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  1. Exploring the data turn of philosophy of language in the era of big data.Shasha Xu & Qian Yang - 2024 - Trans/Form/Ação 47 (4):e0240050.
    La raccolta di dati nella nostra era dell’”Information Technology” ha generato una rivoluzione nella conoscenza. Nell’era dei “big data”, la conseguente crescita senza precedenti dei dati, ha reso necessari cambiamenti nella scala, nella natura e nello stato dei dati, portando quindi i ricercatori ad adottare nuovi paradigmi e metodologie nella ricerca filosofica. In particolare, l’attenzione teorica della filosofia del linguaggio si è spostata verso la conoscenza cognitiva, con un’enfasi sulla proposizione particolare del “data turn” nella cognizione cognitiva nell’era dei “big (...)
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  • Prediction via Similarity: Biomedical Big Data and the Case of Cancer Models.Giovanni Valente, Giovanni Boniolo & Fabio Boniolo - 2023 - Philosophy and Technology 36 (1):1-20.
    In recent years, the biomedical field has witnessed the emergence of novel tools and modelling techniques driven by the rise of the so-called Big Data. In this paper, we address the issue of predictability in biomedical Big Data models of cancer patients, with the aim of determining the extent to which computationally driven predictions can be implemented by medical doctors in their clinical practice. We show that for a specific class of approaches, called k-Nearest Neighbour algorithms, the ability to draw (...)
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  • To Each Technology Its Own Ethics: The Problem of Ethical Proliferation.Henrik Skaug Sætra & John Danaher - 2022 - Philosophy and Technology 35 (4):1-26.
    Ethics plays a key role in the normative analysis of the impacts of technology. We know that computers in general and the processing of data, the use of artificial intelligence, and the combination of computers and/or artificial intelligence with robotics are all associated with ethically relevant implications for individuals, groups, and society. In this article, we argue that while all technologies are ethically relevant, there is no need to create a separate ‘ethics of X’ or ‘X ethics’ for each and (...)
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  • Ethical Redress of Racial Inequities in AI: Lessons from Decoupling Machine Learning from Optimization in Medical Appointment Scheduling.Robert Shanklin, Michele Samorani, Shannon Harris & Michael A. Santoro - 2022 - Philosophy and Technology 35 (4):1-19.
    An Artificial Intelligence algorithm trained on data that reflect racial biases may yield racially biased outputs, even if the algorithm on its own is unbiased. For example, algorithms used to schedule medical appointments in the USA predict that Black patients are at a higher risk of no-show than non-Black patients, though technically accurate given existing data that prediction results in Black patients being overwhelmingly scheduled in appointment slots that cause longer wait times than non-Black patients. This perpetuates racial inequity, in (...)
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