable in the world of online news. We, as a readership and as Americans, need to understand how these algorithms and online news sources work in order to take full advantage of their possibilities. The advancement of filtered media is not something to be afraid of, but instead something to embrace because like it or not, this is the direction that not just the news media are heading in, but the Internet as a whole.
Pariser, Eli. “When the Internet thinks it knows you.” International Herald Tribune 23 May 2011.Infotrac Newsstand. Web. 18 Feb. 2013.
Badke, William. “Personalization and Information Literacy.” Online Jan.-Feb. 2012: 47+. General OneFile. Web. 18 Feb. 2013.
Harper, Christopher. “The Daily Me.” April 1997. American Journalism Review. Web. 18 Feb. 2013
Stray, Jonathan. “Who should see what when? Three principles for personalized news.” 25 July 2012. Nieman Journalism Lab. Web. 8 Feb, 2013.