10 results
Search Results
2. The Challenges of Algorithm Management: The Spanish Perspective.
- Author
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Prado, Daniel Perez del
- Subjects
ALGORITHMS ,LABOR laws ,DISRUPTIVE innovations ,ARTIFICIAL intelligence ,DIGITAL technology - Abstract
This paper focuses on how Spain's labour and employment law is dealing with technological disruption and, particularly, with algorithm management, looking for a harmonious equilibrium between traditional structures and profound changes. It pays special attention to the different actors affected and the most recent normative changes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
3. Bibliometric and Content Analysis of the Scientific Work on Artificial Intelligence in Journalism.
- Author
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Sonni, Alem Febri, Putri, Vinanda Cinta Cendekia, and Irwanto, Irwanto
- Subjects
ARTIFICIAL intelligence ,BIBLIOMETRICS ,CITATION indexes ,CONTENT analysis ,JOURNALISM ,FAKE news - Abstract
This paper presents a comprehensive bibliometric review of the development of artificial intelligence (AI) in journalism based on the analysis of 331 articles indexed in the Scopus database between 2019 and 2023. This research combines bibliometric approaches and quantitative content analysis to provide an in-depth conceptual and structural overview of the field. In addition to descriptive measures, co-citation and co-word analyses are also presented to reveal patterns and trends in AI- and journalism-related research. The results show a significant increase in the number of articles published each year, with the largest contributions coming from the United States, Spain, and the United Kingdom, serving as the most productive countries. Terms such as "fake news", "algorithms", and "automated journalism" frequently appear in the reviewed articles, reflecting the main topics of concern in this field. Furthermore, ethical aspects of journalism were highlighted in every discussion, indicating a new paradigm that needs to be considered for the future development of journalism studies and professionalism. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
4. An AI-based multiphase framework for improving the mechanical ventilation availability in emergency departments during respiratory disease seasons: a case study.
- Author
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Ortiz-Barrios, Miguel, Petrillo, Antonella, Arias-Fonseca, Sebastián, McClean, Sally, de Felice, Fabio, Nugent, Chris, and Uribe-López, Sheyla-Ariany
- Subjects
TREATMENT of respiratory diseases ,COMPUTER simulation ,RANDOM forest algorithms ,PREDICTIVE tests ,CROSS-sectional method ,RESEARCH funding ,RECEIVER operating characteristic curves ,ARTIFICIAL intelligence ,PROBABILITY theory ,HOSPITAL emergency services ,DECISION making ,ARTIFICIAL respiration ,EPIDEMICS ,QUALITY assurance ,CONFIDENCE intervals ,MECHANICAL ventilators ,SENSITIVITY & specificity (Statistics) - Abstract
Background: Shortages of mechanical ventilation have become a constant problem in Emergency Departments (EDs), thereby affecting the timely deployment of medical interventions that counteract the severe health complications experienced during respiratory disease seasons. It is then necessary to count on agile and robust methodological approaches predicting the expected demand loads to EDs while supporting the timely allocation of ventilators. In this paper, we propose an integration of Artificial Intelligence (AI) and Discrete-event Simulation (DES) to design effective interventions ensuring the high availability of ventilators for patients needing these devices. Methods: First, we applied Random Forest (RF) to estimate the mechanical ventilation probability of respiratory-affected patients entering the emergency wards. Second, we introduced the RF predictions into a DES model to diagnose the response of EDs in terms of mechanical ventilator availability. Lately, we pretested two different interventions suggested by decision-makers to address the scarcity of this resource. A case study in a European hospital group was used to validate the proposed methodology. Results: The number of patients in the training cohort was 734, while the test group comprised 315. The sensitivity of the AI model was 93.08% (95% confidence interval, [88.46 − 96.26%]), whilst the specificity was 85.45% [77.45 − 91.45%]. On the other hand, the positive and negative predictive values were 91.62% (86.75 − 95.13%) and 87.85% (80.12 − 93.36%). Also, the Receiver Operator Characteristic (ROC) curve plot was 95.00% (89.25 − 100%). Finally, the median waiting time for mechanical ventilation was decreased by 17.48% after implementing a new resource capacity strategy. Conclusions: Combining AI and DES helps healthcare decision-makers to elucidate interventions shortening the waiting times for mechanical ventilators in EDs during respiratory disease epidemics and pandemics. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
5. Adoption and use factors of artificial intelligence and big data by citizens.
- Author
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Sánchez-Holgado, Patricia and Arcila-Calderón, Carlos
- Subjects
ARTIFICIAL intelligence ,BIG data ,STRUCTURAL equation modeling ,INTENTION - Abstract
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. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
6. Artificial intelligence, disinformation and media literacy proposals around deepfakes.
- Author
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Garriga, Miriam, Ruiz-Incertis, Raquel, and Magallón-Rosa, Raúl
- Subjects
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DEEPFAKES , *ARTIFICIAL intelligence , *MEDIA literacy , *DISINFORMATION - Abstract
The role of artificial intelligence and its place in the new disinformation strategies is perhaps one of the most difficult issues to focus on nowadays, since we are at the beginning of a process of definition and ways of exploration. In this paper, first of all, we analyze the different approaches that are being applied to the regulation of artificial intelligence and that may affect the different disinformation strategies that are being identified. Secondly, we study how artificial intelligence is being used to identify disinformation content. In this regard, from the point of view of verification processes, one of the main challenges is when identifying deepfakes (images and video, mainly) linked to news cycles. From this perspective, a typology of deepfakes is proposed and its main characteristics will be described according to the verifications carried out by the Spanish fact-checking organizations. Finally, a set of recommendations will be presented to work from a media literacy point of view with the identification of deepfakes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
7. Lack of Transparency in Algorithmic Management of Workers and Trade Unions' Right to Information: European and Polish Perspectives.
- Author
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Stefański, Krzysztof and Żywolewska, Katarzyna
- Subjects
PERSONNEL management ,EMPLOYEE rights ,ARTIFICIAL intelligence ,SELF-efficacy - Abstract
The 'black box issue' is one of the biggest problems with algorithmic management. The lack of transparency in the operation and decision-making of AI is of greatest concern to those whose data is being processed (including employees). Trade unions, as the organisations that most represent the interests of workers, can play a big role here; however, they need to be empowered. There is a lack of legislation at EU and Member State level to set norms for this issue; the only country that has already introduced such legislation is Spain. The draft Polish regulation refers to the Spanish solutions and seems to be very interesting. It introduces the possibility for trade unions to obtain data from an employer on the operation of AI in relation to the algorithmic management of employees. The authors present this regulation against the background of EU recommendations and previous Polish legislation on the employer's obligation to provide information. They also identify elements that need to be refined during the parliamentary process in order to make the regulation more effective in protecting workers' rights. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
8. The Technological Impact on Employment in Spain between 2023 and 2035.
- Author
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Chemlal, Oussama and Benomar, Wafaa
- Subjects
LABOR supply ,LABOR demand ,EMPLOYMENT ,LAYOFFS ,TECHNOLOGICAL progress - Abstract
The objective of this work is to predict the impact of technology on employment demand by profession in Spain between 2023 and 2035. The evaluation of this effect involved the comparison of two scenarios: a trend scenario obtained by predicting the evolution of occupations in demand and a technological scenario anticipated in the case of technological progress. To accomplish this goal, a new approach was developed in the present study based on previous research. Thus, we estimated the proportion of jobs likely to be automated using a task-based approach. Each occupation was examined based on its components to determine the degree to which these tasks could be automated. The results suggest that technology may influence job demand but with low percentages (between 3% and 5% for both low- and high-qualified workers) in the long term. However, job losses are greater in absolute difference in low-skilled professions, where a great share of the labor force is engaged. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
9. Driving Behaviour Estimation System Considering the Effect of Road Geometry by Means of Deep NN and Hotelling Transform.
- Author
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Barreno, Felipe, Santos, Matilde, and Romana, Manuel
- Subjects
MOTOR vehicle driving ,CONVOLUTIONAL neural networks ,ARTIFICIAL intelligence ,AGGRESSIVE driving ,DISTRACTED driving ,HYBRID systems - Abstract
In this work, an intelligent hybrid model is proposed to identify hazardous or inattentive driving manoeuvres on roads, with the final goal being to increase and ensure travellers' safety and comfort. The estimation is based on the effects that road geometry may have on vehicle accelerations, displacements and dynamics. The outputs of the intelligent systems proposed are how the type of driving can be characterized as normal, careless or distracted. The intelligent system consists of an LSTM (Long Short-Term Memory) neural network in a first step that distinguishes between normal and abnormal driving behaviour and then a second module that classifies abnormal forms of driving as aggressive or inattentive, with the latter implemented with another LSTM, a CNN (convolutional neural network) or the Hotelling transform. They are applied to some of the characteristics of vehicle dynamics to estimate the driving behaviour. Smartphone inertial sensors such as GPS, accelerometers and gyroscopes are used to measure these vehicle characteristics and to identify driving events in manoeuvres. Specifically, the critical acceleration due to the influence of the road geometry can be measured with inertial sensors, and then, this road acceleration with the lateral acceleration allows us to estimate the driver's perceived acceleration. This perceived acceleration affects the driving style and, consequently, the estimation of the appropriate speed to travel on that road. There is use of both a traditional two-lane and a motorway route located in the Madrid region of Spain. Driving behaviour is determined by considering how changes in road geometry may affect one's driving style and, consequently, the estimation of the proper speed. The results obtained with some of the proposed configurations of the intelligent hybrid system reach an accuracy of 97.21% in detecting dangerous driving or driving with a certain risk. This could allow generating real-time alerts for potentially dangerous or inattentive manoeuvres, leading to safer and more appropriate driving. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
10. ARTIFICIAL INTELLIGENCE IN JOURNALISM: AN AUTOMATED NEWS PROVIDER.
- Author
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Parratt Fernández, Sonia, Rodríguez-Pallares, Miriam, and Pérez-Serrano, María José
- Subjects
ARTIFICIAL intelligence ,FREEDOM of the press ,JOURNALISM ,FINANCIAL crises - Abstract
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- Published
- 2024
- Full Text
- View/download PDF
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