Artificial Intelligence in Participatory Environments: Technologies, Ethics, and Literacy Aspects

A special issue of Societies (ISSN 2075-4698).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4103

Special Issue Editors


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Guest Editor
Multidisciplinary Media and Mediated Communication (M3C) Research Group, School of Journalism & Mass Communications, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: participatory journalism; online news production; user-generated content; legal issues in media organizations

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Guest Editor
Multidisciplinary Media and Mediated Communication (M3C) Research Group, School of Journalism & Mass Communications, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: media technologies; signal processing; machine learning; media authentication; audiovisual content management; multimedia semantics; semantic web
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Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) has constituted a significant scholarly object over the past few decades, profoundly impacting a broad spectrum of academic and industrial fields. The area of AI has exploded in recent years along with participatory tools and media environments. In this age of fragmented information flows and vast amounts of raw data, computational developments along with socio-economic changes facilitate the incorporation of AI technologies in areas ranging from mathematics, engineering, and medical science to psychology, education, media, and communications. Diverse aspects of people’s daily lives are also formed under the driving power of AI tools and systems. Applications based on machine/deep learning (ML/DL) and natural language processing (NLP) techniques increasingly play a considerable role in living, learning, working, and co-situating in collaborative and participatory environments.

Although the utilization of such algorithmic approaches and technologies offers significant benefits for society, the need to consider arising risks and challenges is strong. The request for ethical codes in the use of AI concerns not only the machine training part and the design of the targeted functionalities but also the deployment and implementation of the envisioned services. For example, the acquisition of Facebook users’ personal data by Cambridge Analytica or the role of Twitter bots in the United States Presidential Election of 2016 stand as milestones in the ongoing discussion about AI misusage. Likewise, disinformation problems have been substantially intensified with the proliferation of generative content and deep learning models, launching the so-called deep fakes, which pose severe threats to our societies and democracies. More broadly, issues about transparency, accountability, and justice deserve consideration. Data integrity, privacy, and security protocols are always in place when users and (crowdsourced) datasets are involved. In this vein, initial steps towards a necessary framework have been conducted by national and international authorities. However, the development of precise regulatory guidelines is of great importance in terms of security, data protection, bias, and discrimination avoidance, among others. Against this background and since AI implications are increasingly omnipresent, the prioritization of literacy and educational initiatives should include all actors involved (stakeholders, developers, targeted end users, media and communication professionals, journalists, practitioners, etc.). Thus, a multidisciplinary approach can shape the context for a deeper understanding and the harmless use of AI without overlooking the constantly evolving (technological) landscape.

The current call for papers (CfP) aims at further enlightening the above perspectives. We invite researchers to submit original/featured research works related but not limited to the following multidisciplinary topics:

  • AI techniques in participatory tools and collaborative environments;
  • AI ethics;
  • AI education and multidisciplinary literacy needs;
  • Audience engagement in data crowdsourcing and annotation tasks;
  • Datasets utilization, ethics, and legal concerns in AI;
  • Participatory media, journalism, and AI perspectives;
  • Hate speech detection using AI;
  • Hate crime prevention using AI;
  • AI tools in misinformation and disinformation detection;
  • AI-assisted forensics tools: legal and ethical concerns;
  • AI-assisted management of media assets and/or use rights: technological and ethical concerns;
  • Technological and ethical concerns of big data;
  • Smart systems for education and collaborative working environments;
  • AI-assisted citizen science: Technological limitation, ethics, and training concerns.

Contributions must follow one of the three categories of papers for the journal (article, conceptual paper, or review) and address the topic of the Special Issue.

Dr. Theodora Saridou
Prof. Dr. Charalampos Dimoulas
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Societies is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • artificial intelligence
  • (AI) ethics
  • media industry
  • education
  • digital literacy
  • (algorithmic) journalism
  • participatory/citizen’s journalism
  • machine/deep learning
  • datasets (crowdsourcing, annotation, utilization)

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Published Papers (3 papers)

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20 pages, 17928 KiB  
Article
AI-Generated Graffiti Simulation for Building Façade and City Fabric
by Naai-Jung Shih
Societies 2024, 14(8), 142; https://doi.org/10.3390/soc14080142 - 3 Aug 2024
Viewed by 495
Abstract
Graffiti represents a multi-disciplinary social behavior. It is used to annotate urban landscapes under the assumption that building façades will constantly evolve and acquire modified skins. This study aimed to simulate the interaction between building façades and generative AI-based graffiti using Stable Diffusion [...] Read more.
Graffiti represents a multi-disciplinary social behavior. It is used to annotate urban landscapes under the assumption that building façades will constantly evolve and acquire modified skins. This study aimed to simulate the interaction between building façades and generative AI-based graffiti using Stable Diffusion® (SD v 1.7.0). The context used for graffiti generation considered the graffiti as the third skin, the remodeled façade as the second skin, and the original façade as the first skin. Graffiti was created based on plain-text descriptions, representative images, renderings of scaled 3D prototype models, and characteristic façades obtained from various seed elaborations. It was then generated from either existing graffiti or the abovementioned context; overlaid upon a campus or city; and judged based on various criteria: style, area, altitude, orientation, distribution, and development. I found that rescaling and reinterpreting the context presented the most creative results: it allowed unexpected interactions between the urban fabric and the dynamics created to be foreseen by elaborating on the context and due to the divergent instrumentation used for the first, second, and third skins. With context awareness or homogeneous aggregation, graphic partitions can thus be merged into new topologically re-arranged polygons that enable a cross-gap creative layout. Almost all façades were found to be applicable. AI generation enhances awareness of the urban fabric and facilitates a review of both the human scale and buildings. AI-based virtual governance can use generative graffiti to facilitate the implementation of preventive measures in an urban context. Full article
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18 pages, 1717 KiB  
Article
Importance of University Students’ Perception of Adoption and Training in Artificial Intelligence Tools
by José Carlos Vázquez-Parra, Carolina Henao-Rodríguez, Jenny Paola Lis-Gutiérrez and Sergio Palomino-Gámez
Societies 2024, 14(8), 141; https://doi.org/10.3390/soc14080141 - 3 Aug 2024
Viewed by 1009
Abstract
Undoubtedly, artificial intelligence (AI) tools are becoming increasingly common in people’s lives. The educational field is one of the most reflective on the importance of its adoption. Universities have made great efforts to integrate these new technologies into their classrooms, considering that every [...] Read more.
Undoubtedly, artificial intelligence (AI) tools are becoming increasingly common in people’s lives. The educational field is one of the most reflective on the importance of its adoption. Universities have made great efforts to integrate these new technologies into their classrooms, considering that every future professional will need AI skills and competencies. This article examines the importance of student perception and acceptance in adopting AI tools in higher education effectively. It highlights how students’ positive perceptions can significantly influence their motivation and commitment to learning. This research emphasizes that to integrate AI into university curricula successfully, it is essential to include its technologies in all areas of study and foster positivity among students regarding their use and training. This study’s methodology applied the validated instrument “Perception of Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” to a sample of Mexican students. This exploratory analysis highlights the need for educational institutions to understand and address student perceptions of AI to design educational strategies that incorporate technological advances, are pedagogically relevant, and align with the students’ aspirations and needs. Full article
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16 pages, 619 KiB  
Concept Paper
Artificial Intelligence on Food Vulnerability: Future Implications within a Framework of Opportunities and Challenges
by Diosey Ramon Lugo-Morin
Societies 2024, 14(7), 106; https://doi.org/10.3390/soc14070106 - 29 Jun 2024
Viewed by 1024
Abstract
This study explores the field of artificial intelligence (AI) through the lens of Stephen Hawking, who warned of its potential dangers. It aims to provide a comprehensive understanding of AI and its implications for food security using a qualitative approach and offering a [...] Read more.
This study explores the field of artificial intelligence (AI) through the lens of Stephen Hawking, who warned of its potential dangers. It aims to provide a comprehensive understanding of AI and its implications for food security using a qualitative approach and offering a contemporary perspective on the topic. The study explores the challenges and opportunities presented by AI in various fields with an emphasis on the global food reality. It also highlights the critical importance of striking a harmonious balance between technological progress and the preservation of local wisdom, cultural diversity, and environmental sustainability. In conclusion, the analysis argues that AI is a transformative force with the potential to address global food shortages and facilitate sustainable food production. However, it is not without significant risks that require rigorous scrutiny and ethical oversight. Full article
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