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The irruption of artificial intelligence (AI) in all areas of our lives is a reality to which the university, as an institution of higher education, must respond prudently, but also with no hesitation. This paper discusses the potential that resources based on AI presents as potential reviewers of scientific articles in a hypothetical peer review of already published articles. Using different models (GPT-3.5 and GPT-4) and platforms (ChatPDF and Bing), we obtained three full reviews, both qualitative and quantitative, for each of the five articles examined, thus being able to delineate and contrast the results of all of them in terms of the human reviews that these same articles received at the time. The evidence found highlights the extent to which we can and should rely on generative language models to support our decisions as qualified experts in our field. Furthermore, the results also corroborate the hallucinations inherent in these models while pointing out one of their current major shortcomings: the context window limit. On the other hand, the study also points out the inherent benefits of a model that is in a clear expansion phase, providing a detailed view of the potential and limitations that these models offer as possible assistants to the review of scientific articles, a key process in the communication and dissemination of academic research. [ABSTRACT FROM AUTHOR]

Non-human-centered design tools, such as ChatGPT, have shown potential as effective aids in academic article design. This study conducts a comparative evaluation of ChatGPT-3.5 and ChatGPT-4, examining their capabilities and limitations in supporting the academic article design process. The study aims to demonstrate the utility of ChatGPT as a writing tool and investigate its applicability and efficacy in the context of academic paper design. The author interacted with both versions of ChatGPT, providing prompts and analyzing the generated responses. In addition, a different expert academic was consulted to assess the appropriateness of the ChatGPT responses. The findings suggest that ChatGPT, despite its limitations, could serve as a useful tool for academic writing, particularly in the design of academic articles. Despite the limitations of both GPT-3.5 and GPT-4, GPT-3.5 offers a broader perspective, whereas GPT-4 provides a more in-depth and detailed approach to the design of articles. ChatGPT exhibits capabilities in aiding the design process, generating ideas aligned with the overall purpose and focus of the paper, producing consistent and contextually relevant responses to various natural language inputs, partially assisting in literature reviews, supporting paper design in terms of both content and format, and providing reasonable editing and proofreading for articles. However, limitations were identified, including reduced critical thinking, potential for plagiarism, risk of misinformation, lack of originality and innovation, and limited access to literature. [ABSTRACT FROM AUTHOR]

Technological media effects scholarship in the field of journalism and communication is experiencing a reinvigorated blooming due to the role of Artificial Intelligence (AI) and algorithm-based information. From news production to distribution and consumption, the whole journalistic chain of information media ecosystems and the principles that govern them have all been deeply transformed with the advent of AI and algorithmic tools. Drawing from wellestablished normative principles that have guided the journalistic profession, this paper seeks to synthesize the current state of research on AI and algorithm-based news by providing a principle-based theoretical framework of news media. In doing so, the paper organizes a comparison between algorithmic news versus non-algorithmic news according to three foundational pillars sustaining journalism research: news production, selection, and effects thereof. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is already integrated into news production strategies in some media outlets. Recently, generative AIs such as ChatGPT and others have demonstrated their ability to enhance productivity in content production tasks, raising the question of how journalism faculties can address this new technology. This paper presents an academic study on the application of AI in higher communication studies. The study involved 4 in-depth interviews and 28 semi-structured interviews with university lecturers and researchers. The findings confirm varying degrees of convergence and divergence on different aspects of the technology, including the integration of AI in communication faculties, student training in AI usage, the introduction of AI and journalism as a subject area, and the potential uses of AI in news production and consumption. Additionally, this paper proposes a comprehensive training program on AI and journalism, focusing on its foundations, technical competencies and ethical considerations. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present an international overview of the use of artificial intelligence in the context of media archives in broadcasters, preservation institutions and press agencies, through a comprehensive analysis of sources primarily focusing on case studies presented at international conferences and seminars, together with the results of the survey on the use of artificial intelligence conducted by FIAT/IFTA. Once the most commonly used technologies have been defined and we have identified the stages of the production workflow in which they are used, we will discuss the specific applications of these technologies in television archives, audiovisual heritage preservation organisations, press agencies and innovation projects where technology vendors and media companies collaborate. Finally, we will deal with the challenges related to the implementation of AI in media archives, the need for datasets in the development of language models, and the relevance of a sensible use of technology. [ABSTRACT FROM AUTHOR]

AI integration in media newsrooms is changing professional routines, required profiles and journalistic products. The acceleration in the development of this technology since the end of 2022 makes it necessary to review these tools in order to analyse their uses and risks, as well as their possible applications in the journalistic field. OpenAI launched Chat-GPT in November 2022 open to the public. This tool has been a key element in this technological revolution. This paper analyses ChatGPT applications in journalistic newsrooms through its introduction during a working day in the routine of different professionals. A mixed methodology was used to carry out this experience: a benchmarking of AI tools applied to journalism was created, a walkthrough experience was carried out with ChatGPT and, based on the results obtained in these first two phases, the experiment with journalists was designed. A total of 12 journalists of different ages and sectors with little or no previous contact with technological tools based on artificial intelligence, as the aim of the study is to observe the application in newsrooms without the need for technical training, participated in this research. The results show the usefulness of the tool to automate mechanical processes, rewrite texts, analyse data and even serve as a content idea creator. On the other hand, journalists have also perceived significant risks such as inaccuracy of AI as well as lack of 'empathy'. [ABSTRACT FROM AUTHOR]

Journalism has been able to adapt quickly to technological innovation, especially in recent years. The application of algorithms and artificial intelligence (AI) to this discipline is a phenomenon that has developed rapidly in a very short time. This is therefore a research area that, in spite of its short life, deserves special interest. The objective of this review article is to map and analyze the global scientific production on this topic and to identify which countries are most focused on this issue, which areas are studied most and using which methodological approaches, how and where it is evolving, and the gaps present in this research. The review of 358 texts confirms the considerable attention from academia during the last decade, especially between 2015 and 2020, and that the USA is, by far, the country with most publications on this subject. Most of the published works are research articles carried out, above all, using qualitative methodologies. The areas that have attracted the most interest to date are data journalism, robot writing, and news verification. As is to be expected in a developing discipline, others such as the review of the role of the journalist, the personalization of content, or the incorporation of AI into teaching of journalism have not yet been sufficiently explored but surely will be in the near future. [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]

This study explores workplace gender bias in images generated by DALL-E 2, an application for synthesising images based on artificial intelligence (AI). To do this, we used a stratified probability sampling method, dividing the sample into segments on the basis of 37 different professions or prompts, replicating the study by Farago, Eggum-Wilkens and Zhang (2020) on gender stereotypes in the workplace. The study involves two coders who manually input different professions into the image generator. DALL-E 2 generated 9 images for each query, and a sample of 666 images was collected, with a confidence level of 99% and a margin of error of 5%. Each image was subsequently evaluated using a 3-point Likert scale: 1, not stereotypical; 2, moderately stereotypical; and 3, strongly stereotypical. Our study found that the images generated replicate gender stereotypes in the workplace. The findings presented indicate that 21.6% of AI-generated images depicting professionals exhibit full stereotypes of women, while 37.8% depict full stereotypes of men. While previous studies conducted with humans found that gender stereotypes in the workplace exist, our research shows that AI not only replicates this stereotyping, but reinforces and increases it. Consequently, while human research on gender bias indicates strong stereotyping in 35% of instances, AI exhibits strong stereotyping in 59.4% of cases. The results of this study emphasise the need for a diverse and inclusive AI development community to serve as the basis for a fairer and less biased AI. [ABSTRACT FROM AUTHOR]

In the last decade, journalism has progressively incorporated artificial intelligence (AI) into several processes: information analysis, content extraction, audience research, and automated copywriting, among others. ChatGPT, which has a great capacity for interacting with people through natural language and providing a response to almost any topic, focuses on content creation. This significant technological advancement rekindles the debate on whether machines will replace humans, including journalists. Focusing on the case of the Spanish press and using the framework of studying media participation in the public debate, we are interested in the press's reaction to ChatGPT's launch. Specifically, we asked the following questions: What were the issues that dominated the debate, and what voices were called upon to express their opinions? The stream of opinion on this issue was analyzed from a communication studies and discourse analysis perspective, starting with the identification of opinion statements expressed in articles of various journalistic genres conveyed by the press during the first 100 days since the launch of ChatGPT on November 30, 2022. We worked with 176 press articles that addressed the subject in five Spanish generalist newspapers. The results showed that the flow of opinion developed from 8 subtopics and 11 groups of voices. The prevailing opinion during this period was that ChatGPT is an extraordinary technological milestone, even if it makes mistakes that reveal the technology's immaturity. The main shortcomings identified were the inability to distinguish between what is true and what is false, its tendency to function as a black box, and its failure to account for the sources it uses. However, owing to the business potential that it heralds, it is clear that a real war for the dominance of AI has broken out, which makes it necessary to put regulations in place to reduce the risks of malicious use. [ABSTRACT FROM AUTHOR]

The communicative effects of disintermediation caused by social media promote the expansion of personalist and emotional political discourses that reach the audience directly and evade the traditional journalistic filter. This phenomenon leads to new political communication tactics, but also exposes citizens to potentially fraudulent, contaminated or polarised content. In this context, framed in post-truth, the term 'fake news' gains relevance as a way of referring to disinformation and as a political and performative argument that can be weaponised. This research aims to analyse such use in the discourse of the former president Donald Trump during his presidential term (2017-2021), focussing on Twitter as the main platform in his political communication strategy online. To analyse this, we resort to a methodological triangulation of content, discourse, and sentiment analysis, with the latter combining both lexicon and artificial intelligence (AI) techniques through machine learning on the basis of deep learning and natural language processing, which is applied to his messages published with the term 'fake news' (N = 768). The analysis of the sample, provided here in an open dataset, employs self-developed software that allows each unit of analysis to be filtered and coded around its predominant themes, sentiments, and words. The main results confirm that Trump's attribution of 'fake news' focusses on three main topics: the media (53%), politics (40%) and his cabinet (33%). It also shows how the former president resorts to a personalist agenda, focussed on the defence of his proposals and his team (80%) by delegitimizing his opponents and the press, with a negative tone (72%) loaded with derogatory terms, confirming a weaponised strategy of the term 'fake news' as a political argument of disinformation and disintermediation. [ABSTRACT FROM AUTHOR]

This article presents the experimental design of ClaimCheck, an artificial intelligence tool for detecting repeated falsehoods in political discourse using a semantic similarity model developed by the fact-checking organization Newtral in collaboration with ABC Australia. The study reviews the state of the art in algorithmic fact-checking and proposes a definition of claim matching. Additionally, it outlines the scheme for annotating similar sentences and presents the results of experiments conducted with the tool. [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]

The boom in artificial intelligence and automated technology in the journalistic profession has given rise to what are called synthetic media (Crusafon, 2022), media outlets that produce and publish texts, audio, videos, and other news content through processes executed solely by algorithms, without any intervention from journalists. This research has several objectives: to identify the first synthetic media outlets already operating, to describe how these newsrooms without journalists work, to better understand the type of content they produce, and to find out whether these are isolated and ephemeral operations or if, on the contrary, they mark the beginning of a trend toward journalism without the direct intervention of journalists. To this end, we have used an exploratory methodology, enabling us to identify four synthetic media outlets, which have been taken as an analysis sample: JX Press Corp (Japan); Reuters News Tracer (United Kingdom), News Republic (France), and Videre AI (Spain). An analysis of the news content on each project’s web pages was combined with in-depth semistructured interviews with the heads of technology and communication of the three European ventures. The Japanese initiative has no human staff, so its chatbot was the only way to obtain information. The purpose was to learn about the initiatives’ news production process, their impact on the journalistic profession, and their viability. This analysis helps demonstrate that the journalistic world’s reliance on artificial intelligence is becoming increasingly evident and that communication agencies are the first companies to invest in developing and distributing synthetic content to benchmark media. These initiatives, although still limited, are the most recent step in the process of gradually integrating artificial intelligence into news production. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been progressively expanding over the last decade, with its transversal application to the journalistic process and the engaging of media and technology companies in developing specific tools and services. This research offers a first catalogue of Spanish technological companies and institutions that develop AI systems applicable to journalism, with services and features grouped into three phases of the journalistic process: 1. Automated gathering and documentation of information; 2. Automated production of content; and 3. Information distribution and audience relations. The research uses a methodology of in-depth interviews with 45 innovation heads of Spanish-based companies and technological centres specialised in the development of AI (N = 25), and is supported by questionnaires to systematise four study categories: company profiles, tools, journalism-specific services and future trends. The results confirm a clear evolution of Spanish technological companies within the AI sector, with services and tools available for the whole journalistic process, mainly in the information gathering and content distribution phases related to monetisation; the automated news production phase is thereby overshadowed. The offering is diversified in terms of formats-textual, audiovisual, sound- and platforms, especially web and social media. The companies consulted testify to the profitability of its implementation and note a growing interest from the media, but warn of an uneven progress that reflects “slowness”, “distrust” and “lack of knowledge” regarding the application of AI. [ABSTRACT FROM AUTHOR]

As artificial intelligence (AI) gains space in the media, public broadcasters are testing and experimenting with these technologies to raise their services to the new standards of the audiovisual ecosystem. From algorithms that help recommend the most suitable content for users, to others that detect news and automate some of the tasks of journalists, these tools are increasingly present in public audiovisual corporations. The data were obtained from semi-structured in-depth interviews with a convenience sample of 15 corporations from 12 countries. The results reflect a heterogeneous application of artificial intelligence in corporations, oriented towards the automatic creation of content from structured data, the improvement of audience interaction through chatbots, and personalisation or verification. The implementation of these technologies also poses major challenges. Firstly, the economic cost of adapting these systems to each corporation and the difficulties in hiring experts to develop AI solutions prevent a complete deployment of these tools in public broadcasters. As main conclusions, we have understood that AI as a "culture" is believed to be vital for the public audiovisual services of the future, although its application is still far from being a standard and generally does not occupy a relevant strategic position in the innovation departments of corporations. [ABSTRACT FROM AUTHOR]