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(Series Information) European Papers - A Journal on Law and Integration, 2024 9(1), 105-116 | European Forum Insight of 20 May 2024 | (Table of Contents) I. Introducing the impact of Artificial Intelligence. – II. The AI Act: the risk architecture. – III. Further AI policies: development incentives and state regulatory frameworks. – IV. Proposals for legislation and other measures in Italy. – V. The human-centric approach. | (Abstract) The development of new emerging technologies, such as artificial intelligence, has sparked a scientific debate on their risks and benefits. This debate necessitates legal and regulatory considerations, particularly regarding the balance between technological growth and the protection of human rights. This Insight analyses the legal framework established by the European Union in its initial regulatory measures. The Insight highlights the importance of considering the human-centric perspective and adopting a risk-based methodology in the Artificial Intelligence Act. It also mentions the AI regulatory measures proposed by Member States, with a particular focus on Italy.

This paper discusses the concept of new diplomacy and its relationship to smart power, arguing that soft power is just as important as hard power in international politics. The paper explores the emergence of geotechnology as a new variable in international relations, referring to the competition between countries to control and gain influence in areas of technological importance. Additionally, the paper highlights a theoretical gap in the study of international relations regarding cyberspace and the new realities imposed by technology. It discusses the role of technology in shaping a new framework for international relations, leading to increased complexity, interconnection, and interdependence. The paper argues that states must adapt to the logic of performance in the international environment and that technological progress has led to radical changes in the elements and balances of power. The researcher aims to present a new theory in international relations that analyzes the influence of digital technology and social media on shaping international relations and rearranging actors and factors. This theory suggests that these technological advancements have significant impacts on international policy directions, as well as political and economic decision-making.

(Series Information) European Papers - A Journal on Law and Integration, 2020 5(2), 1087-1097 | European Forum Insight of 20 September 2020 | (Table of Contents) I. Introduction. - I.1. AI and the need for a system of governance. - I.2. Introduction to AI and the risks it poses to fundamental rights. - II. An assessment of the Commission's concerns surrounding the EU's primary legal framework's suitability to address the risks posed by AI to fundamental rights. - III. An analysis of how well the GDPR addresses the challenges posed by AI to the fundamental rights of privacy, personal data protection, and non-discrimination. - IV. Conclusion. | (Abstract) In early 2020, the European Commission published a White Paper on artificial intelligence (AI) regulation, in which it highlighted the need to review the EU's legislative framework with a view to making it fit for the cur-rent technological developments. The aim of this Insight is to carry out such review from the perspective of fundamental rights. The Insight briefly assesses the Commission's concerns surrounding the suitability of the Union's primary legal framework to address the risks posed by AI. More specifically, the analysis is focused on the question concerning how well the GDPR addresses the challenges posed by AI to the fundamental rights of privacy, personal data protection, and non-discrimination - which are the three main intersections between AI and fundamental rights. The perspective adopted in the present study is particularly relevant because the need to regulate AI through the lens of fundamental rights law is still largely underdeveloped. Fundamental rights concerns are mainly triggered when the development and use of AI concern the processing of personal data and thus fall within the scope of application of the GDPR. In this Insight, it is argued that the GDPR is well equipped to disruptively challenge actual or potential undesirable uses and applications of AI but some deficiencies are also clearly visible. In particular, in relation to the concept of specific consent, the scope of the data subject's right to information, and on how best to conduct data protection impact assessments when it comes to guaranteeing a trustworthy fundamental rights compliance of the technology.

AI-based chat agents within educational settings present a promising pathway for bolstering collaborative learning (CL), especially in the sphere of English as a Foreign Language (EFL). This paper investigates the evolving role of chat agents based on Artificial Intelligence (AI) and Large Language Models (LLM), notably ChatGPT, in the landscape of CL specific to EFL. The primary aim is twofold: firstly, to discern the productive and unproductive applications of ChatGPT in a CL environment, and secondly, to investigate approaches for harnessing ChatGPT to amplify productive CL experiences in EFL contexts. We present a literature review addressing the main objective of this paper, i.e., the exploration of the productive and unproductive uses of ChatGPT for CL in the EFL context. The findings aim to provide insights into the capabilities and limitations of ChatGPT in fostering language skills, enhancing communication competence, and encouraging cooperative learning strategies among EFL learners. This present paper delineates approaches and possible pitfalls when employing AI chat agents in language learning, attempting to bridge the divide between AI technology and instructional design, aiming to facilitate a more informed and efficacious utilisation of AI within collaborative EFL learning environments.

The paper investigates the emergence of the phenomenon of new subjectness that arises from the integration of artificial and natural fields in contemporary socio-technical reality. It aims to challenge the subject-object dichotomy established by Modern philosophy tradition. To support this goal, the paper draws on the philosophical views of the proponents of Object-Oriented Ontology (Manuel DeLanda, Graham Harman) and Actor-Network theory (Bruno Latour, John Law). These contemporary philosophers substantiate the idea of distributed hybrid subjectness as the result of multiple network interactions, which can be interpreted using John Law's "method assemblage". This method disregards the attitudes of classical metaphysics and leads to the conclusion that new subjectivity arises from chaotic reality and manifests through the continuous formation and reformation of "bundles of relations". In those relations, it is impossible to differentiate between subject and object, as these roles roles are mobile and volatile

The present paper functions as an introduction to this special issue of mediAzioni, which brings together selected papers presented at the Translating Europe Workshop entitled "L'intelligenza artificiale per la traduzione verso una nuova progettazione didattica?" (3 December 2021), focusing on the pedagogical implications of Artificial Intelligence (AI), with a particular emphasis on Neural Machine Translation (NMT). The article revolves around three main themes. First, it considers the impact of emerging neural technologies on language services, redefining the traditional role of the translator and creating new responsibilities and tasks. Despite the considerable progress that NMT has made compared to previous models, it still has shortcomings that are almost "invisible" because they often lack clear grammatical or morphosyntactic marking. Such errors require a certain cognitive effort to identify, since they involve problems that are less obvious to the untrained eye, such as textuality or inadequacies at the level of discourse. Secondly, the article looks more closely at professional practices, especially those related to pre-editing, post-editing and proofreading. Particular emphasis is placed on the indispensable role of the human in translation workflows that integrate NMT not only at the level of post-editing and text revision, but also at the level of translation project management. Finally, the paper moves on to the implications of NMT for the training of translators and beyond, discussing key insights from the workshop participants regarding future teaching practices at university level. The article concludes by outlining the structure of this special issue and providing a brief synopsis of the collected papers.

It has been observed that the stratification of Autism Spectrum Disorders (ASD) generated by the current scales is not effective for the personalization of early treatments. The clinical evaluation of ASD requires its consideration as a continuum of deficits, and there is a need to identify biologically significant parameters (biomarkers) that have the power to automatically characterize each individual at different stages of neurological development. The emerging field of computational psychiatry (CP) attempts to meet the needs of precision diagnosis by developing powerful computational and mathematical techniques. A growing scientific activity proposes the use of implicit measures based on biosignals for the classification of ASD. Virtual reality (VR) technologies have demonstrated potential for ASD interventions, but most of the work has used virtual reality for the learning / objective of interventions. Very few studies have used biological signals for recording and detailed analysis of behavioral responses that can be used to monitor or produce changes over time. In this paper the concept of behavioral biomarkers based on VR or VRBB is introduced. VRBB will allow the classification of ASD using a paradigm of computational psychiatry based on implicit brain processes measured through psychophysiological signals and the behavior of subjects exposed to complex replicas of social conditions using virtual reality interfaces.

Objective: The Computer-Supported Collaborative Learning (CSCL) approach integrates artificial intelligence (AI) to enhance the learning process through collaboration and information and communication technologies (ICTs). In this sense, innovative and effective strategies could be designed for learning computer programming. This paper presents a systematic mapping study from 2009 to 2021, which shows how the integration of CSCL and AI supports the learning process in programming courses. Methodology: This study was conducted by reviewing data from different bibliographic sources such as Scopus, Web of Science (WoS), ScienceDirect, and repositories of the GitHub platform. It employs a quantitative methodological approach, where the results are represented through technological maps that show the following aspects: i) the programming languages used for CSCL and AI software development; ii) CSCL software technology and the evolution of AI; and iii) the ACM classifications, research topics, artificial intelligence techniques, and CSCL strategies. Results: The results of this research help to understand the benefits and challenges of using the CSCL and AI approach for learning computer programming, identifying some strategies and tools to improve the process in programming courses (e.g., the implementation of the CSCL approach strategies used to form groups, others to evaluate, and others to provide feedback); as well as to control the process and measure student results, using virtual judges for automatic code evaluation, profile identification, code analysis, teacher simulation, active learning activities, and interactive environments, among others. However, for each process, there are still open research questions. Conclusions: This work discusses the integration of CSCL and AI to enhance learning in programming courses and how it supports students' education process. No model integrates the CSCL approach with AI techniques, which allows implementing learning activities and, at the same time, observing and analyzing the evolution of the system and how its users (students) improve their learning skills with regard to programming. In addition, the different tools found in this paper could be explored by professors and institutions, or new technologies could be developed from them.

Objective: This paper is dedicated to Artificial Intelligence and it consists in identifying the role and functions performed by Artificial Intelligence by noting the innovations brought by the introduction of this technology. Artificial Intelligence seems to be the most successful achievement of scientists today. As a result of this development and widespread use have arisen discussions on the legal regulation of Artificial Intelligence. Methodology: The main methodological approach applied is the normative approach. The paper will be based on the qualitative method, which consists of collecting and processing data in order to compare and interpret the provisions or policies that provide for artificial intelligence. The following research methods will be applied in this paper: research method, descriptive method, comparative and analytical method, interpretive analysis method and illustrative method. Results:There is still no proper legislative framework on Artificial Intelligence. Despite not having a consolidated legal framework, states have made the first efforts in drafting legal acts and norms governing the field of Artificial Intelligence. From the concrete analysis of existing legislative acts in many countries, we conclude that the intention of the legislator in trying to regulate the field of Artificial Intelligence arises as a result of the disadvantages of using these technologies, their widespread use and ability to influence the way of the development of many processes. Contributions: The article contributes to the theoretical treatment of Artificial Intelligence by arguing on the problems of its legal regulation.

Over the last decades, the emergence of new technologies has brought changes in all areas of social life, including the education sector. Among those, artificial intelligence (AI), after many years playing a secondary role, has recently positioned itself as one with the most capacity for disruption. The newest AI tools have the potential to meaningfully transform various education areas, particularly at the university level. This paper presents a comparative analysis of the opinions of media students from Spain and Serbia on the use of ChatGPT in the learning process. The aim of the work is to determine the similarities and differences in the opinions of students in relation to the following aspects: intention to use, benefits and challenges and potential for personalised learning. A qualitative research method, with structured written interview, was used on a sample of 40 students of the initial years of media studies from universities in both countries. The results indicate that there are similarities and differences in the opinions of media students about using ChatGPT for learning. The findings provide insight into the opinions of media students as key subjects in the learning process and can be a starting point for further research aimed at understanding the role of AI tools and their application in higher education.

Il saggio affronta in modo innovativo la delicata questione del sistema carcerario. Elemento centrale dell’elaborato è la pena pecuniaria, un prezioso strumento sanzionatorio che gli antichi greci hanno donato al sistema penale e che, come evidenziato dalla Prof.ssa Eva Cantarella, ha consentito il passaggio dal Mondo della Vendetta al Mondo del Diritto. L’Autrice sostiene quanto affermato dal Prof. Emilio Dolcini fin dagli anni ’70 del Secolo scorso, in tema di introduzione del sistema a tassi giornalieri, aggiungendo nuovi elementi. Il Case study è il modello dei tassi giornalieri del sistema penale peruviano che si avvale anche dell’utilizzo di un software, e che, secondo la visione dell’Autrice, è una strada possibile anche in Italia per avere un effetto benefico a catena sul sistema carcerario nel suo complesso. Molti passi avanti sono stati compiuti in tema di pene pecuniarie attraverso la Riforma Cartabia che ha consentito di risolvere importanti problematiche del quadro normativo precedente, ma il presente scritto si soffermerà sui nodi ancora irrisolti in quanto punta ad affrontare le criticità ancora esistenti. The essay tackles the delicate issue of the prison system in an innovative way. The central element of the paper is the pecuniary penalty, a precious sanctioning tool that the ancient Greeks gave to the penal system and that, as Prof. Eva Cantarella pointed out, allowed the passage from the World of Vengeance to the World of Law. The author supports what Prof. Emilio Dolcini has been saying since the 1970s about the introduction of the daily rate system, adding new elements. The case study is the model of daily rates in the Peruvian penal system, which also makes use of software, and which, in the author's view, is a possible way also in Italy to have a beneficial knock-on effect on the prison system as a whole. Many steps forward have been taken in the area of financial penalties through the Cartabia Reform, which resolved important issues of the previous regulatory framework, but this paper will focus on the still unresolved knots as it aims to address the still existing critical issues.

Artificial Intelligence and Language Technologies in the Field of Translation The present paper deals with the opportunities which language technologies and artificial intelligence might offer for translation professionals. The paper also examines and elucidates that these technologies might contain possible problems, hurdles and obstacles. But the researcher reinforces that they also possess the necessary skills, competencies and prerequisites for the successful implementation and use of these technologies as illustrated in the Literature Review and Discussion parts of this research. It has also been shown that the successful implementation of such tools requires both institutional and technical prerequisites. A not inconsiderable problem, however, is the question of the what extent to which and whether the significance of the digital translator can also be adequately illustrated and clarified in the non-institutional private sector. Current developments in this respect unfortunately tend to point to the opposite, i.e. to the degradation of his role to a mere "helper" of the machine that (apparently) does most of the translation work. Translators, then, will ultimately only be able to truly benefit from language technology and artificial intelligence if their status is not further compromised as a result. It is not very helpful if productivity and speed can be increased, but in inverse proportion to this, the fees constantly decrease, because it is made to appear that the computer is now doing most of the work. The end result of this development would be the digital slave rather than the highly professional digital language mediator. The paper projects that language technologies and artificial intelligence potentially offer benefits in the sense that they promote a better understanding and functioning of the symbiosis between humans and machines through the automation and streamlining of certain language-related workflow processes, i.e., a set of tasks that can be performed primarily - or even entirely - through workflow automation and with the help of content management software. Through the various past research on the subject and through secondary data analysis it has been analysed and stated in the paper that the potential acceleration of work processes improves overall efficiency by requiring less time to complete the same tasks. Therefore, this study evidently establishes the argument that artificial intelligence allows human actors to focus on more meaningful tasks associated with quality control, while routine and especially technical tasks are delegated (for the most part) to the machine. This also leaves more time for creative aspects. Artificial intelligence and language technology are not only relevant for translating, but also for interpreting, even if progress in this area is still somewhat slower and a paradigm shift has yet to occur. In this regard, conference interpreting is of particular interest. Problematically, the relevant software has so far lacked the cognitive, cultural, intellectual, and emotional skills that inevitably underlie qualitatively responsive interpretation. But at least it is possible to improve the interpreter's preparation for a meeting or conference. The relevant tools have so far only a supporting role to play. Language technologies and artificial intelligence potentially offer benefits in the sense that they promote a better understanding and functioning of the symbiosis between humans and machines through the automation and streamlining of certain language-related workflow processes, i.e., a set of tasks that can be performed mainly - or even entirely through workflow automation and with the help of content management software. Further development of artificial intelligence, machine translation has recently made significant progress. Nevertheless, it is common practice to first subject the machine-translated text to review or proofreading by a human translator. Post-editing is the process of using a machine-translated text as a basis and having it improved by a human translator. This means that the human translator ultimately creates the final translation.

Formalization of natural language metaphors is a notorious problem in artificial intelligence and in other overlapping domains. It is semantic vagueness that makes metaphors resistant to formulaic or algorithmic descriptions. Great effort has been invested into modeling metaphors computationally but the issue remains methodologically uncertain and needs further research. This paper works on a practical solution to the problem how metaphorical meaning can be represented in a way suitable for computation. The research agenda of this paper is interdisciplinary; it brings together an algebraic heuristic-driven theory for metaphors developed in artificial intelligence and an applied theory of meaning that comes from cognitive linguistics. This agenda postpones theoretical speculation and argument and is solely solution-focused, which contributes to the value of this paper’s attempt to bridge the cognitive science disciplines whose compatibility, though declared, is seldom demonstrated in a piece of practical research. This paper works with metaphors of human emotions that are linguistically manifested in modern English discourse. Emotions by virtue of their ineffability as qualia are rich in metaphorical conceptualizations and serve the research agenda well. This paper in a meaningful way exposes and ranks designated properties of the FEAR, SADNESS, HAPPINESS, and RELAXATION/SERENITY concepts and arranges these properties into general-purpose ontologies that explicitly specify metaphorically preferred emotion conceptualizations and are good candidates for computation. In prospect, this paper will account for some theoretical aspects of the research and probe the algorithmic and repetitive nature of schemas that license metaphorical expressions in natural language.

2001: A Space Odyssey (Kubrick, 1968) speculates on humanities technological ascension through the exploration of space and the ultimate transcendence of humanity galvanised by the invention of AI. Every detail of this portrayal was an exercise in World Building, with careful considerations of then state-of-the-art technology and informed predictions. Kubrick’s speculative vision is comparative to the practice of Design Fiction, by suspending disbelief and leveraging a technologies emergence to question the future’s sociotechnical landscape and its ramifications critically. Discovery’s AI system, Hal9000, is a convincing speculation of intelligence with Kubrick’s vision showcasing current and long-term aims in AI research. To this end, Hal9000 uniquely portrays Artificial General Intelligence (AGI) underpinned by visualising ‘narrow’ AI subproblems; thereby, simultaneously highlighting then current research agendas within AI and manifesting them into the aspirational research agenda of human-computer symbiosis. As a result of Kubrick’s mastery in suspending a viewer’s disbelief despite portraying a particular reality for AI, and humanities fascination with artificial life, the term AI simultaneously refers to the grand vision of AGI as well as relating to the contemporary reality of narrow AI. This confusion, along with establishing AI’s ontology, are current challenges that need addressing to create effective and acceptable realisations of AI. This paper responds to the ontological confusion by reviewing and comparing Kubrick’s speculative methodology to the practice of Design Fiction by unpacking Hal9000 as a diegetic prototype while defining the active threads of ‘AI’s Definitional Dualism’. The paper will also present a Design Fiction submerged in the reality of narrow AI and the adoption of a More-Than Human Centred Design approach to address the complexity of AI’s ontology in alternative ways. Finally, this paper will also define the importance of researching the semantics of AI technology and how film and Design Fiction offer a discursive space for design research to transpire.

This study delved into the world of Digital Marketing in social networks, exploring its evolution from 2018 to April 2023 through the prism of the Scopus database. Using a quantitative methodology with a bibliometric approach, 368 documents were examined using statistical tools such as VOSviewer, RStudio and Microsoft Excel. The results paint a picture where the annual document production shows a steady decline of -3.34%, attributed to saturation, changing algorithms and mutable preferences. With the participation of 81 countries, Spain, USA, UK, India, and Indonesia emerge as prominent players, while 26 subject areas, led by Business, Computer Science and Social Sciences, top the subject matter. Documentary diversity is reflected in articles (76.36%), papers (15.22%) and reviews (3.80%). In this scenario, nine authors, including Civelek et al. (2020), Dwivedi et al. (2020), and Saura (2021), stand out. The exploration of trends took the form of a Thematic Map with specific sections, while future inquiries are oriented towards resource theory, destination marketing, social network platforms, diet advertising and social network analysis. Overall, this study not only provides insight into contemporary scientific production, but also points to fruitful directions for future research.

The purpose of this paper is to illuminate the main ethical, legal and social implications (ELSIs) concerning social humanoid robots that have their base in artificial intelligence (AI). The main dilemma highlighted touches upon the expansion of the concept of legal personhood, and the attribution of appropriate legal responses to govern the future proliferation of AI systems vis-à-vis social humanoid robots. The paper cautions on the need to carefully reflect on notions of personhood and human dignity for AI systems, balanced against the underlying representation of values and behaviors that may threaten to erode the human rights discourse. Additionally, it questions the wisdom of the broad expanse of the European legal response to the development and use of AI systems.

Generative AI applications enable different useful functions for learning based on the generation of content. This paper aims to offer a theoretical framework to understand them as tools for cognition (TFC), framed in the perspective of sociocultural theory and activity theory and distributed cognition. This perspective exemplifies how thought is not only packaged inside the individual's mind, but is distributed among subjects, objects, and artifacts, where tools mediate human activity and help in the executive functions of thought. The perspective of TFC embodies an educational socio-constructivist vision where learners build their knowledge with these tools, taking advantage of their affordances. It is the concept of learning "with" technology instead of the traditional vision of learning "from" technology, where technological applications are limited to providing information and evaluating the students' responses. Finally, we describe Generative AI applications as TFC following David Jonassen's pragmatic and pedagogical criteria, i.e. the capacity of knowledge representation of different subjects, the facilitation of critical and meaningful thinking (based on questioning and prompting) and how they enable complex thinking among students when used in learning tasks, only when executive functions are on the side of the learner.

Il contributo si propone di indagare i meccanismi di automazione nel processo civile nelle procedure concorsuali, attraverso l'analisi della normativa di riferimento sia del processo telematico che del Codice della crisi d’impresa e dell’insolvenza. A tal fine, si prenderà in considerazione il grado di automazione dei procedimenti, evidenziandone le criticità e le funzioni non ancora implementate; si procederà inoltre ad una comparazione con i sistemi processuali di Germania, Francia e Spagna; si tratteggeranno infine le conclusioni in vista di prospettive future utili ad una maggiore armonizzazione tra procedimenti giurisdizionali e tecnologia. The paper aims to investigate the mechanisms of automation in civil and insolvency procedures, through the analysis of the reference legislation of both the telematic process and the New Insolvency Law. To this end, the degree of automation of proceedings will be taken into consideration, highlighting critical issues and functions not yet implemented; a comparison will be made with the procedural systems of Germany, France and Spain; conclusions will be drawn in view of future outlooks useful for a greater harmonisation between judicial proceedings and technology.

In today's professional communication, a constant expansion of vocabulary is necessary to keep up with developments in technology and science. This paper looks at the current topic of artificial intelligence in relation to applications such as ChatGPT and chatbots. The investigation will also explore the potential of artificial intelligence in promoting and supporting linguistic skills. Additionally, the discussion will cover the implementation of these AI tools into foreign language curricula and classroom practices. Specific requirements for teachers and students are addressed under the aspect of future competencies, which represent a particular challenge given the high speed of diverse developments. This study contributes to the ongoing discussion regarding the role of artificial intelligence in higher education. Overall, this evaluation offers insights into a highly topical issue of AI application that will significantly influence linguistic and pedagogical practice in the future.

Artificial intelligence (AI) has emerged as one of the central topics of 2023 with extensive media coverage of the most relevant technologies and issues associated with this subject. In a highly competitive digital media landscape, search engine optimization (SEO) has become cybermedia’s primary strategy to increase visibility and attract more readers. The objective of this paper is to analyze the visibility of content published by the media relating to artificial intelligence, focusing on a selection of related keywords. The research also aims to investigate how this visibility has impacted both the technologies themselves and the analyzed media outlets. A total of 69 media outlets from 12 European Union countries, the United States, and the United Kingdom were examined. The results reveal a pronounced dominance of U.S. media, closely followed by Spanish media. There is an uneven distribution of media outlets across most of the countries analyzed, with two or three most of the of visibility. The search queries that contribute the most visibility to the analyzed media align with an informational intent, are of the long-tail type, and are associated with OpenAI technologies, particularly ChatGPT. Moreover, these queries are primarily found in news sections dedicated to science and technology. The findings underscore both the increasing interest in the subject and the effective SEO practices of certain media outlets.

Hospitals use different technological tools to implement corporate communication initiatives and, in this way, improve their relationships with stakeholders (employees, patients, media companies) and build a reputed brand. However, they face different barriers: limited budgets for corporate communication, strict legal frameworks, and stakeholders’ new needs regarding information and emotional support. This paper aims to analyze how the 100 best hospitals in the United States manage smart technologies to promote their brand. To do that, we conducted a literature review about smart hospitals, branding, and corporate communication; and then we defined 34 quantitative indicators to evaluate how the hospitals previously mentioned managed their websites, online newsrooms, about us sections, and artificial intelligence department web sites for reputation purposes. Our results proved that most hospitals respected indicators related to the homepage (8.67/11) but not those referring to online newsrooms (4.44/11) or about us sections (2.66/6). Besides, only 23 hospitals had implemented a department specialized in artificial intelligence that collaborated with external organizations. We concluded that most American hospitals focused their reputation efforts on patients rather than other targets (media companies, employees, suppliers, shareholders); and that these organizations did not integrate enough artificial intelligence projects into their smart branding initiatives.

The impact of artificial intelligence on people’s lives is demonstrated today. Previous literature has shown that the use of a specific technology is directly linked to the individuals’ intention to use it. The aim of this paper is to study the factors that determine the adoption and use of artificial intelligence and big data in Spain, using a research model based on the Unified Theory of Acceptance and Use of Technology (UTAUT), proposed by Venkatesh et al. (2003). This work addresses the specific gap in the validation of the original theoretical model of UTAUT in two dimensions, with respect to the adoption of artificial intelligence by citizens and with respect to the factors that influence this adoption, evaluating the previous ones and proposing some new ones considering the current context. The methodology used is based on a national survey, and it analyzes the research model using the statistical technique of Partial Least Squares Structural Equation Modelling (PLS-SEM), which details the mediating and moderating relationships between constructs. The results show that Intention to Use has a direct positive influence on the Use of artificial Intelligence and big data, confirming previous literature. Performance Expectancy is the strongest predictor of Intention to Use, and indirectly of the adoption of artificial intelligence and big data applications. Effort Expectancy, in its application to the adoption of AI and big data by citizens, is an indirect determinant mediated by the Intention to Use, but its total effect (direct + indirect) is not significant.

A wide variety of enterprises, corporations, communications service providers (CSPs), and experts have highlighted the difficulty of managing modern networks. These networks exhibit high-impact technological innovations, such as cloud computing, mobility, new traffic profiles, network functions virtualization (NFV), the Internet of things (IoT), Big Data, among others. Network automation is a methodology in which physical and virtual network devices are automatically configured, provisioned, managed, and tested using software. Large enterprises such as Cisco, Juniper, Red Hat, and VMWare offer proprietary solutions for network automation. Additionally, the number of tools assisting in network automation has recently increased. Taken together, these developments have changed the way administrators build and manage networks. In this regard, most large communications operators are now working and moving toward truly autonomous networks that will eventually require an intensive use of Artificial Intelligence (AI). Advances in the area show that three specific segments —CSPs, Cloud Providers, and Enterprises— are all at different stages of automation maturity. Over time, network automation is expected to reach smaller organizations as well. This paper presents a specialized, detailed and current technical study on the state of the art in network automation, highlighting the trends observed in information technology (IT) environments, enterprises and communications operators —which are closely involved in this technology—, and concludes with a discussion on automation tools.

In his novel, Machines Like Me (2019), Ian McEwan offers an interesting example of “alternate history” while dealing with crucial ethical issues connected with the development of Artificial Intelligence. Instead of setting his story in the future, the author chooses to set it in the past, but he radically changes the contours of the latter. Hence, the England of the early 1980s is turned into a technologically advanced society, well ahead of the scientific progress of the early 21st century. Thus, the future casts its light on the past in what appears as a typically postmodernist mélange: besides mingling genres (from speculative fiction to uchronia), McEwan also performs an intriguing hybridization of fact and fiction. The paper intends to explore the rich historical dimension of the novel, which betrays the author’s interest in the reflection on history and on its narrativization – as well as its manipulation and/or contamination – within the literary text.

This article paper explores the evaluation of artificial intelligence (AI) in English as a Foreign Language (EFL) writing courses and the importance of calibration in writing evaluations. The role of calibration has received little attention in language contexts, while the role of artificial intelligence has gained increased attention in the last couple of years. This investigation, conducted from August 2022 to March 2023, involved eight TESOL students enrolled in an English as a Foreign Language (EFL) major at a Costa Rican public university, ten TESOL university professors, and one AI piece of software. It used a quantitative, quasi-experimental design, and a language elicitation data collection process. Data was collected by means of a rubric-based writing assessment. Quantitative data were analyzed using descriptive statistics. Data analyses indicate that: 1) human-created paragraphs (X̄ = 7,56) and AI writing (X̄ = 7,61) yield similar results when evaluated; 2) some criteria may favor human creativity or computer, rule-oriented writing; and 3) professors’ ratings reveal inconsistencies when grading human writing in particular. These findings demonstrate that AI matches, at least to a basic level, human writing skills. Furthermore, data show that students may be falling behind in aspects such as grammar, vocabulary, and mechanics. Finally, the analysis indicates that professors’ grading lacks consistency, and a calibration model should be incorporated as part of regular training workshops.

This article is both an editorial introduction to the guest-edited special issue of JoSTrans on Translation Automation and Sustainability, and a position paper in which we propose a model for evaluating the sustainable use of automation technology in translation and beyond. As grounding notions, the article reviews definitions of automation and considers the urgency of sustainability. Thereafter we propose an adaptation of Elkington’s (1997) triple bottom line, giving equal weight to evaluation based on people, planet, and performance, describing each of these elements in turn. Finally, we introduce the articles from this special issue, in which authors describe various aspects of automation technology in translation with a focus on sustainability.

Modern agricultural extension services help as a source of information for farmer queries. One of its applications are local hot lines where expert agents in specific crops or fields assist in farmer agricultural practices and decisions. As an already established technology in the field of customer services, conversational agents can help this solution by covering for experts when users have difficulties contacting them. These artificial agents can answer general queries at any hour, increasing the extension service accessibility. The creation of a contextualized solution is possible with the advancements of Natural Language Processing (NLP) and its accessibility in cloud services. We write this paper to collect state-of-the-art research on agricultural conversational agents and tools used for its design and deployment. General knowledge on current applications is gather and can later be used to help in the design of a localized solution when agricultural services are difficult to access. Lastly, we describe and analyze a chatbot prototype in the specific field of banana farming using IBM Watson services and the messaging platform Telegram App.

The significant challenge faced by medical schools is the effortful process of writing a high quantity of high-quality case-based multiple-choice questions (MCQs) to assess the higher-order skills of medical students. The demand for a high volume of MCQs in education has led to the development of Automatic Item Generation (AIG), specifically template-based AIG, which involves creating cognitive and item models by subject matter experts to generate hundreds of MCQs at once using software. It demonstrated significant success in various languages and even being incorporated into national medical licensure exams. However, this method still heavily depends on the efforts of subject matter experts. This paper introduces a detailed ChatGPT prompt for quickly generating case-based MCQs and provides important research questions for future exploration into ChatGPT's potential in generating items, signaling the beginning of the artificial intelligence era in medical education, encouraging health professions education researchers to delve deeper into its potential.

In the era of Web 3, digital currencies and virtual cities, human decision-making is very special. In It´s crucial to examine human responses alongside artificial intelligence in the healthcare field following an event and to create a collaborative geographic system based on modern technology. The ultimate goal is the restoration of countries´ essential services prioritizing health. In this research, spatial questions were conducted by considering public opinion, stakeholders, and decision makers under varying mental and emotional conditions. additionally, two different statistical and ranking methods were employed to comprehend the intricacies of individuals' mental states in a mathematical environment. All these methods were executed using software designed for location-based decision making under equal conditions. This paper focuses on a specific region, as an example applicable to a country or even to a larger scale. The results showed that time factors are completely related to decision criteria. While emerging technologies are promising, complete reliance on artificial intelligence for decision-making is misguided. Human choices are intrinsic to decision-making, and therefore, all relevant criteria for spatial decision-making have been considered. This pioneering study, conducted for the first time, showed that human choices can be optimal in different situations with similar conditions. Meanwhile, artificial intelligence only makes logical decisions that are not compatible with human thinking. The ongoing research holds potential value for neurologists or mental health specialists emphasizing the significance of geographical sciences in urban development. While it´s conceivable that medical issues and events can be addressed with artificial intelligence it appears that at least for the next few decades, even with the advancement of artificial intelligence, human presence remains essential in healthcare decision-making.

This paper reports the pedagogical approach and outcomes of a series of academic development programmes organised between 2016 and 2022 in different countries, which are grounded in the ethos of open educational practices, critical thinking, citizenship and pedagogy as well as ideas around social justice, data justice and data ethics using Open Data as open educational resources, to enable critical reflections and practical exercises with academics from different regions. Our recommendations and conclusions provide practical advice promoting a dialogue between different stakeholders to facilitate the development of curricula, workshops and resources using an open model for academic development.