A Decision-Making Model for Adopting Al-Generated News Articles: Preliminary Results

Abstract

This study was conducted to present a consumer acceptance model for artificial intelligence (AI)-generated news articles in review of the most significant factors in the context of accepting AI-generated news articles. To this end, a survey was conducted regarding five key factors among individuals handling news production at media organizations who were familiar with AI-related news: benefits of technology utilization, recognized values, media reliability, content quality, and information perception. These factors were classified into 19 specific evaluation items in order to determine relative importance. According to the results of pairwise comparison analysis among elements through the analytic hierarchy process, hereunder referred to as AHP (analytic hierarchy process), it turned out that the importance of media reliability and content levels was relatively high, while the importance of recognized values and information perception was relatively low. It also turned out that among 19 specific items, the importance of institutional reliability, which was a subordinate item under media reliability, was of utmost value. Even if news articles were based on AI technology, their readers were more likely to be affected by reliability, which is a major attribute of journalism, than technical factors.

Towards a Sustainable News Business: Understanding Readers’ Perceptions of Algorithm-Generated News Based on Cultural Conditioning

“…In particular, news organizations are making efforts to improve the efficiency of news generation by employing news-generating algorithms to simulate natural language. In particular, the scope of artificial intelligence (AI) is constantly expanding and the technology is being used in various areas ranging from marketing to finance, from transportation to agriculture, from healthcare to security, and from chatbots to artificial creativity and production in manufacturing [1,2]. Clearly, AI has started to significantly impact general media and news agencies under the name of "robot journalism" (also known as computational journalism, algorithm journalism, or machine-written journalism) [2,3].…”

“…In particular, the scope of artificial intelligence (AI) is constantly expanding and the technology is being used in various areas ranging from marketing to finance, from transportation to agriculture, from healthcare to security, and from chatbots to artificial creativity and production in manufacturing [1,2]. Clearly, AI has started to significantly impact general media and news agencies under the name of "robot journalism" (also known as computational journalism, algorithm journalism, or machine-written journalism) [2,3]. Robot journalism has been introduced to, or recognized by, the general public since 2010 and refers to the automatic generation of news articles using AI-based algorithms with no involvement of human journalists [2].…”

“…Clearly, AI has started to significantly impact general media and news agencies under the name of "robot journalism" (also known as computational journalism, algorithm journalism, or machine-written journalism) [2,3]. Robot journalism has been introduced to, or recognized by, the general public since 2010 and refers to the automatic generation of news articles using AI-based algorithms with no involvement of human journalists [2]. The Associated Press (AP), Forbes, and Los Angeles Times, to name popular examples, have already made use of such technology [4].…”

“…At present, journalism industries view robot journalism as an opportunity to enhance news quality, accuracy, and message credibility since it allows news content to be produced faster, in multiple languages, and possibly with fewer mistakes and bias [2,4]. Furthermore, this innovative type of journalism has the potential to create a sustainable business model for news organizations.…”

“…The consumption of news on digital media tends to be highly selective [4,5], and these changes in the media environment have produced significant challenges for news organizations [5]. From a marketing perspective, scholars encourage news producers to use algorithms to cover simple local reports because they may reduce costs and broaden news audience [2,5]. Furthermore, news organizations are now experiencing a loss of authority in creating news values and facing audiences' skepticism about the truth.…”