50,381 research outputs found

    Language (Technology) is Power: A Critical Survey of "Bias" in NLP

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    We survey 146 papers analyzing "bias" in NLP systems, finding that their motivations are often vague, inconsistent, and lacking in normative reasoning, despite the fact that analyzing "bias" is an inherently normative process. We further find that these papers' proposed quantitative techniques for measuring or mitigating "bias" are poorly matched to their motivations and do not engage with the relevant literature outside of NLP. Based on these findings, we describe the beginnings of a path forward by proposing three recommendations that should guide work analyzing "bias" in NLP systems. These recommendations rest on a greater recognition of the relationships between language and social hierarchies, encouraging researchers and practitioners to articulate their conceptualizations of "bias"---i.e., what kinds of system behaviors are harmful, in what ways, to whom, and why, as well as the normative reasoning underlying these statements---and to center work around the lived experiences of members of communities affected by NLP systems, while interrogating and reimagining the power relations between technologists and such communities

    Evaluating the Revisionist Critique of Just War Theory

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    Modern analytical just war theory starts with Michael Walzer's defense of key tenets of the laws of war in his Just and Unjust Wars. Walzer advocates noncombatant immunity, proportionality, and combatant equality: combatants in war must target only combatants; unintentional harms that they inflict on noncombatants must be proportionate to the military objective secured; and combatants who abide by these principles fight permissibly, regardless of their aims. In recent years, the revisionist school of just war theory, led by Jeff McMahan, has radically undermined Walzer's defense of these principles. This essay situates Walzer's and the revisionists’ arguments, before illustrating the disturbing vision of the morality of war that results from revisionist premises. It concludes by showing how broadly Walzerian conclusions can be defended using more reliable foundations

    Responsible Data Governance of Neuroscience Big Data

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    Open access article.Current discussions of the ethical aspects of big data are shaped by concerns regarding the social consequences of both the widespread adoption of machine learning and the ways in which biases in data can be replicated and perpetuated. We instead focus here on the ethical issues arising from the use of big data in international neuroscience collaborations. Neuroscience innovation relies upon neuroinformatics, large-scale data collection and analysis enabled by novel and emergent technologies. Each step of this work involves aspects of ethics, ranging from concerns for adherence to informed consent or animal protection principles and issues of data re-use at the stage of data collection, to data protection and privacy during data processing and analysis, and issues of attribution and intellectual property at the data-sharing and publication stages. Significant dilemmas and challenges with far-reaching implications are also inherent, including reconciling the ethical imperative for openness and validation with data protection compliance and considering future innovation trajectories or the potential for misuse of research results. Furthermore, these issues are subject to local interpretations within different ethical cultures applying diverse legal systems emphasising different aspects. Neuroscience big data require a concerted approach to research across boundaries, wherein ethical aspects are integrated within a transparent, dialogical data governance process. We address this by developing the concept of “responsible data governance,” applying the principles of Responsible Research and Innovation (RRI) to the challenges presented by the governance of neuroscience big data in the Human Brain Project (HBP)

    Injecting equipment schemes for injecting drug users : qualitative evidence review

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    This review of the qualitative literature about needle and syringe programmes (NSPs) for injecting drug users (IDUs) complements the review of effectiveness and cost-effectiveness. It aims to provide a more situated narrative perspective on the overall guidance questions

    The Ethics of Resisting Deportation

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    Can anti-deportation resistance be justified, and if so how and by whom may, or perhaps should, unjust deportations be resisted? In this paper, I seek to provide an answer to these questions. The paper starts by describing the main forms and agents of anti-deportation action in the contemporary context. Subsequently, I examine how different justifications for principled resistance and disobedience may each be invoked in the case of deportation resistance. I then explore how worries about the resister’s motivation for engaging in the action and their epistemic position apply in the specific context of anti-deportation action and consider in what circumstances there is not merely a right but a duty to resist deportation. The upshot of this argument, I conclude, is that the liberal state ought to respond to anti-deportation action not by criminalising disobedience and resistance in this field, but rather by creating legal avenues for such actors to influence deportation decision-making. DOI 10.17879/95189423213

    A qualitative study of stakeholders' perspectives on the social network service environment

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    Over two billion people are using the Internet at present, assisted by the mediating activities of software agents which deal with the diversity and complexity of information. There are, however, ethical issues due to the monitoring-and-surveillance, data mining and autonomous nature of software agents. Considering the context, this study aims to comprehend stakeholders' perspectives on the social network service environment in order to identify the main considerations for the design of software agents in social network services in the near future. Twenty-one stakeholders, belonging to three key stakeholder groups, were recruited using a purposive sampling strategy for unstandardised semi-structured e-mail interviews. The interview data were analysed using a qualitative content analysis method. It was possible to identify three main considerations for the design of software agents in social network services, which were classified into the following categories: comprehensive understanding of users' perception of privacy, user type recognition algorithms for software agent development and existing software agents enhancement
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