Artificial Intelligence in the Social Science Area: Systematic Literature Review in Web of Science and Scopus DOI Creative Commons

Aurora Forteza-Martínez,

Nadia Alonso

Tripodos, Journal Year: 2024, Volume and Issue: 55, P. 07 - 07

Published: July 8, 2024

The evolution of technology is giving rise to new scenarios in communication, information access, and social relations. Particularly, artificial intelligence has a great impact on the current media ecosystem, including social, academic, communicative, health aspects, interpersonal relationships. This research aims study how reflected scientific production most relevant publications Social Sciences. To this end, systematic review literature published Spanish Web Science Scopus databases spanning from 2018 first three quarters 2023 was carried out, following standards PRISMA Statement (Preferred Reporting Items for Systematic Reviews Meta-Analyses). From an initial sample 159 articles, 109 were analysed after applying inclusion exclusion criteria. Results show that 2022 productive year, with Spain having highest number publications. Furthermore, field Law, predominance qualitative methodology. key themes benefits implenting (AI) its dangers threats.

Language: Английский

Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research DOI
Ahmed Zahlan, Ravi Prakash Ranjan, David Hayes

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 74, P. 102321 - 102321

Published: July 5, 2023

Language: Английский

Citations

64
Incidences of artificial intelligence in contemporary education DOI Open Access
José Ramón Sanabria Navarro, Yahilina Silveira Pérez, Digna Dionisia Pérez Bravo

et al.

Comunicar, Journal Year: 2023, Volume and Issue: 31(77)

Published: June 18, 2023

The term 'Artificial Intelligence' was coined in 1956 at a conference Dartmouth College and since then it has undergone constant development evolved radically. Prominent pioneers of the include John McCarthy, Marvin Minsky, Allen Newell, Herbert A. Simon. application AI education worldwide increased dramatically with its importance growing an increasing rate. objective this research is to bibliometrically analyze applications contemporary education. methodology includes Prisma articles three fundamental databases: Scopus (n=390), Mendeley (n=113), Science Direct (n=3,594). A total n=4,097 English Spanish were analyzed. systematic literature review recent works employed mixed approach using quantitative qualitative methods. It inferred by authors that revolutionizing offering personalized efficient solutions improve students’ learning. One main conclusions education, students are one groups most affected AI. Furthermore, human intelligence teachers plays role they adapt their methodologies leverage new technologies. Finally, worth noting decisions made schools universities support educational models based on technology. El término «Inteligencia Artificial» fue acuñado en una conferencia College, y desde entonces, este ha experimentado un desarrollo constante evolucionado de manera significativa. Algunos los pioneros más destacados incluyen Newell La aplicación la inteligencia artificial educación aumentado considerablemente nivel mundial dinámica era digital. objetivo investigación es analizar bibliométricamente las incidencias IA contemporánea. metodología contiene tres bases datos fundamentales (n=113) (n=3.594), para n=4.097 artículos idioma inglés español. revisión sistematizada literatura reciente tiene enfoque mixto, cuantitativos cualitativos empleando varios paradigmas función del objetivo, se obtiene que revolucionado educación, ofreciendo soluciones personalizadas eficientes mejorar el aprendizaje estudiantes. En principales conclusiones plantea términos teóricos mayor impacto están estudiantes como elemento principal Por otra parte, profesores juegan papel proceso través sus metodologías uso estas tecnologías. Así mismo currículos educacionales mediante toma decisiones colegios universidades apostando por nuevos modelos tecnológicos educativos.

Citations

53
Does artificial intelligence (AI) boost digital banking user satisfaction? Integration of expectation confirmation model and antecedents of artificial intelligence enabled digital banking DOI Creative Commons

Feras MI Alnaser,

Samar Rahi, Mahmoud Alghizzawi

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(8), P. e18930 - e18930

Published: Aug. 1, 2023

In the era disruptive technology emergence of artificial intelligence has fundamentally improved banking operations. The execution is no longer discretionary for financial institutions and now it considered an essential tool to meet customer expectations. Although enabled digital faster efficient effective however user acceptance driven by in its initial stages. Therefore, current study develops integrated research framework with expectation confirmation model examines satisfaction AI banking. Data were collected from through structured questionnaire. Overall, 320 respondents approached requested participate survey. return 251 valid responses received analyzed structural equation modeling. Findings indicate that jointly determined confirmation, perceived performance, trendiness, visual attractiveness, problem solving, customization, communication quality revealed substantial variance R^2 51.1% satisfaction. corporate reputation have shown considerable 48.3 Moreover, predictive power Q^2 0.449 predict 0.493 Concerning hypotheses relationships exogenous factors positive significant impact except trendiness customization. Practically, this suggested policy makers should pay attention improving which turn enhance boost user's confidence accept This original as integrates antecedents behavior towards

Language: Английский

Citations

40
Artificial intelligence in healthcare institutions: A systematic literature review on influencing factors DOI Creative Commons
Julia Stefanie Roppelt, Dominik K. Kanbach, Sascha Kraus

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 76, P. 102443 - 102443

Published: Dec. 9, 2023

The purpose of this review is integrating and contextualizing relevant literature on the factors influencing adoption AI in healthcare industry into a comprehensive framework. Health systems are considered fundamental to creating societal value. However, global health challenged by increasing number patients due population aging growing prevalence chronic diseases cancer. Meanwhile, United Nations calls for equal access healthcare, tackling costs, addressing resource constraints foster sustainable development societies. In context, artificial intelligence (AI) gaining attention as it constitutes promising technology address these burgeoning challenges. Despite opportunities, specifically fragmented across various research fields, lacking overview. It lacks theoretically grounded integrating, example, that influence institutions. Derived from multi-disciplinary systematic review, building 130 studies, we propose Adoption Healthcare Industry Model. This model encompasses five dimensions contextualizes them. We macro-economic, regulatory, technological readiness serve external antecedents whereas organizational individual constitute internal Our has implications acceptance related healthcare. Further, provide hands-on guidance providers, institutions, official bodies such governments leverage

Language: Английский

Citations

37
Machines that feel: behavioral determinants of attitude towards affect recognition technology—upgrading technology acceptance theory with the mindsponge model DOI Creative Commons
Peter Mantello, Tung Manh Ho, Minh‐Hoang Nguyen

et al.

Humanities and Social Sciences Communications, Journal Year: 2023, Volume and Issue: 10(1)

Published: July 19, 2023

Abstract The rise of emotional AI signals a new era in human-machine relations where intelligent machines not only feel but also feed on human emotions as statistical fodder with the goal reshaping our behavior. Unlike many smart technologies, emotion-recognition systems sense, monitor, harvest and analyze data extracted from person’s non-conscious or psycho-physical state, often without their knowledge consent. As far more invasive manner surveillance capitalism, technological adoption is problematized by myriad legal, ethical, cultural, scientific issues. To better understand behavioral factors determining an individual’s attitude towards this emerging technology, we first identify five major tensions that may impinge adoption. Second, extend Technological Acceptance Model (TAM) (Davis, 1989) model insights mindsponge information filtering (Vuong Napier, 2015) along quantitative affordances offered Bayesian computational approach. Our analysis was conducted based multi-national dataset surveying perceptions 1015 young adults (age 18–27) regarding applications socio-cultural characteristics such income, region, religiosity, home country politics. These are fed into multi-level models varying intercepts so can systematically measure compare effects various determinants attitudes respondents harvesting government private sector actors. Critically, study finds who familiar with, perceive utilities well rate themselves restrained heated arguments social media, less threatened practice both findings offer fertile platform for further exploration intersection between psychology, culture, technologies important policymakers wishing to ensure design regulation technology serve best interests society.

Language: Английский

Citations

32
Process safety 4.0: Artificial intelligence or intelligence augmentation for safer process operation? DOI Creative Commons
Rajeevan Arunthavanathan, Zaman Sajid, Md. Tanjin Amin

et al.

AIChE Journal, Journal Year: 2024, Volume and Issue: 70(7)

Published: May 15, 2024

Abstract The growth of artificial intelligence (AI) has allowed industries to automate and improve their efficiency in operations. Especially process industries, AI helps develop intelligent models tools proactively monitor predict equipment or system failures, minimize downtime, optimize maintenance schedules. With the advancements its ability perform tasks, there is a growing belief that may eventually replace humans. However, absence human involvement operations industry raises safety concerns. Therefore, should collaborate with humans rather than them processing facility This technology referred as augmentation (IA). article (i) presents detailed comparison between IA's potential systems, (ii) identifies feasibility using IA safety, (iii) risk associated implementation industries.

Language: Английский

Citations

13
Domesticating AI in medical diagnosis DOI Creative Commons
Robin Williams, Stuart Anderson, Kathrin Cresswell

et al.

Technology in Society, Journal Year: 2024, Volume and Issue: 76, P. 102469 - 102469

Published: Jan. 26, 2024

We consider the anticipated adoption of Artificial Intelligence (AI) in medical diagnosis. examine how seemingly compelling claims are tested as AI tools move into real-world settings and discuss analysts can develop effective understandings novel rapidly changing settings. Four case studies highlight challenges utilising diagnostic at differing stages their innovation journey. Two 'upstream' cases seeking to demonstrate practical applicability two 'downstream' focusing on roll out scaling more established applications. observed an unfolding uncoordinated process social learning capturing key moments: i) experiments create establish clinical potential tools; and, ii) attempts verify dependability while extending scale scope. Health professionals critically appraise tool performance, relying them selectively where results be demonstrably trusted, a de facto model responsible use. note shift from procuring stand-alone solutions deploying suites through platforms facilitate reduce costs procurement, implementation evaluation which impede viability solutions. New conceptual frameworks methodological strategies needed address rapid evolution they research deployed care across multiple observe how, this deployment, become 'domesticated'. propose longitudinal multisite `biographical' investigations rather than snapshot emerging technologies that fail capture change variation performance contexts.

Language: Английский

Citations

8
Digital transformation of the Pharmaceutical Industry: A future research agenda for management studies DOI Creative Commons
Mario Miozza, Federica Brunetta, Francesco Paolo Appio

et al.

Technological Forecasting and Social Change, Journal Year: 2024, Volume and Issue: 207, P. 123580 - 123580

Published: July 18, 2024

Despite the widespread attention given to Digital Transformation (DT), there is a notable lack of comprehensive knowledge concerning its implications within Pharmaceutical Industry (PI), particularly from Management Studies perspective. This research employs Systematic Literature Review approach, utilizing an initial review 404 articles (which resulted in identification 35 relevant papers) propose Future Research Agenda focusing on key technologies driving PI-DT and addressing major gaps current literature. Specifically, four primary directions are delineated areas (I) Operations Management, (II) Strategic (III) Organization's Theory, (IV) Stakeholder's Theory. In conclusion, addresses underdeveloped field Studies, offering theoretical foundation for further scholarly inquiry development this field.

Language: Английский

Citations

8
High-reward, high-risk technologies? An ethical and legal account of AI development in healthcare DOI Creative Commons

Maelenn Corfmat,

Joé T. Martineau, Catherine Régis

et al.

BMC Medical Ethics, Journal Year: 2025, Volume and Issue: 26(1)

Published: Jan. 15, 2025

Language: Английский

Citations

1
Key drivers for the incorporation of artificial intelligence in humanitarian supply chain management DOI Creative Commons
Koppiahraj Karuppiah,

Jayakrishna Kandasamy,

Luis Rocha-Lona

et al.

International Journal of Industrial Engineering and Operations Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 7, 2025

Purpose Humanitarian supply chain management (HSCM), operating in a complex environment, needs to be agile and robust. The advent of digital technologies has revolutionized HSCM operations, thus, this study identifies evaluates key drivers artificial intelligence (AI) incorporation HSCM. Design/methodology/approach In total, 20 were identified through review the relevant extant literature finalized with experts’ inputs using Likert scale survey. With Kappa analysis, these classified into four groups: technical (T), organization (O), human (H) institution (I). An integrated multi-criteria decision-making (MCDM) method Fermatean fuzzy set (FFS) analytic hierarchy process (AHP) Decision-Making Trial Evaluation Laboratory (DEMATEL) was used rank explore their causal interrelationships. Findings Improved performance output, organizational preparedness, user acceptance continued support, guarantee job security for technologically semi-skilled workers government support are five AI Originality/value This integration FFS-AHP-DEMATEL.

Language: Английский

Citations

1