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AI & SOCIETY
<p><strong>AI & Society: Knowledge, Culture and Communication</strong>, is an International Journal publishing refereed scholarly articles, position papers, debates, short communications, systematic reviews and reviews of books and other publications. Established in 1986, the Journal focuses on societal issues including the design, use, management, and policy of information, communications and new media technologies, with a particular emphasis on cultural, social, cognitive, economic, ethical, and philosophical implications, addressing the need for a paradigm shift in the way digital systems are conceived, used, applied, and regulated. </p>
<p><strong>AI & Society</strong> positions the significance of values for critical thinking, a diversity of cultural perspectives and practices to address the issues of our times to shape AI mediated futures for the common good. We welcome reflective and contextual contributions and participation from researchers and practitioners in a variety of fields including humanities, social sciences, arts and sciences, design, and digital media arts. This includes broader societal and cultural impacts and contexts. The journal encourages contributions exploring the potential and fundamental values beyond algorithmic optimization, efficiency, or profitability. Co-authored articles from diverse disciplines are encouraged.</p>
<p><strong>AI & Society </strong>has a broad scope and is strongly interdisciplinary. It examines the roles of algorithms as scientific instruments and cultural determinants, critically attending to the outstanding need to shift from algorithmic governance shaping society, to society shaping algorithms and their influence. Most fundamentally, <em>AI & Society</em> considers how the shift from personalization to personification of algorithmic technologies is, has been and should be, affecting our ability to navigate indeterminacy - that which cannot be modelled in advance - in order that we can deal with that which is not represented, with the tacit, or the excluded.</p>
<p><strong>AI & Society</strong> promotes an understanding of the potential, transformative impacts and critical consequences of technological mediation for human and natural ecologies and societies. Technological innovations, including new sciences such as biotech, nanotech and neuroscience, offer great potential, but also pose existential risks. Rooted in the human-centred tradition of science and technology, <em>AI & Society</em> acts as a catalyst, promoter and facilitator of engagement with a diversity of voices on visionary, over-the-horizon issues involving the arts, philosophy, science and technology. </p>
<p>In keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the societal dimension of research, particularly the benefits, impacts and implications for human beings and the natural and institutional ecosystems on which we depend. This may include factors such as trust, empathy, ethics, aesthetics, bias and prejudice, privacy, reliability, responsibility, and competence of AI systems. Such arguments should be validated by critical comment on current research in associated area, clearly exposing the significance of submitted works for the journal's contemporary, internal and diverse readership. </p>
<p>The journal is in four parts: a) Research; b) Open Forum; c) Curmudgeon Corner; d) Reviews and Book Reviews.</p>
<p><strong>Research </strong>articles are strictly focused, academically coherent, theoretically grounded, methodologically sound and empirically strong. In keeping with the ethos of the journal, submissions should provide a substantial and explicit argument on the purpose of the article, its relevance to current and future design and applications of AI, particularly on the societal dimension of research, potential benefits, impacts and implications for society. Articles in this category are expected to make a significant contribution to knowledge. </p>
<p><strong>Open Forum</strong> articles advance on established and ongoing research, focusing on social impacts of emerging technologies, applications, and practices. Controversial themes are to be treated with balance, nuance, informed scholarship and insight. Submissions are expected to expose key concepts, ideas, and theories through deep and detailed engagement with foundational works and comparable contemporary research programs and publications. The articles should develop strong central messages clearly communicating their significance as contributions to current inquiries and attendant discussions. </p>
<p><strong>Review </strong>articles provide analytically rigorous and conceptually grounded examinations of existing scholarship, practices, or debates relevant to the journal’s scope. Suitable formats include structured literature reviews of research, theory driven integrative surveys, critical state of the field analyses, and reflective reviews that advance conceptual or methodological understanding. Review articles may also examine science practices, exhibitions, research forums, policy developments, or books, provided they demonstrate analytical depth and clear relevance to societal, cultural, or application domains. Reviews should engage critically with existing empirical findings, compare approaches across studies, and articulate implications for future research, design, or implementation. Book Reviews are reviewed by the Editorial Board. </p>
<p><strong>Curmudgeon Corner </strong>is a short opinionated letter to the editor on trends in technology, arts, science and society, commenting emphatically on issues of concern to the research community and wider society. The Curmudgeon usually benefits from a clearly staked claim, a distinctive argumentative voice, and a slightly combative or contrarian edge. Curmudgeon article is a straight essay (no abstract, no key words), with no subsections, no more than 3 references and 2 co-authors. The Curmudgeon Corner letters are reviewed by the Editorial Board.</p>
<p><strong>Submissions</strong> in all the above categories should be clear, accessible, and informative for readers from diverse cultural backgrounds and disciplines, who are often reading in English as a second and/or foreign language outside of personal areas of expertise. LLM use for tasks other than grammar and translation, and high similarity submissions (archived/published) are strongly discouraged. Pre-publications should be acknowledged in the declaration section. Normal word length: Research 10k, Open Forum 8k, Curmudgeon 1-1.5k, Reviews 8k, Book Reviews: 1-1.5 K</p>
List of Papers (Total 1,007)
Amid the pervasive integration of AI technologies across societal and industrial domains, understanding users’ trust in these systems becomes increasingly crucial. This study addresses the growing need to understand users’ trust in Generative Artificial Intelligence (GenAI) and explores the societal implications of this type of trust. Based on the socio-technical systems theory...
Auditing of AI systems is a promising way to understand and manage ethical problems and societal risks associated with contemporary AI systems, as well as some anticipated future risks. Efforts to develop standards for auditing artificial intelligence (AI) systems have therefore understandably gained momentum. However, current approaches are not just insufficient, but can be...
The rise of ChatGPT has emphasized the need for an improved conceptual understanding of users’ agency when interacting with artificial intelligence (AI) systems for healthcare. Australian ChatGPT users (N = 216) completed a repeated measures online survey. Hierarchical regression analyses assessed the influence of demographic factors (age and gender), Technology Acceptance Model...
Although there is a wide range of scientific papers introducing artificial intelligence techniques in the mental health field, there is a lack of literature assessing the reporting of ethical concerns in such studies. In addition, it is not yet known whether the authors seek ethical approval or informed consent while performing such research. This study aimed to investigate the...
Exploring human trust in artificial intelligence (AI) in Law Enforcement domain is paramount for its ethical and effective deployment. As AI systems become increasingly integrated into society, trust ensures transparency, accountability, and fairness in their deployment. Despite the rapid increase in discussion about AI usage in law enforcement in various sectors globally, no...
Despite significant advancements in AI and automated driving, a robust ethical framework for AV decision-making remains undeveloped. Such a framework requires clearly defined moral attributes to guide AVs in evaluating complex and ethically sensitive scenarios. Existing frameworks often rely on a single normative ethical theory, limiting their ability to address the nuanced...
This article investigates the pervasive issue of bias within AI-driven cultural heritage collections, emphasizing how digital technologies both inherit and amplify existing societal and historical prejudices embedded in analogue records. It outlines the multifaceted nature of bias—ranging from data selection and annotation to algorithmic design and user interaction—demonstrating...
This article traces the conceptual lineage of AGI through three influential paradigms: strong AI, human-level AI, and AGI—highlighting the philosophical and operational tensions shaping contemporary debates. The article examines emerging reorientations toward operational benchmarks that decouple artificial intelligence from human-like cognition. It proposes a novel taxonomy to...
I look at the main metaphors used to frame the role of artificial intelligence (AI) in artistic creativity—tool, collaborator, and medium. I argue that these metaphorical framings not only describe but also actively shape our perceptions of AI and its role. By trying to fit AI into traditional categories, they potentially overlook its ability to introduce something radically new...
AI algorithms require human input to achieve technological aims. This fact is often overlooked in discussions of autonomous systems and AI safety, to the detriment of both philosophical discourse and practical progress. One potential remedy is to ground our theorizing more fundamentally in the idea that AI technologies are sociotechnological systems with human and artifactual...
The primary objective of this study is to determine whether the level of digital literacy among pre-service teachers reliably correlates with their anxiety levels concerning artificial intelligence. The study was conducted as a correlational study, with a sample size of 221 pre-service teachers. The study’s population comprised 3922 pre-service teachers enrolled at Turkish state...
This article situates current deep learning (DL) artificial intelligence (AI) within Leroi-Gourhan’s deep history of the human species’ relation to technology. According to Leroi-Gourhan, technology is both a key element of anthropogenesis and a source of later tensions (or disentanglement) between the human species and its external and increasingly autonomous technics. Human...
Successful implementation of autonomous vehicle (AV) technology is not only an engineering challenge but also a social, political, and ethical one. As AVs become commonplace and begin affecting people’s daily lives in a more profound way, media coverage of the social and ethical considerations of these technologies will follow suit. We seek to analyze and categorize the media’s...
Artificial testimony generated by large language models (LLMs) can be a source of knowledge. However, the requirement that artificial testifiers must satisfy for successful knowledge acquisition is different from the requirement that human testifiers must satisfy. Correspondingly, the epistemic ground of artificial testimonial knowledge is not the well-known and accepted ones...
People’s concerns regarding the fairness of algorithmic decision-making, coupled with its expanding utilization across various spheres of our lives underscores the need for robust measures to assess perceived fairness in standardized survey research. Existing fairness scales often suffer from inadequate content coverage, particularly in terms of Perceived Group Discrimination...
This paper examines the application of evolutionary analogy in AI (artificial intelligence) research, focussing on narratives that perpetuate individuated and autonomous imaginaries of AI systems through biological diction. AI research has long drawn inspiration from evolution to design and predict algorithmic change. Occasionally, these narratives extend inspiration to reimagine...