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  1. 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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  2. 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 (high, medium, (...)
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  3. Texts Without Authors: Ascribing Literary Meaning in the Case of AI.Sofie Vlaad - forthcoming - Journal of Aesthetics and Art Criticism.
    With the increasing popularity of Large Language Models (LLMs), there has been an increase in the number of AI generated literary works. In the absence of clear authors, and assuming such works have meaning, there lies a puzzle in determining who or what fixes the meaning of such texts. I give an overview of six leading theories for ascribing meaning to literary works. These are Extreme Actual Intentionalism, Modest Actual Intentionalism (1 & 2), Conventionalism, Actual Author Hypothetical Intentionalism, and Postulated (...)
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  4. Anthropomorphism and AI Hype.Nicholas Barrow - 2024 - AI and Ethics.
    As humans, we have an innate tendency to ascribe human-like qualities to non-human entities. Whilst sometimes helpful, such anthropomorphic projections are often misleading. This commentary considers how anthropomorphising AI contributes to its misrepresentation and hype. First, I outline three manifestations (terminology; imagery; and morality). Then, I consider the extent to which we ought to mitigate it.
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  5. Protecting scientific integrity in an age of generative AI.Wolfgang Blau - 2024 - Proceedings of the National Academy of Sciences 121 (22):e2407886121.
  6. Reading at university in the time of GenA.Thomas Corbin, Yifei Liang, Margaret Bearman, Tim Fawns, Gene Flenady, Paul Formosa, Lucinda McKnight, Jack Reynolds & Jack Walton - 2024 - Learning Letters 3 (35):1-8.
    Concerns around Generative Artificial Intelligence (GenAI) in higher education have so far largely centred on assessment integrity, resulting in fundamental questions about students’ broader engagement with these tools remaining underexplored. This paper reports on the findings of a survey that forms part of a wider study, comprising the first empirical investigation of GenAI use by university students as a method of engaging with their academic readings. Our survey of 101 students shows that over half of all students surveyed used GenAI (...)
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  7. Deepfakes and Dishonesty.Tobias Flattery & Christian B. Miller - 2024 - Philosophy and Technology 37 (120):1-24.
    Deepfakes raise various concerns: risks of political destabilization, depictions of persons without consent and causing them harms, erosion of trust in video and audio as reliable sources of evidence, and more. These concerns have been the focus of recent work in the philosophical literature on deepfakes. However, there has been almost no sustained philosophical analysis of deepfakes from the perspective of concerns about honesty and dishonesty. That deepfakes are potentially deceptive is unsurprising and has been noted. But under what conditions (...)
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  8. The Many Meanings of Vulnerability in the AI Act and the One Missing.Federico Galli & Claudio Novelli - 2024 - Biolaw Journal 1.
    This paper reviews the different meanings of vulnerability in the AI Act (AIA). We show that the AIA follows a rather established tradition of looking at vulnerability as a trait or a state of certain individuals and groups. It also includes a promising account of vulnerability as a relation but does not clarify if and how AI changes this relation. We spot the missing piece of the AIA: the lack of recognition that vulnerability is an inherent feature of all human-AI (...)
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  9. Correction: ChatGPT is bullshit.Michael Townsen Hicks, James Humphries & Joe Slater - 2024 - Ethics and Information Technology 26 (3):1-2.
  10. Artifacts Without Authors: Generative Artificial Intelligence and the Question of Authorship.Nurbay Irmak - 2024 - Metaphysics 7 (1):1-15.
    Artifacts are often characterized as intentional products of human activities, suggesting that they must have authors. However, contrary to this common characterization, I argue that there exist novel examples of artifacts that lack authors. This novelty arises directly from the emergence of generative artificial intelligence applications. I provide several examples of such authorless artifacts and address potential objections to their existence.
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  11. Generative Artificial Intelligence and Authorship Gaps.Tamer Nawar - 2024 - American Philosophical Quarterly 61 (4):355-367.
    The ever increasing use of generative artificial intelligence raises significant questions about authorship and related issues such as credit and accountability. In this paper, I consider whether works produced by means of users inputting natural language prompts into Generative Adversarial Networks are works of authorship. I argue that they are not. This is not due to concerns about randomness or machine-assistance compromising human labor or intellectual vision, but instead due to the syntactical and compositional limitations of existing AI systems in (...)
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  12. Should the use of adaptive machine learning systems in medicine be classified as research?Robert Sparrow, Joshua Hatherley, Justin Oakley & Chris Bain - 2024 - American Journal of Bioethics 24 (10):58-69.
    A novel advantage of the use of machine learning (ML) systems in medicine is their potential to continue learning from new data after implementation in clinical practice. To date, considerations of the ethical questions raised by the design and use of adaptive machine learning systems in medicine have, for the most part, been confined to discussion of the so-called “update problem,” which concerns how regulators should approach systems whose performance and parameters continue to change even after they have received regulatory (...)
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  13. Authorship and ChatGPT: a Conservative View.René van Woudenberg, Chris Ranalli & Daniel Bracker - 2024 - Philosophy and Technology 37 (1):1-26.
    Is ChatGPT an author? Given its capacity to generate something that reads like human-written text in response to prompts, it might seem natural to ascribe authorship to ChatGPT. However, we argue that ChatGPT is not an author. ChatGPT fails to meet the criteria of authorship because it lacks the ability to perform illocutionary speech acts such as promising or asserting, lacks the fitting mental states like knowledge, belief, or intention, and cannot take responsibility for the texts it produces. Three perspectives (...)
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  14. Chatting with Bots: AI, Speech-Acts, and the Edge of Assertion.Iwan Williams & Tim Bayne - 2024 - Inquiry: An Interdisciplinary Journal of Philosophy.
    This paper addresses the question of whether large language model-powered chatbots are capable of assertion. According to what we call the Thesis of Chatbot Assertion (TCA), chatbots are the kinds of things that can assert, and at least some of the output produced by current-generation chatbots qualifies as assertion. We provide some motivation for TCA, arguing that it ought to be taken seriously and not simply dismissed. We also review recent objections to TCA, arguing that these objections are weighty. We (...)
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  15. Impossibility of Emergent Works’ Protection in U.S. and EU Copyright Law.Matt Blaszczyk - 2023 - North Carolina Journal of Law and Technology 25 (1):1-55.
    Protection of emergent works is impossible. Without an author, there is no expression of ideas which can be original, and thus no copyrightable work. Indeed, the whole system of copyright law, its conceptual building blocks of idea-expression dichotomy, originality, authorship, and the concept of a protectable work operate in the notation of human creativity. Emergent works fall outside of copyright’s positive ontology, being akin to ideas, facts, or subject-matter predicated by technical considerations, rather than authorial creativity. In other words, they (...)
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  16. Guilty Artificial Minds: Folk Attributions of Mens Rea and Culpability to Artificially Intelligent Agents.Michael T. Stuart & Markus Https://Orcidorg Kneer - 2021 - Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2).
    While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...)
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  17. Trustworthy use of artificial intelligence: Priorities from a philosophical, ethical, legal, and technological viewpoint as a basis for certification of artificial intelligence.Jan Voosholz, Maximilian Poretschkin, Frauke Rostalski, Armin B. Cremers, Alex Englander, Markus Gabriel, Hecker Dirk, Michael Mock, Julia Rosenzweig, Joachim Sicking, Julia Volmer, Angelika Voss & Stefan Wrobel - 2019 - Fraunhofer Institute for Intelligent Analysis and Information Systems Iais.
    This publication forms a basis for the interdisciplinary development of a certification system for artificial intelligence. In view of the rapid development of artificial intelligence with disruptive and lasting consequences for the economy, society, and everyday life, it highlights the resulting challenges that can be tackled only through interdisciplinary dialogue between IT, law, philosophy, and ethics. As a result of this interdisciplinary exchange, it also defines six AI-specific audit areas for trustworthy use of artificial intelligence. They comprise fairness, transparency, autonomy (...)
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  18. Vertrauenswürdiger Einsatz von Künstlicher Intelligenz.Jan Voosholz, Maximilian Poretschkin, Frauke Rostalski, Armin B. Cremers, Alex Englander, Markus Gabriel, Dirk Hecker, Michael Mock, Julia Rosenzweig, Joachim Sicking, Julia Volmer, Angelika Voss & Stefan Wrobel - 2019 - Fraunhofer-Institut Für Intelligente Analyse- Und Informationssysteme Iais.
    Die vorliegende Publikation dient als Grundlage für die interdisziplinäre Entwicklung einer Zertifizierung von Künstlicher Intelligenz. Angesichts der rasanten Entwicklung von Künstlicher Intelligenz mit disruptiven und nachhaltigen Folgen für Wirtschaft, Gesellschaft und Alltagsleben verdeutlicht sie, dass sich die hieraus ergebenden Herausforderungen nur im interdisziplinären Dialog von Informatik, Rechtswissenschaften, Philosophie und Ethik bewältigen lassen. Als Ergebnis dieses interdisziplinären Austauschs definiert sie zudem sechs KI-spezifische Handlungsfelder für den vertrauensvollen Einsatz von Künstlicher Intelligenz: Sie umfassen Fairness, Transparenz, Autonomie und Kontrolle, Datenschutz sowie Sicherheit und (...)
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