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Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Doxa Comunicación is the property of Fundacion Universitaria San Pablo - CEU and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of disinformation. At the same time, quality journalism is under pressure due to loss of revenue and competition from alternative information providers. This vision paper discusses how recent advances in Artificial Intelligence (AI), and in Machine Learning (ML) in particular, can be harnessed to support efficient production of high-quality journalism. From a news consumer perspective, the key parameter here concerns the degree of trust that is engendered by quality news production. For this reason, the paper will discuss how AI techniques can be applied to all aspects of news, at all stages of its production cycle, to increase trust. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of artificial intelligence (AI) on journalism and disinformation. To achieve this, methodological design begins with a review of the scientific literature that is complemented by the analysis of three interrelated perspectives: journalistic, economic and ethical. The results reveal disinformation to be a polysemic phenomenon, complicating the design of public policies to counter it. AI's emergence presents an opportunity to contribute to this and develop the concept of citizenship along three lines: 1) improving the state of professional journalism; 2) managing privacy; and 3) an ethical approach to technological development, which helps make informative decision-making conscious and free from biases. [ABSTRACT FROM AUTHOR]

The open launch of new artificial intelligence tools such as ChatGPT-3.5 (Generated Pre-trained Transformer) in November 2022 by the company OpenAI -and then its update to version GPT-4 in March 2023-poses new opportunities and challenges for journalism, and especially for professionals specifically focused on information verification. This research aims to understand and analyze the perceptions generated by the irruption of ChatGPT among fact-checking professionals in Spain with the aim of identifying disadvantages and advantages in its use, professional implications and desired functionalities. The study uses qualitative methodology with in-depth interviews with professionals from all Spanish fact-checking platforms belonging to the International Factchecking Network (IFCN) and the European Digital Media Observatory (EDMO). The results conclude that the use of ChatGPT presents notable ambivalences. On the one hand, there are perceived drawbacks in issues such as the transparency and reliability of sources, the scope of the data, and the format of the responses generated. However, fact-checkers also point to a possible auxiliary use of the chatbot in the tasks of gathering information, detecting falsehoods, and producing denials. The irruption of ChatGPT has a direct impact on the work routines of the fact-checkers, which can be made more difficult, reinforced or extended. Fact-checking professionals perceive themselves as "context agents" in a new ecosystem that also obliges them to further diversify their fields of action in the fight against disinformation and to accelerate the implementation of media education actions that empower citizens in the responsible use of artificial intelligence. [ABSTRACT FROM AUTHOR]

The increasing prevalence of disinformation has led to a growing interest in leveraging artificial intelligence (AI) for detecting and combating this phenomenon. This article presents a thematic analysis of the potential benefits of automated disinformation detection from the perspective of information sciences. The analysis covers a range of approaches, including fact checking, linguistic analysis, sentiment analysis, and the utilization of human-in-the-loop systems. Furthermore, the article explores how the combination of blockchain and AI technologies can be used to automate the process of disinformation detection. Ultimately, the article aims to consider the integration of AI into journalism and emphasizes the importance of ongoing collaboration between these fields to effectively combat the spread of disinformation. The article also addresses ethical considerations related to the use of AI in journalism, including concerns about privacy, transparency, and accountability. [ABSTRACT FROM AUTHOR]

Internet and social media have revolutionised the way news is distributed and consumed. However, the constant flow of massive amounts of content has made it difficult to discern between truth and falsehood, especially in online platforms plagued with malicious actors who create and spread harmful stories. Debunking disinformation is costly, which has put artificial intelligence (AI) and, more specifically, machine learning (ML) in the spotlight as a solution to this problem. This work revises recent literature on AI and ML techniques to combat disinformation, ranging from automatic classification to feature extraction, as well as their role in creating realistic synthetic content. We conclude that ML advances have been mainly focused on automatic classification and scarcely adopted outside research labs due to their dependence on limited-scope datasets. Therefore, research efforts should be redirected towards developing AI-based systems that are reliable and trustworthy in supporting humans in early disinformation detection instead of fully automated solutions. [ABSTRACT FROM AUTHOR]