The complex issue of fake news has been approached extensively by many disciplines in academia. Despite this variety of approaches, the concept of fake news still lacks a reasonable degree of definitional unicity. This paper critically analyzes a sample of definitions from the current literature. By diving into the set of definitions, it will exhibited a total of ten necessary conditions that scholars generally consider: imitation, falsity, deception, bullshit, purpose, morality, assessability, virality, channel, and appeal. Current definitions of fake news (...) have certain blindspots and leave too much leeway for interpretation. This leeway is utterly problematic because it creates a grey zone in which articles are left stranded halfway between fake news and factual news articles. However, it has the crucial advantage of opening up new epistemic paths of inquiry regarding fake news. As a conclusion, we will summarize the conditions one can accept or reject to define fake news. (shrink)

Since its emergence in the 1960s, Artifcial Intelligence (AI) has grown to conquer many technology products and their felds of application. Machine learning, as a major part of the current AI solutions, can learn from the data and through experience to reach high performance on various tasks. This growing success of AI algorithms has led to a need for interpretability to understand opaque models such as deep neural networks. Various requirements have been raised from diferent domains, together with numerous tools (...) to debug, justify outcomes, and establish the safety, fairness and reliability of the models. This variety of tasks has led to inconsistencies in the terminology with, for instance, terms such as interpretable, explainable and transparent being often used interchangeably in methodology papers. These words, however, convey diferent meanings and are “weighted" diferently across domains, for example in the technical and social sciences. In this paper, we propose an overarching terminology of interpretability of AI systems that can be referred to by the technical developers as much as by the social sciences community to pursue clarity and efciency in the defnition of regulations for ethical and reliable AI development. We show how our taxonomy and defnition of interpretable AI difer from the ones in previous research and how they apply with high versatility to several domains and use cases, proposing a—highly needed—standard for the communication among interdisciplinary areas of AI. (shrink)

Digital privacy scholars tend to bemoan ordinary people’s limited knowledge of and lukewarm interest in what happens to their digital data. This general lack of interest and knowledge is often taken as a consideration in favor of legislation aiming to force internet companies into adopting more responsible data practices. While we remain silent on whether any new laws are called for, in this paper we wish to underline a neglected consequence of people’s ignorance of and apathy for digital privacy: their (...) potential to encourage capture by industry interests. In particular, we argue that such laws may be at increased risk of capture because they are unlikely to be democratically responsive. We make this claim on a twofold basis: first, well-known theoretical mechanisms explaining how the absence of responsiveness leads to capture, identified in prior political science and political philosophy literature, yield the prediction that digital privacy legislation is likely to be unresponsive and thus captured; second, empirical data concerning the European Union’s digital privacy laws, with a special focus on the General Data Protection Regulation, appears to confirm these predictions: the bloc’s (world’s?) flagship privacy protection law seems more responsive to corporate than citizen interests. (shrink)

This paper argues, against the prevailing view, that consent to privacy policies that regular internet users usually give is largely unproblematic from the moral point of view. To substantiate this claim, we rely on the idea of the right not to know (RNTK), as developed by bioethicists. Defenders of the RNTK in bioethical literature on informed consent claim that patients generally have the right to refuse medically relevant information. In this article we extend the application of the RNTK to online (...) privacy. We then argue that if internet users can be thought of as exercising their RNTK before consenting to privacy policies, their consent ought to be considered free of the standard charges leveled against it by critics. (shrink)

This article argues that Rousseau's endorsement of male domination and his illiberal views of rape, punishment and the education of women have been seriously underestimated by twentieth century commentators who tend to produce expoisitions of his work that evade, ignore or marginalise this 'darker side' of his educational philosophy.