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  1. Infosphere, Datafication, and Decision-Making Processes in the AI Era.Andrea Lavazza & Mirko Farina - 2023 - Topoi 42 (3):843-856.
    A recent interpretation of artificial intelligence (AI) (Floridi 2013, 2022) suggests that the implementation of AI demands the investigation of the binding conditions that make it possible to build and integrate artifacts into our lived world. Such artifacts can successfully interact with the world because our environment has been designed to be compatible with intelligent machines (such as robots). As the use of AI becomes ubiquitous in society, possibly leading to the formation of increasingly intelligent bio-technological unions, there will likely (...)
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  • Mind embedded or extended: transhumanist and posthumanist reflections in support of the extended mind thesis.Andrea Lavazza & Mirko Farina - 2022 - Synthese 200 (6):1-24.
    The goal of this paper is to encourage participants in the debate about the locus of cognition (e.g., extended mind vs embedded mind) to turn their attention to noteworthy anthropological and sociological considerations typically (but not uniquely) arising from transhumanist and posthumanist research. Such considerations, we claim, promise to potentially give us a way out of the stalemate in which such a debate has fallen. A secondary goal of this paper is to impress trans and post-humanistically inclined readers to embrace (...)
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  • Filter Bubbles and the Unfeeling: How AI for Social Media Can Foster Extremism and Polarization.Ermelinda Rodilosso - 2024 - Philosophy and Technology 37 (2):1-21.
    Social media have undoubtedly changed our ways of living. Their presence concerns an increasing number of users (over 4,74 billion) and pervasively expands in the most diverse areas of human life. Marketing, education, news, data, and sociality are just a few of the many areas in which social media play now a central role. Recently, some attention toward the link between social media and political participation has emerged. Works in the field of artificial intelligence have already pointed out that there (...)
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  • Machine learning in human creativity: status and perspectives.Mirko Farina, Andrea Lavazza, Giuseppe Sartori & Witold Pedrycz - 2024 - AI and Society 39 (6):3017-3029.
    As we write this research paper, we notice an explosion in popularity of machine learning in numerous fields (ranging from governance, education, and management to criminal justice, fraud detection, and internet of things). In this contribution, rather than focusing on any of those fields, which have been well-reviewed already, we decided to concentrate on a series of more recent applications of deep learning models and technologies that have only recently gained significant track in the relevant literature. These applications are concerned (...)
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  • The case for a broader approach to AI assurance: addressing “hidden” harms in the development of artificial intelligence.Christopher Thomas, Huw Roberts, Jakob Mökander, Andreas Tsamados, Mariarosaria Taddeo & Luciano Floridi - forthcoming - AI and Society:1-16.
    Artificial intelligence (AI) assurance is an umbrella term describing many approaches—such as impact assessment, audit, and certification procedures—used to provide evidence that an AI system is legal, ethical, and technically robust. AI assurance approaches largely focus on two overlapping categories of harms: deployment harms that emerge at, or after, the point of use, and individual harms that directly impact a person as an individual. Current approaches generally overlook upstream collective and societal harms associated with the development of systems, such as (...)
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  • Balancing AI and academic integrity: what are the positions of academic publishers and universities?Bashar Haruna Gulumbe, Shuaibu Muhammad Audu & Abubakar Muhammad Hashim - forthcoming - AI and Society:1-10.
    This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...)
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  • Personal AI, deception, and the problem of emotional bubbles.Philip Maxwell Thingbø Mlonyeni - forthcoming - AI and Society:1-12.
    Personal AI is a new type of AI companion, distinct from the prevailing forms of AI companionship. Instead of playing a narrow and well-defined social role, like friend, lover, caretaker, or colleague, with a set of pre-determined responses and behaviors, Personal AI is engineered to tailor itself to the user, including learning to mirror the user’s unique emotional language and attitudes. This paper identifies two issues with Personal AI. First, like other AI companions, it is deceptive about the presence of (...)
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  • Machine Learning in Society: Prospects, Risks, and Benefits.Mirko Farina & Witold Pedrycz - 2024 - Philosophy and Technology 37 (3):1-8.
    Machine Learning (ML) is revolutionizing the functioning of our societies and reshaping much of the economic tissue underlying them. The deep integration of ML into the fabric of our lives has changed to way we work and communicate and how we relate to each other. In this Topical Collection we reflect on the reach and impact of this AI (ML-driven) revolution in our society, critically analyzing some of the most important ethical, epistemological, scientific, and sociological issues underlying it.
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  • From liability gaps to liability overlaps: shared responsibilities and fiduciary duties in AI and other complex technologies.Bart Custers, Henning Lahmann & Benjamyn I. Scott - forthcoming - AI and Society:1-16.
    Complex technologies such as Artificial Intelligence (AI) can cause harm, raising the question of who is liable for the harm caused. Research has identified multiple liability gaps (i.e., unsatisfactory outcomes when applying existing liability rules) in legal frameworks. In this paper, the concepts of shared responsibilities and fiduciary duties are explored as avenues to address liability gaps. The development, deployment and use of complex technologies are not clearly distinguishable stages, as often suggested, but are processes of cooperation and co-creation. At (...)
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  • Is Generative AI Possible Cause of the Swan Song of the Rational Civilisation?Łukasz Mścisławski - 2024 - Studies in Logic, Grammar and Rhetoric 69 (1):441-455.
    Despite the many successes of generative AI, a number of fundamental questions have begun to arise around this technology. There is undoubtedly an interesting situation from a philosophical point of view. It can be carefully assumed that contemporary digital information processing technologies have arisen inside a circle of civilisation, one of the foundations of which is the classical account of truth. This account, even if seen as ideal and absolute, nevertheless seems to be a driving force in the field of (...)
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  • Why you Should not use CI to Evaluate Socially Disruptive Technology.Alexandra Prégent - 2025 - Philosophy and Technology 38 (6):1-19.
    Contextual Integrity (CI) is built to assess potential privacy violations of new sociotechnical systems and practices. It does so by evaluating their respect for the context-relative informational norms at play in a given context. But can CI evaluate new sociotechnical systems that severely disrupt established social practices? In this paper, I argue that, while CI claims to be able to assess privacy violations of all sociotechnical systems and practices, it cannot assess the ones that cause severe changes and disruptions in (...)
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