Results for 'Generative AI'

971 found
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  1. Generative AI and the Future of Democratic Citizenship.Paul Formosa, Bhanuraj Kashyap & Siavosh Sahebi - 2024 - Digital Government: Research and Practice 2691 (2024/05-ART).
    Generative AI technologies have the potential to be socially and politically transformative. In this paper, we focus on exploring the potential impacts that Generative AI could have on the functioning of our democracies and the nature of citizenship. We do so by drawing on accounts of deliberative democracy and the deliberative virtues associated with it, as well as the reciprocal impacts that social media and Generative AI will have on each other and the broader information landscape. Drawing (...)
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  2.  27
    Generative AI in Graph-Based Spatial Computing: Techniques and Use Cases.Sankara Reddy Thamma Sankara Reddy Thamma - 2024 - International Journal of Scientific Research in Science and Technology 11 (2):1012-1023.
    Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique (...)
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  3. Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity.Claudio Novelli, Federico Casolari, Philipp Hacker, Giorgio Spedicato & Luciano Floridi - 2024 - Computer Law and Security Review 55.
    The complexity and emergent autonomy of Generative AI systems introduce challenges in predictability and legal compliance. This paper analyses some of the legal and regulatory implications of such challenges in the European Union context, focusing on four areas: liability, privacy, intellectual property, and cybersecurity. It examines the adequacy of the existing and proposed EU legislation, including the Artificial Intelligence Act (AIA), in addressing the challenges posed by Generative AI in general and LLMs in particular. The paper identifies potential (...)
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  4. Generative AI in the Creative Industries: Revolutionizing Art, Music, and Media.Mohammed F. El-Habibi, Mohammed A. Hamed, Raed Z. Sababa, Mones M. Al-Hanjori, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Engineering Research(Ijaer) 8 (10):71-74.
    Abstract: Generative AI is transforming the creative industries by redefining how art, music, and media are produced and experienced. This paper explores the profound impact of generative AI technologies, such as deep learning models and neural networks, on creative processes. By enabling artists, musicians, and content creators to collaborate with AI, these systems enhance creativity, speed up production, and generate novel forms of expression. The paper also addresses ethical considerations, including intellectual property rights, the role of human creativity (...)
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  5. Generative AI and photographic transparency.P. D. Magnus - forthcoming - AI and Society:1-6.
    There is a history of thinking that photographs provide a special kind of access to the objects depicted in them, beyond the access that would be provided by a painting or drawing. What is included in the photograph does not depend on the photographer’s beliefs about what is in front of the camera. This feature leads Kendall Walton to argue that photographs literally allow us to see the objects which appear in them. Current generative algorithms produce images in response (...)
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  6.  35
    Optimization of Generative AI Costs in Multi-Agent and Multi-Cloud Systems.Sankara Reddy Thamma Sankara Reddy Thamma - 2024 - International Journal of Scientific Research in Science and Technology 11 (6):953-965.
    The generative AI system is being adopted across the several fields to provide novel solutions for text generation, image synthesis, and decision-making. But when they are used in multi-agent and multi-cloud systems, they are expensive in terms of computation and finance. Regarding the aforementioned factors, this paper aims to examine methods of reducing such costs while achieving system efficiency. Such measures as dynamic workload distribution, resource scaling, as well as cost-conscious model selection is described. Through the examples of case (...)
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  7. Growing the image: Generative AI and the medium of gardening.Nick Young & Enrico Terrone - forthcoming - Philosophical Quarterly.
    In this paper, we argue that Midjourney—a generative AI program that transforms text prompts into images—should be understood not as an agent or a tool, but as a new type of artistic medium. We first examine the view of Midjourney as an agent, considering whether it could be seen as an artist or co-author. This perspective proves unsatisfactory, as Midjourney lacks intentionality and mental states. We then explore the notion of Midjourney as a tool, highlighting its unpredictability and the (...)
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  8. Trust and generative AI: embodiment considered.Kefu Zhu - 2024 - AI and Ethics.
    Questions surrounding engagement with generative AI are often framed in terms of trust, yet mere theorizing about trust may not yield actionable insights, given the multifaceted nature of trust. Literature on trust typically overlooks how individuals make meaning in their interactions with other entities, including AI. This paper reexamines trust with insights from Merleau-Ponty’s views on embodiment, positing trust as a style of world engagement characterized by openness—an attitude wherein individuals enact and give themselves to their lived world, prepared (...)
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  9. Generative AI and the value changes and conflicts in its integration in Japanese educational system.Ngoc-Thang B. Le, Phuong-Thao Luu & Manh-Tung Ho - manuscript
    This paper critically examines Japan's approach toward the adoption of Generative AI such as ChatGPT in education via studying media discourse and guidelines at both the national as well as local levels. It highlights the lack of consideration for socio-cultural characteristics inherent in the Japanese educational systems, such as the notion of self, teachers’ work ethics, community-centric activities for the successful adoption of the technology. We reveal ChatGPT’s infusion is likely to further accelerate the shift away from traditional notion (...)
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  10. Can ChatGPT be an author? Generative AI creative writing assistance and perceptions of authorship, creatorship, responsibility, and disclosure.Paul Formosa, Sarah Bankins, Rita Matulionyte & Omid Ghasemi - forthcoming - AI and Society.
    The increasing use of Generative AI raises many ethical, philosophical, and legal issues. A key issue here is uncertainties about how different degrees of Generative AI assistance in the production of text impacts assessments of the human authorship of that text. To explore this issue, we developed an experimental mixed methods survey study (N = 602) asking participants to reflect on a scenario of a human author receiving assistance to write a short novel as part of a 3 (...)
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  11.  91
    Innovating Financial and Medical Services: Generative AI’s Impact on Banking and Healthcare.M. Sheik Dawood - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):610-618.
    Results indicate substantial improvements in efficiency, accuracy, and personalized care, but also highlight the challenges of data privacy, ethical considerations, and system scalability. By providing a structured analysis, this research contributes insights into optimizing generative AI deployments for both banking and healthcare, ensuring a balance between innovation and risk management. The study concludes with recommendations for future research directions, including advanced model training, ethical guidelines, and enhanced privacy measures. These insights aim to inform practitioners on the benefits of (...) AI, ensuring sustainable integration into banking and healthcare ecosystems. (shrink)
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  12.  33
    Revolutionizing Healthcare: Spatial Computing Meets Generative AI.Sankara Reddy Thamma Sankara Reddy Thamma - 2024 - International Journal of Scientific Research in Science, Engineering and Technology 11 (5):324-336.
    The health industry is experiencing change, the newest forerunner of which is being propelled by spatial computing and generative AI. Spatial computing simply refers to the ability to interface with physical space through computation and digital devices; on the other hand, generative AI means using advanced machine learning to generate new output. This paper examines the roles and the combined possibilities of these two technologies with the view of transforming health care and diagnostics in the field of patient (...)
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  13. (1 other version)Generative AI and human labor: who is replaceable?AbuMusab Syed - 2023 - AI and Society:1-3.
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  14. Embracing ChatGPT and other generative AI tools in higher education: The importance of fostering trust and responsible use in teaching and learning.Jonathan Y. H. Sim - 2023 - Higher Education in Southeast Asia and Beyond.
    Trust is the foundation for learning, and we must not allow ignorance of this new technologies, like Generative AI, to disrupt the relationship between students and educators. As a first step, we need to actively engage with AI tools to better understand how they can help us in our work.
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  15. Diffusing the Creator: Attributing Credit for Generative AI Outputs.Donal Khosrowi, Finola Finn & Elinor Clark - 2023 - Aies '23: Proceedings of the 2023 Aaai/Acm Conference on Ai, Ethics, and Society.
    The recent wave of generative AI (GAI) systems like Stable Diffusion that can produce images from human prompts raises controversial issues about creatorship, originality, creativity and copyright. This paper focuses on creatorship: who creates and should be credited with the outputs made with the help of GAI? Existing views on creatorship are mixed: some insist that GAI systems are mere tools, and human prompters are creators proper; others are more open to acknowledging more significant roles for GAI, but most (...)
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  16. Transforming Industries: The Role of Generative AI in Revolutionizing Banking and Healthcare.M. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):580-600.
    The research evaluates generative AI’s capabilities through a multi-phase framework, addressing how data synthesis, language models, and predictive algorithms contribute to sector-specific applications. In banking, the model assesses the impact of AI-driven chatbot interactions, credit risk assessment, and personalized financial services on customer experience and bank performance. Healthcare applications are explored through image synthesis for diagnostics, predictive modeling in patient care, and drug discovery simulations. The experimental setup is rigorously tested across metrics such as response accuracy, cost-effectiveness, and data (...)
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  17. Advancing Financial Risk Modeling: Vasicek Framework Enhanced by Agentic Generative Ai.Satyadhar Joshi - 2025 - International Research Journal of Modernization in Engineering Technology and Science 1 (7):4413-4420.
    This paper provides a comprehensive review of the Vasicek model and its applications in finance, categorizing the literature into four key areas: Vasicek model applications, Monte Carlo simulations, negative interest rates and risk, and deep learning for financial time series. To provide deeper insights, a synthesis chart and chronological analysis are included to highlight significant trends and contributions. Building upon this foundation, we employ Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to generate synthetic future interest rate data. These (...)
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  18. Using text-to-image generative AI to create storyboards: Insights from a college psychology classroom.Shantanu Tilak, Blake Bagley, Jadalynn Cantu, Mya Cosby, Grace Engelbert, Ja'Kaysiah Hammonds, Gabrielle Hickman, Aaron Jackson, Bryce Jones, Kadie Kennedy, Stephanie Kennedy, Austin King, Ryan Kozlej, Allyssa Mortenson, Muller Sebastien, Julia Najjar, Sydney Queen, Milo Schuehle, Nolan Schulte, Emily Schwarz, Joshua Shearn, Kalyse Williams & Malik Williams - 2024 - Journal of Sociocybernetics 19 (1):1-42.
    This participatory study, conducted in an introductory psychology class, recounts self-reflections of 22 undergraduate students and their instructor engaging in an GenAI-mediated storyboard generation process. It relies on Gordon Pask’s conversation theory, structuring out the nature of interactions between students, instructor, and GenAI, and then uses a qualitative narrative to describe these conversational feedback loops constituting the creation of draft and final storyboards. Results suggest students engaged in cyclical feedback driven processes to master their creations, used elements of photography related (...)
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  19. An Experimental Analysis of Revolutionizing Banking and Healthcare with Generative AI.Sankara Reddy Thamma - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):580-590.
    Generative AI is reshaping sectors like banking and healthcare by enabling innovative applications such as personalized service offerings, predictive analytics, and automated content generation. In banking, generative AI drives customer engagement through tailored financial advice, fraud detection, and streamlined customer service. Meanwhile, in healthcare, it enhances medical imaging analysis, drug discovery, and patient diagnostics, significantly impacting patient care and operational efficiency. This paper presents an experimental study examining the implementation and effectiveness of generative AI in these sectors.
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  20.  99
    Machines That Create: Contingent Computation and Generative AI.M. Beatrice Fazi - 2024 - Media Theory 8 (2):1-12.
    In this article, M. Beatrice Fazi takes up Media Theory’s invitation to engage with Alan Díaz Alva’s analysis of her philosophical work on contingency in computation. The central argument of Fazi’s Contingent Computation: Abstraction, Experience, and Indeterminacy in Computational Aesthetics is that computation can be productive of ontological novelty. This piece revisits that argument in the light of the technological developments that have occurred since 2018, when the book was published. Focusing on generative artificial intelligence (generative AI), the (...)
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  21.  97
    The Computational Search for Unity: Synthesis in Generative AI.M. Beatrice Fazi - 2024 - Journal of Continental Philosophy 5 (1):31-56.
    The outputs of generative artificial intelligence (generative AI) are often called “synthetic” to imply that they are not natural but artificial. Against that use of the term, this article focuses on a different denotation of synthesis, stressing the unifying and compositional aspects of anything synthetic. The case of large language models (LLMs) is used as an example to address synthesis philosophically alongside notions of representation in contemporary computational systems. It is argued that synthesis in generative AI should (...)
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  22.  62
    Smart City and IoT Data Collection Leveraging Generative AI.Eric Garcia - manuscript
    The rapid urbanization of modern cities necessitates innovative approaches to data collection and integration for smarter urban management. With the Internet of Things (IoT) at the core of these advancements, the ability to efficiently gather, analyze, and utilize data becomes paramount. Generative Artificial Intelligence (AI) is revolutionizing data collection by enabling intelligent synthesis, anomaly detection, and real-time decision-making across interconnected systems. This paper explores how generative AI enhances IoT-driven data collection in smart cities, focusing on applications in transportation, (...)
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  23. Escape climate apathy by harnessing the power of generative AI.Quan-Hoang Vuong & Manh-Tung Ho - 2024 - AI and Society 39 (6):1-2.
    “Throw away anything that sounds too complicated. Only keep what is simple to grasp...If the information appears fuzzy and causes the brain to implode after two sentences, toss it away and stop listening. Doing so will make the news as orderly and simple to understand as the truth.” - In “GHG emissions,” The Kingfisher Story Collection, (Vuong 2022a).
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  24. Legal Definitions of Intimate Images in the Age of Sexual Deepfakes and Generative AI.Suzie Dunn - 2024 - McGill Law Journal 69:1-15.
    In January 2024, non-consensual deepfakes came to public attention with the spread of AI generated sexually abusive images of Taylor Swift. Although this brought new found energy to the debate on what some call non-consensual synthetic intimate images (i.e. images that use technology such as AI or photoshop to make sexual images of a person without their consent), female celebrities like Swift have had deepfakes like these made of them for years. In 2017, a Reddit user named “deepfakes” posted several (...)
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  25. Every dog has its day: An in-depth analysis of the creative ability of visual generative AI.Maria Hedblom - 2024 - Cosmos+Taxis 12 (5-6):88-103.
    The recent remarkable success of generative AI models to create text and images has already started altering our perspective of intelligence and the “uniqueness” of humanity in this world. Simultaneously, arguments on why AI will never exceed human intelligence are ever-present as seen in Landgrebe and Smith (2022). To address whether machines may rule the world after all, this paper zooms in on one of the aspects of intelligence Landgrebe and Smith (2022) neglected to consider: creativity. Using Rhodes four (...)
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  26. AI Art is Theft: Labour, Extraction, and Exploitation, Or, On the Dangers of Stochastic Pollocks.Trystan S. Goetze - 2024 - Proceedings of the 2024 Acm Conference on Fairness, Accountability, and Transparency:186-196.
    Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues (...)
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  27. AI as Legal Persons: Past, Patterns, and Prospects.Claudio Novelli, Luciano Floridi, Giovanni Sartor & Gunther Teubner - manuscript
    This paper examines the debate on AI legal personhood, emphasizing the role of path dependencies in shaping current trajectories and prospects. Three primary path dependencies emerge: prevailing legal theories on personhood (singularist vs. clustered), the actual participation of AI in socio-digital institutions (instrumental vs. non-instrumental), and the impact of technological advancements. We argue that these factors dynamically interact, with technological optimism fostering broader attribution of the legal entitlements to AI entities and periods of scepticism narrowing such entitlements. Additional influences include (...)
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  28. AI training data, model success likelihood, and informational entropy-based value.Quan-Hoang Vuong, Viet-Phuong La & Minh-Hoang Nguyen - manuscript
    Since the release of OpenAI's ChatGPT, the world has entered a race to develop more capable and powerful AI, including artificial general intelligence (AGI). The development is constrained by the dependency of AI on the model, quality, and quantity of training data, making the AI training process highly costly in terms of resources and environmental consequences. Thus, improving the effectiveness and efficiency of the AI training process is essential, especially when the Earth is approaching the climate tipping points and planetary (...)
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  29. AI Enters Public Discourse: a Habermasian Assessment of the Moral Status of Large Language Models.Paolo Monti - 2024 - Ethics and Politics 61 (1):61-80.
    Large Language Models (LLMs) are generative AI systems capable of producing original texts based on inputs about topic and style provided in the form of prompts or questions. The introduction of the outputs of these systems into human discursive practices poses unprecedented moral and political questions. The article articulates an analysis of the moral status of these systems and their interactions with human interlocutors based on the Habermasian theory of communicative action. The analysis explores, among other things, Habermas's inquiries (...)
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  30. AI-Testimony, Conversational AIs and Our Anthropocentric Theory of Testimony.Ori Freiman - 2024 - Social Epistemology 38 (4):476-490.
    The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact (...)
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  31. Acceleration AI Ethics, the Debate between Innovation and Safety, and Stability AI’s Diffusion versus OpenAI’s Dall-E.James Brusseau - manuscript
    One objection to conventional AI ethics is that it slows innovation. This presentation responds by reconfiguring ethics as an innovation accelerator. The critical elements develop from a contrast between Stability AI’s Diffusion and OpenAI’s Dall-E. By analyzing the divergent values underlying their opposed strategies for development and deployment, five conceptions are identified as common to acceleration ethics. Uncertainty is understood as positive and encouraging, rather than discouraging. Innovation is conceived as intrinsically valuable, instead of worthwhile only as mediated by social (...)
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  32. Mapping the potential AI-driven virtual hyper-personalised ikigai universe.Soenke Ziesche & Roman Yampolskiy - manuscript
    Ikigai is a Japanese concept, which, in brief, refers to the “reason or purpose to live”. I-risks have been identified as a category of risks complementing x- risks, i.e., existential risks, and s-risks, i.e., suffering risks, which describes undesirable future scenarios in which humans are deprived of the pursuit of their individual ikigai. While some developments in AI increase i-risks, there are also AI-driven virtual opportunities, which reduce i-risks by increasing the space of potential ikigais, largely due to developments in (...)
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  33. Sự gia tăng của AI tạo sinh và những rủi ro tiềm ẩn cho con người.Hoang Tung-Duong, Dang Tuan-Dung & Manh-Tung Ho - 2024 - Tạp Chí Thông Tin Và Truyền Thông 9 (9/2024):66-73.
    Sự xuật hiện của các công cụ AI tạo sinh trên nền tảng các mô hình ngôn ngữ lớn (LLMs) đã đem đến một công cụ mới cho con người, đặc biệt là trong các ngành sư phạm, báo chí, nhưng chúng cũng đem đến nhiều vấn đề Trong bài viết này, nhóm tác giả sẽ chỉ ra những những bất cập mới xuất hiện hoặc những vấn đề đã tồn tại nhưng có nguy cơ được đẩy lên cao hơn (...)
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  34. The Hazards of Putting Ethics on Autopilot.Julian Friedland, B. Balkin, David & Kristian Myrseth - 2024 - MIT Sloan Management Review 65 (4).
    The generative AI boom is unleashing its minions. Enterprise software vendors have rolled out legions of automated assistants that use large language model (LLM) technology, such as ChatGPT, to offer users helpful suggestions or to execute simple tasks. These so-called copilots and chatbots can increase productivity and automate tedious manual work. In this article, we explain how that leads to the risk that users' ethical competence may degrade over time — and what to do about it.
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  35. AI-generated art and fiction: signifying everything, meaning nothing?Steven R. Kraaijeveld - forthcoming - AI and Society:1-3.
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  36. The Artificial Sublime.Regina Rini - manuscript
    Generative AI systems like ChatGPT and Midjourney can produce prose or images. But can they produce art? I argue that this question, though natural and intriguing, is the wrong one to ask. A better question is this: can generative AI yield distinct or novel forms of aesthetic value? And I argue that the answer is yes. Generative AI can be used to put us in contact with the artificial sublime – a type of aesthetic value that Kant (...)
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  37. Towards a Definition of Generative Artificial Intelligence.Raphael Ronge, Markus Maier & Benjamin Rathgeber - manuscript
    The concept of Generative Artificial Intelligence (GenAI) is ubiquitous in the public and semi-technical domain, yet rarely defined precisely. We clarify main concepts that are usually discussed in connection to GenAI and argue that one ought to distinguish between the technical and the public discourse. In order to show its complex development and associated conceptual ambiguities, we offer a historical-systematic reconstruction of GenAI and explicitly discuss two exemplary cases: the generative status of the Large Language Model BERT and (...)
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  38.  75
    Virtual Anthropology: When and What Could We Learn From Multimodal Agentic Behavior in Generative Worlds?Fabian Kerj - manuscript
    This paper examines the convergence of large language models, multimodal AI, and generative spatial technologies to enable sophisticated simulated worlds for studying agentic behavior. Recent developments in generative architectures, particularly GenEx and topology-aware mesh generation, facilitate the creation of coherent, explorable environments with artificial agents capable of complex interactions. The proposed framework for "virtual anthropology" presents novel opportunities for studying emergent behaviors and cognitive processes in controlled, generative environments, with implications for both theoretical research and practical applications (...)
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  39. Tool, Collaborator, or Participant: AI and Artistic Agency.Anthony Cross - forthcoming - British Journal of Aesthetics.
    Artificial intelligence is now capable of generating sophisticated and compelling images from simple text prompts. In this paper, I focus specifically on how artists might make use of AI to create art. Most existing discourse analogizes AI to a tool or collaborator; this focuses our attention on AI’s contribution to the production of an artistically significant output. I propose an alternative approach, the exploration paradigm, which suggests that artists instead relate to AI as a participant: artists create a space for (...)
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  40. ChatGPT and the Technology-Education Tension: Applying Contextual Virtue Epistemology to a Cognitive Artifact.Guido Cassinadri - 2024 - Philosophy and Technology 37 (14):1-28.
    According to virtue epistemology, the main aim of education is the development of the cognitive character of students (Pritchard, 2014, 2016). Given the proliferation of technological tools such as ChatGPT and other LLMs for solving cognitive tasks, how should educational practices incorporate the use of such tools without undermining the cognitive character of students? Pritchard (2014, 2016) argues that it is possible to properly solve this ‘technology-education tension’ (TET) by combining the virtue epistemology framework with the theory of extended cognition (...)
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  41. Can AI Mind Be Extended?Alice C. Helliwell - 2019 - Evental Aesthetics 8 (1):93-120.
    Andy Clark and David Chalmers’s theory of extended mind can be reevaluated in today’s world to include computational and Artificial Intelligence (AI) technology. This paper argues that AI can be an extension of human mind, and that if we agree that AI can have mind, it too can be extended. It goes on to explore the example of Ganbreeder, an image-making AI which utilizes human input to direct behavior. Ganbreeder represents one way in which AI extended mind could be achieved. (...)
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  42. What Are Lacking in Sora and V-JEPA’s World Models? -A Philosophical Analysis of Video AIs Through the Theory of Productive Imagination.Jianqiu Zhang - unknown
    Sora from Open AI has shown exceptional performance, yet it faces scrutiny over whether its technological prowess equates to an authentic comprehension of reality. Critics contend that it lacks a foundational grasp of the world, a deficiency V-JEPA from Meta aims to amend with its joint embedding approach. This debate is vital for steering the future direction of Artificial General Intelligence(AGI). We enrich this debate by developing a theory of productive imagination that generates a coherent world model based on Kantian (...)
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  43. AI and access to justice: How AI legal advisors can reduce economic and shame-based barriers to justice.Brandon Long & Amitabha Palmer - 2024 - TATuP 33 (1).
    ChatGPT – a large language model – recently passed the U.S. bar exam. The startling rise and power of generative artificial intelligence (AI) systems such as ChatGPT lead us to consider whether and how more specialized systems could be used to overcome existing barriers to the legal system. Such systems could be employed in either of the two major stages of the pursuit of justice: preliminary information gathering and formal engagement with the state’s legal institutions and professionals. We focus (...)
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  44. Digital Homunculi: Reimagining Democracy Research with Generative Agents.Petr Špecián - manuscript
    The pace of technological change continues to outstrip the evolution of democratic institutions, creating an urgent need for innovative approaches to democratic reform. However, the experimentation bottleneck - characterized by slow speed, high costs, limited scalability, and ethical risks - has long hindered progress in democracy research. This paper proposes a novel solution: employing generative artificial intelligence (GenAI) to create synthetic data through the simulation of digital homunculi, GenAI-powered entities designed to mimic human behavior in social contexts. By enabling (...)
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  45.  72
    Is AI intelligent because of its instrumental rationality?Xin Guan - 2023 - Dissertation, University of Oxford
    This thesis argues against the claim that AI is intelligent due to instrumental rationality, refuting both the reduction and emergence thesis. It contends that intelligence cannot be reduced to instrumental rationality and highlights issues in AI development and application. Instead, it proposes the motivation adaptation approach, where intelligence arises from network of generative motivations and the ability to adapt. This alternative is conceptually intuitive, avoids counterexamples, and provides clear development goals and foundations for ethical development. Thus, the thesis concludes (...)
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  46. Wittgenstein and the Aesthetic Robot's Handicap.Julian Friedland - 2005 - Philosophical Investigations 28 (2):177-192.
    Ask most any cognitive scientist working today if a digital computational system could develop aesthetic sensibility and you will likely receive the optimistic reply that this remains an open empirical question. However, I attempt to show, while drawing upon the later Wittgenstein, that the correct answer is in fact available. And it is a negative a priori. It would seem, for example, that recent computational successes in generative AI and textual attribution, most notably those of Donald Foster (famed finder (...)
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  47. Content Reliability in the Age of AI: A Comparative Study of Human vs. GPT-Generated Scholarly Articles.Rajesh Kumar Maurya & Swati R. Maurya - 2024 - Library Progress International 44 (3):1932-1943.
    The rapid advancement of Artificial Intelligence (AI) and the developments of Large Language Models (LLMs) like Generative Pretrained Transformers (GPTs) have significantly influenced content creation in scholarly communication and across various fields. This paper presents a comparative analysis of the content reliability between human-generated and GPT-generated scholarly articles. Recent developments in AI suggest that GPTs have become capable in generating content that can mimic human language to a greater extent. This highlights and raises questions about the quality, accuracy, and (...)
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  48. Disambiguating Algorithmic Bias: From Neutrality to Justice.Elizabeth Edenberg & Alexandra Wood - 2023 - In Francesca Rossi, Sanmay Das, Jenny Davis, Kay Firth-Butterfield & Alex John (eds.), AIES '23: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery. pp. 691-704.
    As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are hampered by conflations (...)
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  49. The value of testimonial-based beliefs in the face of AI-generated quasi-testimony.Felipe Alejandro Álvarez Osorio & Ruth Marcela Espinosa Sarmiento - 2024 - Aufklärung 11 (Especial):25-38.
    The value of testimony as a source of knowledge has been a subject of epistemological debates. The "trust theory of testimony" suggests that human testimony is based on an affective relationship supported by social norms. However, the advent of generative artificial intelligence challenges our understanding of genuine testimony. The concept of "quasi-testimony" seeks to characterize utterances produced by non-human entities that mimic testimony but lack certain fundamental attributes. This article analyzes these issues in depth, exploring philosophical perspectives on testimony (...)
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  50. Prosthetic Godhood and Lacan’s Alethosphere: The Psychoanalytic Significance of the Interplay of Randomness and Structure in Generative Art.Rayan Magon - 2023 - 26Th Generative Art Conference.
    Psychoanalysis, particularly as articulated by figures like Freud and Lacan, highlights the inherent division within the human subject—a schism between the conscious and unconscious mind. It could be said that this suggests that such an internal division becomes amplified in the context of generative art, where technology and algorithms are used to generate artistic expressions that are meant to emerge from the depths of the unconscious. Here, we encounter the tension between the conscious artist and the generative process (...)
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