Search

Large language models and generative AI, such as ChatGPT, have gained influence over people's personal lives and work since their launch, and are expected to scale even further. While the promises of generative artificial intelligence are compelling, this technology harbors significant biases, including those related to gender. Gender biases create patterns of behavior and stereotypes that put women, men and gender-diverse people at a disadvantage. Gender inequalities and injustices affect society as a whole. As a social practice, gendering is achieved through the repeated citation of rituals, expectations and norms. Shared understandings are often captured in scripts, including those emerging in and from generative AI, which means that gendered views and gender biases get grafted back into social, political and economic life. This paper's central argument is that large language models work performatively, which means that they perpetuate and perhaps even amplify old and non-inclusive understandings of gender. Examples from ChatGPT are used here to illustrate some gender biases in AI. However, this paper also puts forward that AI can work to mitigate biases and act to 'undo gender'. [ABSTRACT FROM AUTHOR]

AI predictive tools for migration management in the humanitarian field can significantly aid humanitarian actors in augmenting their decision-making capabilities and improving the lives and well-being of migrants. However, the use of AI predictive tools for migration management also poses several risks. Making humanitarian responses more effective using AI predictive tools cannot come at the expense of jeopardizing migrants' rights, needs, and interests. Against this backdrop, embedding AI ethical principles into AI predictive tools for migration management becomes paramount. AI ethical principles must be imbued in the design, development, and deployment stages of these AI predictive tools to mitigate risks. Current guidelines to apply AI ethical frameworks contain high-level ethical principles which are not sufficiently specified for achievement. For AI ethical principles to have real impact, they must be translated into low-level technical and organizational measures to be adopted by those designing and developing AI tools. The context-specificity of AI tools implies that different contexts raise different ethical challenges to be considered. Therefore, the problem of how to operationalize AI ethical principles in AI predictive tools for migration management in the humanitarian field remains unresolved. To this end, eight ethical requirements are presented, with their corresponding safeguards to be implemented at the design and development stages of AI predictive tools for humanitarian action, with the aim of operationalizing AI ethical principles and mitigating the inherent risks. [ABSTRACT FROM AUTHOR]

The wide scale adoption of Artificial Intelligence (AI) will require that AI engineers and developers can provide assurances to the user base that an algorithm will perform as intended and without failure. Assurance is the safety valve for reliable, dependable, explainable, and fair intelligent systems. AI assurance provides the necessary tools to enable AI adoption into applications, software, hardware, and complex systems. AI assurance involves quantifying capabilities and associating risks across deployments including: data quality to include inherent biases, algorithm performance, statistical errors, and algorithm trustworthiness and security. Data, algorithmic, and context/domain-specific factors may change over time and impact the ability of AI systems in delivering accurate outcomes. In this paper, we discuss the importance and different angles of AI assurance, and present a general framework that addresses its challenges. [ABSTRACT FROM AUTHOR]

Back in 2004, Google Inc. (Menlo Park, CA, USA) began digitizing full texts of magazines, journals, and books dating back centuries. At present, over 25 million books have been scanned and anyone can use the service (currently called Google Books) to search for materials free of charge (including academics of any discipline). All the books have been scanned, converted to text using optical character recognition and stored in its digital database. The present paper describes a very precise six-stage Boolean date-specific research method on Google, referred to as Internet Date Detection (IDD) for short. IDD can be used to examine countless alleged facts and myths in a systematic and verifiable way. Six examples of the IDD method in action are provided (the terms, words, and names ‘self-fulfilling prophecy’, ‘Humpty Dumpty’, ‘living fossil’, ‘moral panic’, ‘boredom’, and ‘selfish gene’) and each of these examples is shown to disconfirm widely accepted expert knowledge belief claims about their history of coinage, conception, and published origin. The paper also notes that Google’s autonomous deep learning AI program RankBrain has possibly caused the IDD method to no longer work so well, addresses how it might be recovered, and how such problems might be avoided in the future. [ABSTRACT FROM AUTHOR]

AI has the potential to revolutionize mental health services by providing personalized support and improving accessibility. However, it is crucial to address ethical concerns to ensure responsible and beneficial outcomes for individuals. This systematic review examines the ethical considerations surrounding the implementation and impact of artificial intelligence (AI) interventions in the field of mental health and well-being. To ensure a comprehensive analysis, we employed a structured search strategy across top academic databases, including PubMed, PsycINFO, Web of Science, and Scopus. The search scope encompassed articles published from 2014 to 2024, resulting in a review of 51 relevant articles. The review identifies 18 key ethical considerations, including 6 ethical considerations associated with using AI interventions in mental health and wellbeing (privacy and confidentiality, informed consent, bias and fairness, transparency and accountability, autonomy and human agency, and safety and efficacy); 5 ethical principles associated with the development and implementation of AI technologies in mental health settings to ensure responsible practice and positive outcomes (ethical framework, stakeholder engagement, ethical review, bias mitigation, and continuous evaluation and improvement); and 7 practices, guidelines, and recommendations for promoting the ethical use of AI in mental health interventions (adhere to ethical guidelines, ensure transparency, prioritize data privacy and security, mitigate bias and ensure fairness, involve stakeholders, conduct regular ethical reviews, and monitor and evaluate outcomes). This systematic review highlights the importance of ethical considerations in the responsible implementation and impact of AI interventions for mental health and well-being. By addressing privacy, bias, consent, transparency, human oversight, and continuous evaluation, we can ensure that AI interventions like chatbots and AI-enabled medical devices are developed and deployed in an ethically sound manner, respecting individual rights, promoting fairness, and maximizing benefits while minimizing potential harm. [ABSTRACT FROM AUTHOR]

This study analyses the dimensions of trust in artificial intelligence (AI), focusing on why a significant portion of the UK population demonstrates a higher level of trust in AI compared to humans. Conducted through a mixed-methods approach, this study gathered 894 responses, with 451 meeting the criteria for analysis. It utilised a combination of a six-step Likert-scale survey and open-ended questions to explore the psychological, sociocultural, and technological facets of trust. The analysis was underpinned by structural equation modelling (SEM) and correlation techniques. The results unveil a strong predilection for trusting AI, mainly due to its perceived impartiality and accuracy, which participants likened to conventional computing systems. This preference starkly contrasts with the scepticism towards human reliability, which is influenced by the perception of inherent self-interest and dishonesty in humans, further exacerbated by a general distrust in media narratives. Additionally, this study highlights a significant correlation between distrust in AI and an unwavering confidence in human judgment, illustrating a dichotomy in trust orientations. This investigation illuminates the complex dynamics of trust in the era of digital technology, making a significant contribution to the ongoing discourse on AI's societal integration and underscoring vital considerations for future AI development and policymaking. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI)-based generative imaging systems such as DALL·E, Midjourney, Stable Diffusion, and Adobe Firefly, which work by transforming natural language descriptions into images, are revolutionizing computer vision. In this exploratory and qualitative research, we have replicated requests for images of women in different professions by comparing these representations in previous studies with DALL·E, observing that this model continues to provide in its last version, DALL·E 3, inequitable results in terms of gender. In addition, Bing Image Creator, Microsoft's free tool that is widely used among the population and runs under DALL·E, has been tested for the first time. It also presents a sexualization of women and stereotypical children's representations. The results reveal the following: 1. A slight improvement in terms of the presence of women in professions previously shown only with men. 2. They continue to offer biased results in terms of the objectification of women by showing sexualized women. 3. The representation of children highlights another level of gender bias, reinforcing traditional stereotypes associated with gender roles from childhood, which can impact future decisions regarding studies and occupations. [ABSTRACT FROM AUTHOR]

Political bots, through astroturfing and other strategies, have become important players in recent elections in several countries. This study aims to provide researchers and the citizenry with the necessary knowledge to design strategies to identify bots and counteract what international organizations have deemed bots' harmful effects on democracy and, simultaneously, improve automatic detection of them. This study is based on two innovative methodological approaches: (1) dealing with bots using hybrid intelligence (HI), a multidisciplinary perspective that combines artificial intelligence (AI), natural language processing, political science, and communication science, and (2) applying framing theory to political bots. This paper contributes to the literature in the field by (a) applying framing to the analysis of political bots, (b) defining characteristics to identify signs of automation in Spanish, (c) building a Spanish-language bot database, (d) developing a specific classifier for Spanish-language accounts, (e) using HI to detect bots, and (f) developing tools that enable the everyday citizen to identify political bots through framing. [ABSTRACT FROM AUTHOR]

Digitalization, robotization, artificial intelligence, and all kinds of new technologies that are known as Industry 4.0 or the fourth industrial revolution have great influence on the future of work because they will gather new jobs with new skills, and a majority of the senior workforce will probably have a lot of problems with those kinds of changes and challenges. The major objective of the paper is to recognize the dependence of the unemployment of the age category 55–64 upon selected explanatory variables. The explanatory variables were selected, and the expectations of their signs were presented in the research design. The secondary data of Eurostat and OECD 2015 has been used, covering the twenty-two member countries of the European Union (the countries that provided minimum wage were included only). The econometric analysis, specifically model specification and model quantification were the main methods used in the paper. The main outcomes and relevance of the model as well as its limitations have been compared with the findings of other authors in the discussion and implications for further research. [ABSTRACT FROM AUTHOR]

This research endeavours to systematically investigate the multifaceted domain of AI literacy, given the pervasive impact of artificial intelligence on diverse facets of contemporary human existence. The inquiry is motivated by a fundamental question posed to educators: how best to cultivate AI literacies and competencies and how these proficiencies are structured and influenced. Employing a rigorous two-part methodology, the initial phase scrutinises 28 studies from the SCOPUS database, unveiling five distinct discourses germane to AI literacy. Subsequently, the second phase involves the administration of questionnaires to 73 students, whose responses undergo thematic analysis to discern patterns within the four domains delineated by Ng et al. The ensuing discourse underscores a pivotal revelation: despite formal adherence to established discourses, the conceptualisation of AI literacy necessitates a departure from conventional perspectives. Ethical principles, elucidated by students, emerge not merely as individual components but as integral facets of a broader societal literacy profile, thereby advocating a paradigm shift towards social reflection. This novel insight prompts a critical re-evaluation of AI literacy's prevailing assumptions and conceptual frameworks, urging a transition towards models grounded in ecological or network dynamic interactionist principles. [ABSTRACT FROM AUTHOR]

In the last decade, artificial intelligence has generated several challenges in societies, with a special focus on public administration. Through the development of this literature review, we intend to underline the challenges that this has caused in the realm of public affairs, especially in terms of the smart cities framework, considering the legal perspective that is intrinsically associated with it. In this way, we based our research on a wide range of articles, from which we considered those with the greatest relevance and the highest number of citations in order to substantiate this theme in a more precise way. Finally, we present a set of conclusions, as well as opportunities for future investigations. [ABSTRACT FROM AUTHOR]

The differentiation of contemporary approaches to qualitative data analysis can seem daunting even for experienced social science researchers. Especially when they move forward in the data analysis process from general analytical strategies used in qualitative research to more specific approaches for different types of qualitative data, including interviews, text, audio, images, videos, and so-called virtual data, by discovering the domain ontology of the qualitative research field, we see that there are more than twice as many different classes of data analysis methods as qualitative research methods. This article critically reflects on qualitative research and the qualitative computer data analysis process, emphasising its significance in harnessing digital opportunities and shaping collaborative work. Using our extensive analytical and research project experience, the last research results, and a literature review, we try to show the impact of new technologies and digital possibilities on our thinking. We also try to do the qualitative data analysis. The essence of this procedure is a dialectical interplay between the new world of digital technology and the classic methodology. The use of digital possibilities in qualitative research practices shapes the researcher's identity and their analytical and research workshop. Moreover, it teaches collaborative thinking and teamwork and fosters the development of new analytical, digital, and Information Technology (IT) skills. Imagining contemporary qualitative research and data analysis in the humanities and social sciences is difficult. Opening to modern technologies in computer-based qualitative data analysis shapes our interpretation frameworks and changes the optics and perception of research problems. [ABSTRACT FROM AUTHOR]

In this comprehensive study, insights from 1389 scholars across the US, UK, Germany, and Switzerland shed light on the multifaceted perceptions of artificial intelligence (AI). AI's burgeoning integration into everyday life promises enhanced efficiency and innovation. The Trustworthy AI principles by the European Commission, emphasising data safeguarding, security, and judicious governance, serve as the linchpin for AI's widespread acceptance. A correlation emerged between societal interpretations of AI's impact and elements like trustworthiness, associated risks, and usage/acceptance. Those discerning AI's threats often view its prospective outcomes pessimistically, while proponents recognise its transformative potential. These inclinations resonate with trust and AI's perceived singularity. Consequently, factors such as trust, application breadth, and perceived vulnerabilities shape public consensus, depicting AI as humanity's boon or bane. The study also accentuates the public's divergent views on AI's evolution, underlining the malleability of opinions amidst polarising narratives. [ABSTRACT FROM AUTHOR]

This study examined the impact of Twitter usage development in crisis communication in Türkiye during the 6 February 2023 by showing the development of its use during the 1999 Izmit and 2000 Izmir earthquakes. As well as its usage in the 48 h following the 2023 earthquake. It found that Twitter's positive determinism has evolved over time from gathering information to actively supporting victims' rescue. Twitter was crucial for finding casualties and providing on-the-ground updates during critical moments, confirming the media's surveillance function. During the first 48 h of the 2023 earthquake, Twitter significantly affected the rescue and relief activities, enabling individuals trapped beneath the debris to contact, seek, and receive assistance. Twitter's importance has increased in political communication by opinion leaders and government authorities, and President Erdoğan's engagement via Twitter was critical in expressing solidarity and coordinating rescue and relief efforts. This study concluded that Twitter has become an indispensable tool for obtaining and disseminating information, as well as aiding and identifying individuals in need. It was widely used by official accounts, informational accounts, and citizens, and effectively aiding rescue and relief efforts, especially in the first 48 h after the disaster. [ABSTRACT FROM AUTHOR]

Disinformation does not always take the form of a fake news item, it also appears in much less evident formats which are subtly filtered into public opinion, thus making its detection more difficult. A method is proposed in this paper to address the study of "widespread" disinformation by combining social science methods with artificial intelligence and text mining. The case study chosen was the expression "right of self-determination" as a generator of disinformation within the context of the Catalan independence process. The main work hypothesis was that the (intentional or unintentional) confusion around the meaning and scope of this right has become widely extended within the population, generating negative emotions which favour social polarisation. The method utilised had three stages: (1) Description of the disinformation elements surrounding the term with the help of experts; (2) Detection of these elements within a corpus of tweets; (3) Identification of the emotions expressed in the corpus. The results show that the disinformation described by experts clearly dominates the conversation about "self-determination" on Twitter and is associated with a highly negative emotional load in which contempt, hatred, and frustration prevail. [ABSTRACT FROM AUTHOR]

The current crisis of participation and crisis of engagement of Western societies also affects the application and the validity of the participatory design methodology. Traditional techniques to collaboratively design future solutions with the users and bring their knowledge to the technology application might not no longer be sufficient for the complex nature of our societies. This paper describes the applied research and design of a Digital Companion with AI-based profiling, needs matching, and service-access supporting chatbots. The objective of the Digital Companion is to enhance both the effectiveness of the services currently provided to migrants and refugees by local public administration and organizations, and the life quality of the migrants themselves. The adoption of participatory, iterative, and experimental co-creation approaches allowed to contribute to the innovation of the participatory design framework at a theoretical and methodological level, as is required in order to turn participation into action, to go beyond the mere public consultation and to find new pathways for involving all the citizens (not only migrants or local service providers) as a first step to build a successful project. [ABSTRACT FROM AUTHOR]

Research Aims. This research project investigates what are the major benefits and risks of Chinese students using ChatGPT for academic activities. Also, the project assesses how, if applicable, should ChatGPT be regulated in Chinese academic settings in order to maintain academic integrity and ethical standards. Methodology. The collection of primary data from relevant newspaper articles serves as the foundation of this research project. Here, the content analysis is used for primary data collection. A combination of keywords ["ChatGPT" AND ("China" OR "Chinese") AND ("students" OR "student")] were typed on the Google news search engine on 12 April 2023. A sum of 40 newspaper articles were deemed eligible for data analysis. Both qualitative and quantitative data were extracted and analyzed. Findings. The opinion of using ChatGPT to fulfil academic responsibilities has been polarized in China. The conservative camps worry that students are using ChatGPT to commit academic cheating. However, some Chinese educators believe AI-powered technologies should be incorporated into academic learning as AI-enabled writing tools can help improve the quality of academic outputs. A major concern that Chinese educators hold, to date, is plagiarism violations by students as an act of academic cheating. Most newspaper articles presented the use of ChatGPT in Chinese academic settings neutrally. Newspaper articles published in March 2023 contained more positive and negative word(s) about the use of ChatGPT in academic learning. Conclusions. Given the benefits ChatGPT can provide and the near-infeasibility of massively ban the use of AI-powered software, more regulations should be set up in Chinese academia. Teachers have to guide students on how to fact-check the details provided by AI and add citations and references accordingly in their coursework. Moreover, teachers should guide students on how to ask AI-powered software questions systematically and creatively, in order to maximize the intellectual outputs generated from ChatGPT. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the Adaptive Learning Framework (Alef) platform and determine how parents perceive the implementation of such a program to support their children's learning. Alef is a smart learning program that is mandated in United Arab Emirates (UAE) public schools to promote student-centered, interactive, and differentiated learning and personalized experiences. The participants were parents of students enrolled in grades 9–12 in UAE public high schools. The study used semi-structured interviews to gather qualitative data to delve deeply into parents' perceptions of how Alef supports their children's learning. The results showed that Alef offers stimulating and engaging educational experiences and encourages independent learning. It was found that students' learning was bolstered when using Alef. In addition, the results indicated the existence of some challenges stemming from the usage of Alef that could have an impact on students' learning and motivation and, ultimately, the sustainability of such a program. Recommendations are provided to overcome these challenges. [ABSTRACT FROM AUTHOR]

In recent years, the use of Artificial Intelligence agents to augment and enhance the operational decision making of human agents has increased. This has delivered real benefits in terms of improved service quality, delivery of more personalised services, reduction in processing time, and more efficient allocation of resources, amongst others. However, it has also raised issues which have real-world ethical implications such as recommending different credit outcomes for individuals who have an identical financial profile but different characteristics (e.g., gender, race). The popular press has highlighted several high-profile cases of algorithmic discrimination and the issue has gained traction. While both the fields of ethical decision making and Explainable AI (XAI) have been extensively researched, as yet we are not aware of any studies which have examined the process of ethical decision making with Intelligence augmentation (IA). We aim to address that gap with this study. We amalgamate the literature in both fields of research and propose, but not attempt to validate empirically, propositions and belief statements based on the synthesis of the existing literature, observation, logic, and empirical analogy. We aim to test these propositions in future studies. [ABSTRACT FROM AUTHOR]

The article aims to provide a comparative analysis of determining the legal status of artificial intelligence, as well as strategic planning of its implementation in the public sector in the countries of the Romano-Germanic, Anglo-Saxon, socialist, religious, and traditional systems of law. The study replies to the research questions regarding statutory definition of AI, state authorities responsible for AI, national government strategy in the field of AI and targets set therein, and action plans of AI with reference to countries with the highest Global Talent Competitiveness Index in reference to the mentioned legal systems. The research is of qualitative and applied nature; theoretical analysis of academic sources provides the groundwork for ICT-facilitated thematic content analysis of legal and administrative documents of the mentioned countries. The findings reveal common and specific trends regarding the data under study, and allow the author to suggest a revision of AI definition and to specify legislative and doctrinal issues that seem to be relevant and promising in the further strategic development and implementation of AI in the public sphere across countries. [ABSTRACT FROM AUTHOR]

Recent advancements in Large Language Models (LLMs) suggest imminent commercial applications of such AI systems where they will serve as gateways to interact with technology and the accumulated body of human knowledge. The possibility of political biases embedded in these models raises concerns about their potential misusage. In this work, we report the results of administering 15 different political orientation tests (14 in English, 1 in Spanish) to a state-of-the-art Large Language Model, the popular ChatGPT from OpenAI. The results are consistent across tests; 14 of the 15 instruments diagnose ChatGPT answers to their questions as manifesting a preference for left-leaning viewpoints. When asked explicitly about its political preferences, ChatGPT often claims to hold no political opinions and to just strive to provide factual and neutral information. It is desirable that public facing artificial intelligence systems provide accurate and factual information about empirically verifiable issues, but such systems should strive for political neutrality on largely normative questions for which there is no straightforward way to empirically validate a viewpoint. Thus, ethical AI systems should present users with balanced arguments on the issue at hand and avoid claiming neutrality while displaying clear signs of political bias in their content. [ABSTRACT FROM AUTHOR]

Following the large-scale 2015–2016 migration crisis that shook Europe, deploying big data and social media harvesting methods became gradually popular in mass forced migration monitoring. These methods have focused on producing 'real-time' inferences and predictions on individual and social behavioral, preferential, and cognitive patterns of human mobility. Although the volume of such data has improved rapidly due to social media and remote sensing technologies, they have also produced biased, flawed, or otherwise invasive results that made migrants' lives more difficult in transit. This review article explores the recent debate on the use of social media data to train machine learning classifiers and modify thresholds to help algorithmic systems monitor and predict violence and forced migration. Ultimately, it identifies and dissects five prevalent explanations in the literature on limitations for the use of such data for A.I. forecasting, namely 'policy-engineering mismatch', 'accessibility/comprehensibility', 'legal/legislative legitimacy', 'poor data cleaning', and 'difficulty of troubleshooting'. From this review, the article suggests anonymization, distributed responsibility, and 'right to reasonable inferences' debates as potential solutions and next research steps to remedy these problems. [ABSTRACT FROM AUTHOR]

As the number of migrants arriving in Europe increases, host societies face the challenge of supporting their smooth integration, respecting their needs and recognizing their competencies. A key element for their new life is their integration in the labour market. This paper presents a platform which offers a set of tools that has been developed to support migrants to find their way into the labour market in EU countries. This set includes tools for skill assessment, artificial intelligence tools providing recommendations for jobs that match their personal skills and needs, tools for suggesting training paths and options to empower their candidacy, and easy-to-use tools for creating their CV/portfolio. We focus on the evaluation of this platform in real life settings in two countries (Greece and Spain), which is part of our co-creation approach. The results are very promising and show the satisfaction of the migrants. Additionally, they provide valuable insights for both those that develop such tools and those that can use them in their work/activities with the migrants (such as the non-governmental organisations and host authorities). [ABSTRACT FROM AUTHOR]

Smart Factory is a complex system that integrates the main elements of the Industry 4.0 concept (e.g., autonomous robots, Internet of Things, and Big data). In Smart Factories intelligent robots, tools, and smart workpieces communicate and collaborate with each other continuously, which results in self-organizing and self-optimizing production. The significance of Smart Factories is to make production more competitive, efficient, flexible and sustainable. The purpose of the study is not only the introduction of the concept and operation of the Smart Factories, but at the same time to show the application of Simulation and Artificial Intelligence (AI) methods in practice. The significance of the study is that the economic and social operational requirements and impacts of Smart Factories are summarized and the characteristics of the traditional factory and the Smart Factory are compared. The most significant added value of the research is that a real case study is introduced for Simulation of the operation of two collaborating robots applying AI. Quantitative research methods are used, such as numerical and graphical modeling and Simulation, 3D design, furthermore executing Tabu Search in the space of trajectories, but in some aspects the work included fundamental methods, like suggesting an original whip-lashing analog for designing robot trajectories. The conclusion of the case study is that—due to using Simulation and AI methods—the motion path of the robot arm is improved, resulting in more than five percent time-savings, which leads to a significant improvement in productivity. It can be concluded that the establishment of Smart Factories will be essential in the future and the application of Simulation and AI methods for collaborating robots are needed for efficient and optimal operation of production processes. [ABSTRACT FROM AUTHOR]

This study proposes a crime prediction model according to communes (areas or districts in which the city of Buenos Aires is divided). For this, the Python programming language is used, due to its versatility and wide availability of libraries oriented to Machine Learning. The crimes reported (period 2016–2019) that occurred in the city of Buenos Aires selected to test the model are: homicides, theft, injuries, and robberies. With this, it is possible to generate a crime prediction model according to the city area based on the SEMMA (Sample, Explore, Modify, Model, and Assess) model and after data manipulation, standardization and cleaning; clustering is performed using K-means and subsequently the neural network is generated. For prediction, it is necessary to provide the model with the information corresponding to the predictive characteristics (predict); these characteristics being according to the developed neural network model: year, month, day, time zone, commune, and type of crime. [ABSTRACT FROM AUTHOR]

In the last six decades, many advances have been made in the field of artificial intelligence (AI). Bearing in mind that AI technologies are influencing societies and political systems differently, it can be useful to understand what are the common issues between similar states in the European Union and how these political systems can collaborate with each other, seeking synergies, finding opportunities and saving costs. Therefore, we carried out an exploratory research among similar states of the European Union, in terms of scientific research in areas of AI technologies, namely: Portugal, Greece, Austria, Belgium and Sweden. A key finding of this research is that intelligent decision support systems (IDSS) are essential for the political decision-making process, since politics normally deals with complex and multifaceted decisions, which involve trade-offs between different stakeholders. As public health is becoming increasingly relevant in the field of the European Union, the IDSSs can provide relevant contributions, as it may allow sharing critical information and assist in the political decision-making process, especially in response to crisis situations. [ABSTRACT FROM AUTHOR]

Opinion mining and sentiment analysis has become ubiquitous in our society, with applications in online searching, computer vision, image understanding, artificial intelligence and marketing communications (MarCom). Within this context, opinion mining and sentiment analysis in marketing communications (OMSAMC) has a strong role in the development of the field by allowing us to understand whether people are satisfied or dissatisfied with our service or product in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To the best of our knowledge, there is no science mapping analysis covering the research about opinion mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work during the last two decades in this interdisciplinary area and to show trends that could be the basis for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer and InCites based on results from Web of Science (WoS). The results of this analysis show the evolution of the field, by highlighting the most notable authors, institutions, keywords, publications, countries, categories and journals. [ABSTRACT FROM AUTHOR]

The Government of Japan's "Society 5.0" initiative aims to create a cyber-physical society in which (among other things) citizens' daily lives will be enhanced through increasingly close collaboration with artificially intelligent systems. However, an apparent paradox lies at the heart of efforts to create a more "human-centered" society in which human beings will live alongside a proliferating array of increasingly autonomous social robots and embodied AI. This study seeks to investigate the presumed human-centeredness of Society 5.0 by comparing its makeup with that of earlier societies. By distinguishing "technological" and "non-technological" processes of posthumanization and applying a phenomenological anthropological model, this study demonstrates: (1) how the diverse types of human and non-human members expected to participate in Society 5.0 differ qualitatively from one another; (2) how the dynamics that will shape the membership of Society 5.0 can be conceptualized; and (3) how the anticipated membership of Society 5.0 differs from that of Societies 1.0 through 4.0. This study describes six categories of prospective human and non-human members of Society 5.0 and shows that all six have analogues in earlier societies, which suggests that social scientific analysis of past societies may shed unexpected light on the nature of Society 5.0. [ABSTRACT FROM AUTHOR]