Monografico_3_EN_Doxa_29

writing will soon show what it can really do, especially when it merges with other technological advances in journalistic writing and production.

The newspaper industry is aware that it must adapt to changing times and apply these techniques to traditional methods of generating news (Hansen et al., 2017). AI provides an encouraging scenario for innovative quality journalism (Fernández Barrero, 2018), which will allow journalists to move away from tasks that are more repetitive and routine and develop ones that are more creative and add value to journalistic work (Bunz, 2010; Ford, 2013; Graefe, 2016). In this context, recent investigations have analysed automated news writing and its impact on news production (Túñez, Parada, Toural, 2019), as well as the quality of automated news (Sandoval Martín, et al., 2019). Others show that the audience is not able to differentiate between texts produced by journalists and those produced through AI (Napoli, 2012; Van Dalen, 2012). For Silverman (2013), AI improves the quality and accuracy of journalism since its use promotes real time verification, allows for rapid identification of errors, provides instantaneous generation of timelines with factual data, detects plagiarism and manipulation of texts, and efficiently gathers a significant number of sources.

However, it should not be forgotten that there are various risks involved in its use, especially from the point of view of employment, business and the quality of information (Murcia; Ufarte, 2019). Another challenge is the development of AI proposals that not only replace the mechanical or operative part of the data control process and its objective value, but also succeed in transferring the cognitive part of journalistic work to the machine (Túñez; Toural, 2018). However, whether its use is more or less ethical does not depend on the scientific discipline developed over the years, but rather on the use made of it. For Sancho Caparrini (2018), its use is certain to change radically the way we face and solve specific problems, and this process has already begun, according to this researcher.

In this context of change, Cid (2017) and Oremus (2014) state that while this technology may be an excuse to replace editors and result in a crisis of unemployment just when the profession is starting to be resuscitated after a deep economic crisis (APM, 2018), the cause should not be sought in automatic writing systems, but in a business model shaken by the transfer of readers and advertisers from print to digital formats.

Whittaker (2018) criticizes the situation in which the growing weight of technology in information businesses has increased the value of business decisions to the detriment of journalistic issues. These systems need the help of humans to learn, so an analysis of their own functioning and the value of information is necessary. Therefore, there is no real danger of the profession becoming extinct, but we might instead see a process of change and adjustment to which machines are incorporated as proactive players, and in which journalists must emphasize their personal contribution, the cognitive part of news production (Cerezo, 2018; Renó, 2018; Salaverría, 2016; Túñez; Toural, 2018).

The objectives of the present investigation are as follows: to analyse the structure and organization chart of the startup company called Narrativa Inteligencia Artificial, as well as to study its production processes and the quality of the journalistic texts it produces. The work uses both a quantitative and qualitative methodology and is based on the following hypotheses:

H1. The company not only pursues individual profit for its founders. Through the search for a business model that helps them generate and achieve value, they can place their attention on the demands of different sectors, such as the media, that see certain needs covered