About this Research Topic
The media have been undergoing a digital transformation for several decades; one that has had profound effects on all their work processes. The emergence of artificial intelligence (AI) and, more recently, generative AI, has given a significant boost to content automation; a process already experimented with for over half a century. In the context of journalism, for example, the applications of content automation are commonly associated with the use of algorithmic processes that convert data into narrative texts and news, with limited or no human intervention beyond the initial programming phase (Carlson, 2015). Unlike previous experiences, the implementation of AI in the media will have a more global and widespread impact on the creation of content, thereby fueling the debate about the future of journalists, audiences, and the media themselves.
AI is a dual-use technology; as such, its impact on the media, journalists, and audiences is complex and multifaceted. On the one hand, it has the potential to eventually turn algorithms into proper content-generating agents, thus assuming a role that goes far beyond the one it has played until now as a mediating agent of human communication (Guzman and Lewis, 2020). Its capabilities can also be key in the optimization of production processes, the improvement of the media’s economy, and the creation of new business models, such as personalized content.
On the other hand, the implementation of AI in the media can create new vulnerabilities, multiply information disorders (Brennen et al., 2018; Brundage, 2018; Karnouskos, 2020), as well as generate challenges relating to transparency. Furthermore, it also risks becoming the back door to increasing the media’s dependence on the large technological platforms.
By the same token, the potential for AI to transform the work of journalists is enormous: routine tasks can be fully automated, leaving them with more time to return to the essence of their profession. Yet such advantages are accompanied by the fear of staff redundancies as well as the questioning of their social status.
Finally, while audiences may perceive the emergence of AI tools as an opportunity to enrich the information they access, they may also experience new threats: the rise of new divides caused by the employment of old/biased data banks or design errors, the invasion of their privacy, damage to pluralism, and political polarization.
The goal of this Research Topic is to respond to these challenges, risks, and opportunities in the light of the growing implementation of AI in the field of communication. Potential themes of interest include, but are not limited to, the following:
• the analysis of automated information content (credibility, quality of information, ease of reading, etc.)
• new journalistic formats
• the relationship between platforms and media in an increasingly technological environment
• the impact of AI on the privacy and transparency of media content
• regulatory and legal developments on AI
• the ethical repercussions of the use of automated content
• new professional profiles and new tasks
• changes in the training of journalists and communicators
• the impact of AI on the employment and working conditions of journalists
• the reception of automated content by audiences and its social effects (polarization, pluralism, etc.)
• new digital divides (gender, race, social class, etc.).
Image credit: Martina Stiftinger
AI is a dual-use technology; as such, its impact on the media, journalists, and audiences is complex and multifaceted. On the one hand, it has the potential to eventually turn algorithms into proper content-generating agents, thus assuming a role that goes far beyond the one it has played until now as a mediating agent of human communication (Guzman and Lewis, 2020). Its capabilities can also be key in the optimization of production processes, the improvement of the media’s economy, and the creation of new business models, such as personalized content.
On the other hand, the implementation of AI in the media can create new vulnerabilities, multiply information disorders (Brennen et al., 2018; Brundage, 2018; Karnouskos, 2020), as well as generate challenges relating to transparency. Furthermore, it also risks becoming the back door to increasing the media’s dependence on the large technological platforms.
By the same token, the potential for AI to transform the work of journalists is enormous: routine tasks can be fully automated, leaving them with more time to return to the essence of their profession. Yet such advantages are accompanied by the fear of staff redundancies as well as the questioning of their social status.
Finally, while audiences may perceive the emergence of AI tools as an opportunity to enrich the information they access, they may also experience new threats: the rise of new divides caused by the employment of old/biased data banks or design errors, the invasion of their privacy, damage to pluralism, and political polarization.
The goal of this Research Topic is to respond to these challenges, risks, and opportunities in the light of the growing implementation of AI in the field of communication. Potential themes of interest include, but are not limited to, the following:
• the analysis of automated information content (credibility, quality of information, ease of reading, etc.)
• new journalistic formats
• the relationship between platforms and media in an increasingly technological environment
• the impact of AI on the privacy and transparency of media content
• regulatory and legal developments on AI
• the ethical repercussions of the use of automated content
• new professional profiles and new tasks
• changes in the training of journalists and communicators
• the impact of AI on the employment and working conditions of journalists
• the reception of automated content by audiences and its social effects (polarization, pluralism, etc.)
• new digital divides (gender, race, social class, etc.).
Image credit: Martina Stiftinger
Keywords: AI, generative AI, media, journalists, audiences, content automation
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