Consider the following earnings report, which the Associated Press published shortly after Apple released its quarterly figures in January 2015.
Apple tops Street 1Q forecasts
Apple posts 1Q profit, results beat Wall Street forecasts
AP. January 27, 2015 4:39 PM
CUPERTINO, Calif. (AP) _ Apple Inc. (AAPL) on Tuesday reported fiscal first-quarter net income of $18.02 billion. The Cupertino, California-based company said it had profit of $3.06 per share. The results surpassed Wall Street expectations. The average estimate of analysts surveyed by Zacks Investment Research was for earnings of $2.60 per share. The maker of iPhones, iPads and other products posted revenue of $74.6 billion in the period, also exceeding Street forecasts. Analysts expected $67.38 billion, according to Zacks. For the current quarter ending in March, Apple said it expects revenue in the range of $52 billion to $55 billion. Analysts surveyed by Zacks had expected revenue of $53.65 billion. Apple shares have declined 1 percent since the beginning of the year, while the Standard & Poor’s 500 index has declined slightly more than 1 percent. In the final minutes of trading on Tuesday, shares hit $109.14, an increase of 39 percent in the last 12 months.
At first glance, the article may appear to be a routine, financial news report. Except for the footnote, which states that the story was generated by software or, more precisely, an algorithm. Granted, the piece may sound a bit technical and boring, but it provides all the facts a journalist is likely to cover and in which an investor is likely to be interested.
This technological innovation, known as automated journalism, is a relatively new phenomenon in the area of computational journalism. Automated journalism refers to the process of using software or algorithms to automatically generate news stories without human intervention—after the initial programming of the algorithm, of course. Thus, once the algorithm is developed, it allows for automating each step of the news production process, from the collection and analysis of data, to the actual creation and publication of news. Automated journalism—also referred to as algorithmic1 or, somewhat misleadingly, robot journalism2—works for fact-based stories for which clean, structured, and reliable data are available. In such situations, algorithms can create content on a large scale, personalizing it to the needs of an individual reader, quicker, cheaper, and potentially with fewer errors than any human journalist.
While computation has long assisted journalists in different phases of the news production process—as in the collection, organization, and analysis of data, as well as the communication and dissemination of news—journalists have remained the authority for actually creating the news. This division of labor is changing, which, not surprisingly, has shaken up journalism in recent years. The World Editors Forum listed automated journalism as a top 2015 newsroom trend,3 and both researchers and practitioners are debating the implications of this development.4 For example, while some observers see potential for automating routine tasks to increase news quality, journalists’ fears that the technology will eventually eliminate newsroom jobs often dominates the public debate.5
In any case, opinions run strong on the use of automated journalism, which is why the technology has attracted so much attention. Popular media coverage includes NPR’s Planet Money podcast, which had one of its most experienced reporters compete with an algorithm to write a news story,6 and The New York Times’s quiz that allows readers to guess whether a human or an algorithm wrote a particular story.7 Even The Daily Show’s humorous coverage of the topic sheds light on potentials and concerns of increased usage8.
This guide is structured as follows. Chapter 2 describes the status quo of automated journalism; Chapter 3 then discusses key questions and implications for stakeholders, such as journalists, news consumers, news organizations, and society at large; and Chapter 4 summarizes the findings and provides recommendations for future research.