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  1. Autonomous Vehicles: From Whether and When to Where and How.Luciano Floridi - 2019 - Philosophy and Technology 32 (4):569-573.
    The digital revolution, in the form of autonomous driving, is changing the very essence of mobility. This paper discusses four different ways in which these transformations are taking place and argues that public policies and business strategies need to focus on innovating and re-engineering (enveloping) whole environments. Only then will autonomous vehicles become an ordinary – and environmentally sustainable – reality. -/- .
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  • AI and its New Winter: From Myths to Realities.Luciano Floridi - 2020 - Philosophy and Technology 33 (1):1-3.
    An AI winter may be defined as the stage when technology, business, and the media come to terms with what AI can or cannot really do as a technology without exaggeration. Through discussion of previous AI winters, this paper examines the hype cycle (which by turn characterises AI as a social panacea or a nightmare of apocalyptic proportions) and argues that AI should be treated as a normal technology, neither as a miracle nor as a plague, but rather as of (...)
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  • The Ethics of Algorithms: Key Problems and Solutions.Andreas Tsamados, Nikita Aggarwal, Josh Cowls, Jessica Morley, Huw Roberts, Mariarosaria Taddeo & Luciano Floridi - 2021 - AI and Society.
    Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016, 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative (...)
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  • Artificial Intelligence Methods for a Bayesian Epistemology‐Powered Evidence Evaluation.Francesco De Pretis, Jürgen Landes & William Peden - 2021 - Journal of Evaluation in Clinical Practice 27 (3):504-512.
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  • Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective.Erik Hermann - forthcoming - Journal of Business Ethics:1-19.
    Artificial intelligence is shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To (...)
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  • A Moral Analysis of Intelligent Decision-Support Systems in Diagnostics Through the Lens of Luciano Floridi’s Information Ethics.Dmytro Mykhailov - 2021 - Human Affairs 31 (2):149-164.
    Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine (...)
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  • Automated news recommendation in front of adversarial examples and the technical limits of transparency in algorithmic accountability.Antonin Descampe, Clément Massart, Simon Poelman, François-Xavier Standaert & Olivier Standaert - forthcoming - AI and Society:1-14.
    Algorithmic decision making is used in an increasing number of fields. Letting automated processes take decisions raises the question of their accountability. In the field of computational journalism, the algorithmic accountability framework proposed by Diakopoulos formalizes this challenge by considering algorithms as objects of human creation, with the goal of revealing the intent embedded into their implementation. A consequence of this definition is that ensuring accountability essentially boils down to a transparency question: given the appropriate reverse-engineering tools, it should be (...)
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  • Recommendation Algorithms, a Neglected Opportunity for Public Health.Lê Nguyên Hoang, Louis Faucon & El-Mahdi El-Mhamdi - 2021 - Revue Médecine et Philosophie 4 (2):16-24.
    The public discussion on artificial intelligence for public health often revolves around future applications like drug discovery or personalized medicine. But already deployed artificial intelligence for content recommendation, especially on social networks, arguably plays a far greater role. After all, such algorithms are used on a daily basis by billions of users worldwide. In this paper, we argue that, left unchecked, this enormous influence of recommendation algorithms poses serious risks for public health, e.g., in terms of misinformation and mental health. (...)
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  • Artificial Intelligence in Cyber Physical Systems.Petar Radanliev, David De Roure, Max Van Kleek, Omar Santos & Uchenna Ani - forthcoming - AI and Society:1-14.
    This article conducts a literature review of current and future challenges in the use of artificial intelligence in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in (...)
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