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  1. Fairer Machine Learning in the Real World: Mitigating Discrimination Without Collecting Sensitive Data.Reuben Binns & Michael Veale - 2017 - Big Data and Society 4 (2).
    Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such (...)
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  • Of ‘Black Boxes’ and Algorithmic Decision-Making in (Higher) Education – A Commentary.Paul Prinsloo - 2020 - Big Data and Society 7 (1).
    Higher education institutions have access to higher volumes and a greater variety and granularity of student data, often in real-time, than ever before. As such, the collection, analysis and use of student data are increasingly crucial in operational and strategic planning, and in delivering appropriate and effective learning experiences to students. Student data – not only in what data is collected, but also how the data is framed and used – has material and discursive effects, both permanent and fleeting. We (...)
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  • The Old in the New: Voter Surveillance in Political Clientelism and Datafied Campaigning.Isabel Kusche - 2020 - Big Data and Society 7 (1).
    This article compares political clientelism and datafied campaigning as two modes of relating politicians/parties and voters that are centred around voter surveillance. It contributes to the discussion on consequences of Big Data by showing similarities of datafied campaigns with a type of electoral politics that pre-dates the advent of mass media and is usually regarded as deficient. It thus departs from the predominant perspective on datafication and surveillance, which draws on Foucault, in order to identify the particular challenges that datafication (...)
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  • Artificial virtue: the machine question and perceptions of moral character in artificial moral agents.Patrick Gamez, Daniel B. Shank, Carson Arnold & Mallory North - 2020 - AI and Society 35 (4):795-809.
    Virtue ethics seems to be a promising moral theory for understanding and interpreting the development and behavior of artificial moral agents. Virtuous artificial agents would blur traditional distinctions between different sorts of moral machines and could make a claim to membership in the moral community. Accordingly, we investigate the “machine question” by studying whether virtue or vice can be attributed to artificial intelligence; that is, are people willing to judge machines as possessing moral character? An experiment describes situations where either (...)
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  • “Strongly Recommended” Revisiting Decisional Privacy to Judge Hypernudging in Self-Tracking Technologies.Marjolein Lanzing - 2019 - Philosophy and Technology 32 (3):549-568.
    This paper explores and rehabilitates the value of decisional privacy as a conceptual tool, complementary to informational privacy, for critiquing personalized choice architectures employed by self-tracking technologies. Self-tracking technologies are promoted and used as a means to self-improvement. Based on large aggregates of personal data and the data of other users, self-tracking technologies offer personalized feedback that nudges the user into behavioral change. The real-time personalization of choice architectures requires continuous surveillance and is a very powerful technology, recently coined as (...)
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  • Dissecting the Algorithmic Leviathan: On the Socio-Political Anatomy of Algorithmic Governance.Pascal D. König - 2020 - Philosophy and Technology 33 (3):467-485.
    A growing literature is taking an institutionalist and governance perspective on how algorithms shape society based on unprecedented capacities for managing social complexity. Algorithmic governance altogether emerges as a novel and distinctive kind of societal steering. It appears to transcend established categories and modes of governance—and thus seems to call for new ways of thinking about how social relations can be regulated and ordered. However, as this paper argues, despite its novel way of realizing outcomes of collective steering and coordination, (...)
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  • Ethical Decision Making in Autonomous Vehicles: The AV Ethics Project.Katherine Evans, Nelson de Moura, Stéphane Chauvier, Raja Chatila & Ebru Dogan - forthcoming - Science and Engineering Ethics:1-28.
    The ethics of autonomous vehicles has received a great amount of attention in recent years, specifically in regard to their decisional policies in accident situations in which human harm is a likely consequence. Starting from the assumption that human harm is unavoidable, many authors have developed differing accounts of what morality requires in these situations. In this article, a strategy for AV decision-making is proposed, the Ethical Valence Theory, which paints AV decision-making as a type of claim mitigation: different road (...)
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  • Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life.John Danaher - 2017 - Science and Engineering Ethics 23 (1):41-64.
    Suppose we are about to enter an era of increasing technological unemployment. What implications does this have for society? Two distinct ethical/social issues would seem to arise. The first is one of distributive justice: how will the efficiency gains from automated labour be distributed through society? The second is one of personal fulfillment and meaning: if people no longer have to work, what will they do with their lives? In this article, I set aside the first issue and focus on (...)
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  • The Ghost in the Legal Machine: Algorithmic Governmentality, Economy, and the Practice of Law.Adam Harkens - 2018 - Journal of Information, Communication and Ethics in Society 16 (1):16-31.
    Purpose This paper aims to investigate algorithmic governmentality – as proposed by Antoinette Rouvroy – specifically in relation to law. It seeks to show how algorithmic profiling can be particularly attractive for those in legal practice, given restraints on time and resources. It deviates from Rouvroy in two ways. First, it argues that algorithmic governmentality does not contrast with neoliberal modes of government in that it allows indirect rule through economic calculations. Second, it argues that critique of such systems is (...)
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  • An Evaluative Conservative Case for Biomedical Enhancement.John Danaher - 2016 - Journal of Medical Ethics 42 (9):611-618.
    It is widely believed that a conservative moral outlook is opposed to biomedical forms of human enhancement. In this paper, I argue that this widespread belief is incorrect. Using Cohen’s evaluative conservatism as my starting point, I argue that there are strong conservative reasons to prioritise the development of biomedical enhancements. In particular, I suggest that biomedical enhancement may be essential if we are to maintain our current evaluative equilibrium (i.e. the set of values that undergird and permeate our current (...)
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  • Behavioural Artificial Intelligence: An Agenda for Systematic Empirical Studies of Artificial Inference.Tore Pedersen & Christian Johansen - 2020 - AI and Society 35 (3):519-532.
    Artificial intelligence receives attention in media as well as in academe and business. In media coverage and reporting, AI is predominantly described in contrasted terms, either as the ultimate solution to all human problems or the ultimate threat to all human existence. In academe, the focus of computer scientists is on developing systems that function, whereas philosophy scholars theorize about the implications of this functionality for human life. In the interface between technology and philosophy there is, however, one imperative aspect (...)
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  • Algorithms and values in justice and security.Paul Hayes, Ibo van de Poel & Marc Steen - 2020 - AI and Society 35 (3):533-555.
    This article presents a conceptual investigation into the value impacts and relations of algorithms in the domain of justice and security. As a conceptual investigation, it represents one step in a value sensitive design based methodology. Here, we explicate and analyse the expression of values of accuracy, privacy, fairness and equality, property and ownership, and accountability and transparency in this context. We find that values are sensitive to disvalue if algorithms are designed, implemented or deployed inappropriately or without sufficient consideration (...)
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  • There Is No Techno-Responsibility Gap.Daniel W. Tigard - forthcoming - Philosophy and Technology:1-19.
    In a landmark essay, Andreas Matthias claimed that current developments in autonomous, artificially intelligent systems are creating a so-called responsibility gap, which is allegedly ever-widening and stands to undermine both the moral and legal frameworks of our society. But how severe is the threat posed by emerging technologies? In fact, a great number of authors have indicated that the fear is thoroughly instilled. The most pessimistic are calling for a drastic scaling-back or complete moratorium on AI systems, while the optimists (...)
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  • Ethics of Artificial Intelligence and Robotics.Vincent C. Müller - 2020 - In Edward Zalta (ed.), Stanford Encyclopedia of Philosophy. Palo Alto, Cal.: CSLI, Stanford University. pp. 1-70.
    Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...)
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  • Toward an Ethics of AI Assistants: An Initial Framework.John Danaher - 2018 - Philosophy and Technology 31 (4):629-653.
    Personal AI assistants are now nearly ubiquitous. Every leading smartphone operating system comes with a personal AI assistant that promises to help you with basic cognitive tasks: searching, planning, messaging, scheduling and so on. Usage of such devices is effectively a form of algorithmic outsourcing: getting a smart algorithm to do something on your behalf. Many have expressed concerns about this algorithmic outsourcing. They claim that it is dehumanising, leads to cognitive degeneration, and robs us of our freedom and autonomy. (...)
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  • The Computational Therapeutic: Exploring Weizenbaum’s ELIZA as a History of the Present.Caroline Bassett - 2019 - AI and Society 34 (4):803-812.
    This paper explores the history of ELIZA, a computer programme approximating a Rogerian therapist, developed by Jospeh Weizenbaum at MIT in the 1970s, as an early AI experiment. ELIZA’s reception provoked Weizenbaum to re-appraise the relationship between ‘computer power and human reason’ and to attack the ‘powerful delusional thinking’ about computers and their intelligence that he understood to be widespread in the general public and also amongst experts. The root issue for Weizenbaum was whether human thought could be ‘entirely computable’. (...)
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  • Why Internal Moral Enhancement Might Be Politically Better Than External Moral Enhancement.John Danaher - 2019 - Neuroethics 12 (1):39-54.
    Technology could be used to improve morality but it could do so in different ways. Some technologies could augment and enhance moral behaviour externally by using external cues and signals to push and pull us towards morally appropriate behaviours. Other technologies could enhance moral behaviour internally by directly altering the way in which the brain captures and processes morally salient information or initiates moral action. The question is whether there is any reason to prefer one method over the other? In (...)
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  • Algorithmic Accountability and Public Reason.Reuben Binns - 2018 - Philosophy and Technology 31 (4):543-556.
    The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...)
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