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Technological advancements in present-day journalism: Prospects and challenges

Zahangir Kabir | Published: July 12, 2019 21:05:41 | Updated: July 15, 2019 22:27:18


Figure: Seven challenges of creative AI

Journalism has now been going through several major technological changes due to the advancement of information technologies during the past few decades. The pace of these changes is quickening now, altering the practice of the profession as never before. These changes, which encompass a wide range of activities from news gathering to dissemination through digital journalism, data journalism, and robot journalism, are bringing many benefits. At the same time, the profession faces some negative impacts too.

DIGITAL JOURNALISM: Digital journalism, also known as online journalism, is a contemporary form of journalism where editorial content is distributed via the Internet, as opposed to publishing via print or broadcast. In digital journalism the news, features on current affairs, are presented solely or in combination as text, audio, video, or some interactive forms like news-games, and disseminated through both print and digital media technology. Fewer barriers to entry, lowered distribution costs, and diverse computer networking technologies have led to the widespread practice of digital journalism.

DATA JOURNALISM: Data journalism is a journalism specialty reflecting the increased role where numerical data is used in the production and distribution of information in the digital era. It reflects the increased interaction between content producers (journalists) and several other fields such as design, computer and statistics. According to author and data journalism trainer Henk van Ess, "Data journalism can be based on any data that has to be processed first with tools before a relevant story is possible. It doesn't include visualisation per se."

Data journalism is the use of data and number crunching in journalism to uncover, better explain and/or provide context to a news story. According to the Data Journalism Handbook, data can be either the tool used to tell a story, the source upon which a story is based, or both. It often involves the use of statistics, charts, graphs or infographics. Data journalism has emerged as a new branch of journalism, thanks to the sheer scale of digital information now available and the software that may be used to crunch that data into useful forms.

In the past, journalists worked by being present on the scene and reporting the news in front of them. Today, however, news unfolds differently, often over the Internet, as multiple sources add information through blogs, videos and social media. As a result, the need to be able to access and filter that continuous stream of information has become much more important in newsrooms. By using data, a journalist's focus shifts from being the first person on the scene to being the one who provides context to an event and aims to explain what it really means.

AREAS COVERED IN DATA JOURNALISM: Areas covered in data journalism are: (i) Cybercrime reporting, (ii) Computer assisted reporting and data-driven journalism, where journalists make use of large databases to produce stories, (iii) Infographics, (iv) Data visualisation, (v) Interactive visualisation, (vi) Serious games, in the sense that they take interaction a step further, and  (vii) Database journalism or structured journalism, an information management system where pieces of information are organised in a database (as opposed to a traditional story-centric organisational structure).

AI IN JOURNALISM: In automated journalism, also known as robot journalism or algorithmic journalism, news articles are generated by computer programmes. Through artificial intelligence (AI) software, stories are produced automatically by computers rather than human reporters. These programmes interpret, organise, and present data in human-readable ways. Typically, the process involves an algorithm that scans large amounts of provided data, selects from an assortment of pre-programmed article structures, orders key points, and inserts details such as names, places, amounts, rankings, statistics, and other figures. The output can also be customized to fit a certain voice, tone, or style.

Data science and AI companies such as Automated Insights, Narrative Science, United Robots and Yseop develop and provide these algorithms to news outlets. As of 2016, only a few media organizations have used automated journalism in the world. Early adopters include news providers such as the Associated Press, Forbes, ProPublica, and the Los Angeles Times.

Due to the formulaic nature of automation, it is mainly used for stories based on statistics and numerical figures. Common topics include sports recaps, weather, financial reports, real estate analysis, and earnings reviews. In 2006, Thomson Reuters announced switch to automation to generate financial news stories on its online news platform. More famously, an algorithm called Quakebot published a story about a 2014 California earthquake on The Los Angeles Times website within three minutes after the incident happened.

Automated journalism is sometimes seen as an opportunity to free journalists from routine reporting, providing them with more time for complex tasks. It also allows efficiency and cost-cutting, alleviating some financial burden that many news organizations face. However, automated journalism is also perceived as a threat to the authorship and quality of news and the precocity of employment within the industry.

BENEFITS OF AI: Robot reporters are built to produce large quantities of information at quicker speeds. The Associated Press announced that their use of automation has increased the volume of earnings reports from customers by more than ten times. With software from Automated Insights and data from other companies, they can produce 150 to 300-word articles in the same time it takes journalists to crunch numbers and prepare information. By automating routine stories and tasks, journalists are promised more time for complex jobs such as investigative reporting and in-depth analysis of events.

Automated journalism is cheaper because more content can be produced in less time. It also lowers labour costs for news organisations. Reduced human input means less expense on wages or salaries, paid leaves, vacations, and employment insurance. Automation serves as a cost-cutting tool for news outlets struggling with tight budgets.

CHALLENGES: In an automated story, there is often confusion about who should be credited as the author. Several participants of a study on algorithmic authorship attributed the credit to the programmer; others perceived the news organisation as the author, emphasising the collaborative nature of the work. There is no way for the reader to verify whether an article was written by a robot or human, which raises issues of transparency.

There are concerns about the perceived credibility of automated news. Critics doubt if algorithms are "fair and accurate, free from subjectivity, error, or attempted influence." It is also remarked that machines do not replace human capabilities such as creativity, humour, and critical-thinking. Computers alone lack the ability to write stories with perspective, emotion, thorough analysis, and surprising observations.

Among the concerns about automation is the loss of employment for journalists. In the interest of saving costs, as mentioned previously, news organisations are inclined to cut staff when switching to cheaper, faster machines. In 2014, an annual census from The American Society of News Editors announced that the newspaper industry lost 3,800 full-time, professional editors. Falling by more than 10 per cent within a year, this is the biggest drop since the industry cut over 10,000 jobs in 2007 and 2008.

The future of automated journalism can be seen as beneficial by some. However, others would argue that it could be detrimental to the industry as it removes the sense of objectivity. As stated above, in the benefits section, the costs and efficiency of robot journalism are present and proven; however, utilising a system of automation may separate the readers from the news story. This can happen because a human journalist writing on world issues may have his own personal writing style attached to the story, whereas, an article written using automation would result in the story being bland, and mechanical.

MACHINES WILL NOT REPLACE JOURNALISTS: Due to the journalism industry's reliance on technology, the industry itself must stay dynamic and shift with current trends. The professionals who work within this field can become over-saturated due to the internet. As the internet has caused many shifts in the way this industry operates, it also opened the avenue for a citizen journalist to participate in the media much more frequently than before. Due to smart phones, with access to online databases and media sites, many people have taken on roles of amateur journalists. Overall, this has benefited the industry from an efficiency perspective; however, it can be seen as hurting the professionals who work in the journalism field.

A report titled "News Automation - the rewards, risks and realities of 'machine journalism'" focuses on a specific part of news automation: the automated generation of news texts based on structured data. This is not about crystal ball gazing. Media outlets face ever-growing commercial pressure to extract higher margins from dwindling resources and that is a key driver for news automation. Right now, one of the main goals of automated content is to save journalistic effort, especially on repetitive tasks, while increasing output volume. Automated production is foremost a tool, aiding and creating additional content.

One of the characteristics of what is labeled "automated news" is that its focus is on writing stories that journalists cannot or do not necessarily have the time to write. The good news is that so far, news automation has not replaced humans, and looks set to work alongside humans in the newsroom.

For all the hype about "robot journalism" we are more or less in the same spot as three years ago. AI has a hype problem and we need to put aside our Hollywood-inspired ideas about super-advanced AI and instead see the automation process as a logical extension of the Industrial Revolution. The future of automation lies in decomposition, or deconstruction of the fundamental principles of journalism. That means breaking down journalistic work into the actual information artifacts and micro processes to analyse what can be automated and what are inherently human tasks.

Automated journalism transforms structured data into news articles, and the quality of the output is highly dependent on the quality of the data that is fed into it. The quality of data is often described as the five V's: volume, velocity, variety, value and veracity. Volume, variety and velocity are largely relevant from a business perspective, satisfying content-hungry customers and driving revenue streams. Veracity, on the other hand, matters more from an ethical and journalistic viewpoint.

Professor Dr. M. Zahangir Kabir is Head of the Department of Journalism and Media Studies, Manarat International University, Dhaka, and Former Chairman of Media Studies, The Islamia University of Bahawalpur, Pakistan.

drzahangir@gmail.com

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