Topic Editors

Department of Sociology, Faculty of Social and Human Sciences, University of the Azores, 9500-321 Ponta Delgada, Portugal
CIPES – Centre for Research in Higher Education Policies, 4450-227 Matosinhos, Portugal

The Impact of Artificial Intelligence on Research and Communication in the Social Sciences and Humanities

Abstract submission deadline
31 May 2025
Manuscript submission deadline
31 July 2025
Viewed by
4953

Topic Information

Dear Colleagues,

The undeniable and inevitable rise of Artificial Intelligence (AI) in various fields of human activity presents both remarkable opportunities and potential risks for scientific research. While AI promises significant advances, its integration into research practices raises uncertainties and ethical considerations. These concerns extend beyond the design and conduct of research to the products of scientific inquiry, their dissemination through various communication channels, peer review processes, and engagement with both specialized and broader audiences. As a result, the landscape of scientific activity is undergoing a fundamental transformation, driven by AI-based technologies. This evolving context poses profound challenges to science itself and to researchers. These challenges involve complex and often controversial issues across technical and ethical domains. Key questions include the extent to which AI tools can actively participate in research activities, from analysis and co-authorship to dissemination. In addition, the role of human researchers in knowledge creation and dissemination is under scrutiny. This call highlights the need for proactivity within the Social Sciences and the Humanities regarding the specificities of AI use and its broader implications. This topic aims to foster a deeper understanding of these critical issues and to promote informed practices for the development of rigorous knowledge.

We welcome submissions that address this topic from a variety of theoretical and methodological perspectives and a range of manuscript types, including research articles, reviews, commentaries, and others. We are particularly interested in manuscripts that bridge the gap between technical advances in AI and the specific needs and considerations of research in Social Sciences and the Humanities.

Dr. Sandro Serpa
Dr. Maria José Sá
Topic Editors

Keywords

  • artificial intelligence
  • social sciences
  • education
  • research
  • communication
  • scientific ethics
  • humanities
  • publication

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Societies
societies
1.7 3.1 2011 32.1 Days CHF 1400 Submit
AI
ai
3.1 7.2 2020 18.9 Days CHF 1600 Submit
Social Sciences
socsci
1.7 2.6 2012 34.2 Days CHF 1800 Submit

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Published Papers (2 papers)

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12 pages, 1289 KiB  
Article
Social Biases in AI-Generated Creative Texts: A Mixed-Methods Approach in the Spanish Context
by María Gabino-Campos, José I. Baile and Aura Padilla-Martínez
Soc. Sci. 2025, 14(3), 170; https://doi.org/10.3390/socsci14030170 - 11 Mar 2025
Viewed by 732
Abstract
This study addresses the biases in artificial intelligence (AI) when generating creative content, a growing challenge due to the widespread adoption of these technologies in creating automated narratives. Biases in AI reflect and amplify social inequalities. They perpetuate stereotypes and limit diverse representation [...] Read more.
This study addresses the biases in artificial intelligence (AI) when generating creative content, a growing challenge due to the widespread adoption of these technologies in creating automated narratives. Biases in AI reflect and amplify social inequalities. They perpetuate stereotypes and limit diverse representation in the generated outputs. Through an experimental approach with ChatGPT-4, biases related to age, gender, sexual orientation, ethnicity, religion, physical appearance, and socio-economic status, are analyzed in AI-generated stories about successful individuals in the context of Spain. The results reveal an overrepresentation of young, heterosexual, and Hispanic characters, alongside a marked underrepresentation of diverse groups such as older individuals, ethnic minorities, and characters with varied socio-economic backgrounds. These findings validate the hypothesis that AI systems replicate and amplify the biases present in their training data. This process reinforces social inequalities. To mitigate these effects, the study suggests solutions such as diversifying training datasets and conducting regular ethical audits, with the aim of fostering more inclusive AI systems. These measures seek to ensure that AI technologies fairly represent human diversity and contribute to a more equitable society. Full article
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23 pages, 3835 KiB  
Article
Perception and Ethical Challenges for the Future of AI as Encountered by Surveyed New Engineers
by Hisham O. Khogali and Samir Mekid
Societies 2024, 14(12), 271; https://doi.org/10.3390/soc14120271 - 18 Dec 2024
Viewed by 2705
Abstract
Our extensive history of embracing AI technological advances demonstrates that AI may be a useful tool if humans learn to use it intelligently, and that concerns about it replacing human occupations may be unwarranted. Indeed, a range of remarkable new AI approaches are [...] Read more.
Our extensive history of embracing AI technological advances demonstrates that AI may be a useful tool if humans learn to use it intelligently, and that concerns about it replacing human occupations may be unwarranted. Indeed, a range of remarkable new AI approaches are fast transforming diverse human experiences and fundamentally disrupting our lives, but not without some drawbacks. This study reflects on how new engineers view AI’s influence on trust and ethical attitudes. Data-driven perceptions drive educated debates, education initiatives, and legislative decisions aimed at effectively addressing non-scientific AI concerns. This contributes to improving the future of AI-based learning through transdisciplinary research that considers the evidence of ethical challenges raised by AI misapplication. Our analysis of quantitative data from a survey of 715 recently graduated engineers from diverse fields, who often use information technologies, reveals that many believed AI-related difficulties were scientifically uncertain. According to this study’s findings, the observed variance in the trend relating to reduced fear of job losses due to AI (R2 = 0.1121) suggests that specialties heavily impacted by crucial decision making have a lower level of fear. This provides strong evidence for an optimistic path to AI breakthroughs boosting the level of confidence in and acceptance of AI across many industries. Full article
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