Are Algorithms Objective?
Social media is a platform that gives individuals or organizations the space to create conversation and send information of any sort. Interactions, like commenting, liking, and sharing are what makes it all so intriguing. Journalists have participated in this data-driven platform and merging the user generated content into live coverage and reporting news. People worry about the credibility of the media sources and their partiality (Lotan as cited in McBride & Rosenstiel, 2013). This is all so different from the way traditional media works; they are required to stick to facts and not express any opinion that would lead to bias, meaning they should be neutral and accurate. It is important for the news to be impartial, fair, verified, independent, and neutral (Ward, 2009). This signifies the key difference between social media and the traditional because in social media, news are randomly spread to all users while on Tv or newspapers, there should be a criteria for the kind of news that will be published. Moreover, objectivity is questioned here. Objectivity is all about not taking sides in certain news stories and giving the people the space to decide where they want to stand. It is important for news to be objective and truthful to provide the audience with the necessary information instead of leaving things out and create prejudice among the people.
No matter how important objectivity is, it is important to note how hard it is to achieve it. To ask for a journalist to be nothing but a messenger to people is hard because after all, having personal opinions is only natural. In addition to that, there is no way the legacy media focuses on providing peace because of their power which allows them to dominate different aspects of society such as politics, economics, and national culture. Traditional media advocates political interests and corporate economics (Bouzov, 2015). This shows that it isn’t just the social media platforms that challenges objectivity. Moreover, with the rise of bloggers, citizen journalists, instant news, and any other kind of news that focuses on the social connectivity of the new media, the term objectivity seems a bit far fetched and needs to be reconsidered (Ward, 2009). How can journalists continue their practice of being neutral with the development of the new media that is all about creating conversation internationally? Journalists also face the pressure of algorithms that data companies use to personalize the news that is shown to the users based on their interests because of the possibility that their news might not be worthy to be selected. This brings us to objectivity in social media. Algorithms function by turning random information into useful sources of news. The way things work now is by knowing as much as possible about the users and the sites they use and information they gather to provide them with similar topics. The algorithm works whenever the user does any activity on social media in order to update its information system (Gillespie, 2012). This gives social media an advantage because it creates a window for the users to gain knowledge of all the news that interests them instead of being limited to the news that are broadcasted on legacy media. It also gives the freedom for people to share what they think of certain events and act accordingly by expressing their opinions and connecting with people that are on the same side.
Whether algorithms are in fact beneficial to the people is still quite debatable. For once, data companies now provide lists of the trendiest news for people to look at and what the biggest headlines are. This makes people wonder about the process behind choosing which topics get to be on top of the list while others are ignored. It also shows the limitations of what the people get to see instead of letting them choose what they want. It also sheds light on the important role journalists play because they try to provide the basic information that people need to know about and allow the readers to choose whether to ignore it or not instead of just providing them with events that they think is relevant. Moreover, algorithms can help create polarization and partisanship. One example can be the “Occupy Wall Street” movement that struggled to become a trendy topic on twitter. The problem that caused that is the algorithm because people weren’t being as engaged to it with respect to other trending hashtags. This questions the way Twitter plays the role of an editor in deciding what goes on top and what doesn’t (Lotan as cited in McBride & Rosenstiel, 2013). Another example is, Facebook has played a huge role in the political conversation in America. It has created accounts and pages that are political, engineered to grab the users’ attention through their feeds (Herrman, 2016). This implies it has used the information of the users to find ways to achieve the goal of manipulating them into choosing whatever side they want them to be with. In other words, algorithms harm the people by choosing what they see based on what they assume is important instead of allowing the spread of news from different point of views. Also, the fact that algorithms alters users’ news feed based on what characteristics they believe the person has, limits the interests that the person may have that they have no clue about.
All in all, social media has provided people with the space to create relatable content that have helped them know about different perspectives. On the other hand, algorithms have become more harmful than beneficial because of its loss of evaluation on what is important rather than what is trendy. It has also played a role in being bias due to using people’s data to influence them the way they want to. What should be done to reduce such harm is provide certain regulations that can keep people safe from being targeted as subjects to be influenced the way the big companies and organizations want. The audience should know of the ways advertising companies use their data and realize the power that the data companies hold against them (Gillespie, 2012); the only way to change a system is by changing the way the power is spread.
Bouzov, V. I. (2015). Philosophy of Media Manipulation in the Globalization Era: Options for Countering. Diogenes. An International Thematic Journal. pp.10–16.
Gillespie, T. (2012). The relevance of algorithms. Culture digitally. Retrieved from http://culturedigitally.org/2012/11/the-relevance-of-algorithms/
Herrman, J. (2016, August 24). Inside Facebook’s (Totally Insane, Unintentionally Gigantic,Hyperpartisan) PoliticalMedia Machine. The New York Times Magazine. Retrieved from https://www.nytimes.com/2016/08/28/magazine/inside-facebooks-totally-insane-unintentionally-gigantic-hyperpartisan-political-media-machine.html
Lotan, G. (2013) Networked Audiences, in McBride, K. & Rosenstiel, T. The new Ethics of Journalism, Sage, London, p. 105–119.
Ward (2009) ‘Truth and Objectivity’ in in Wilkins & Christians (eds.) Handbook of Mass Media Ethics, Routledge, London; New York, pp. 71–83.
