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Brent Mittelstadt [18]Brent Daniel Mittelstadt [3]
  1. The ethics of algorithms: mapping the debate.Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter & Luciano Floridi - 2016 - Big Data and Society 3 (2):2053951716679679.
    In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...)
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  2. Explaining Explanations in AI.Brent Mittelstadt - forthcoming - FAT* 2019 Proceedings 1.
    Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it’s important to remember Box’s maxim that "All models are wrong but some are useful." We focus on (...)
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  3. The ethics of big data: current and foreseeable issues in biomedical contexts.Brent Daniel Mittelstadt & Luciano Floridi - 2016 - Science and Engineering Ethics 22 (2):303–341.
    The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...)
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  4. Artificial intelligence and the ‘Good Society’: the US, EU, and UK approach.Corinne Cath, Sandra Wachter, Brent Mittelstadt, Mariarosaria Taddeo & Luciano Floridi - 2018 - Science and Engineering Ethics 24 (2):505-528.
    In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a ‘good (...)
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  5. Why a right to explanation of automated decision-making does not exist in the General Data Protection Regulation.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - International Data Privacy Law 1 (2):76-99.
    Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to the (...)
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  6. Transparent, explainable, and accountable AI for robotics.Sandra Wachter, Brent Mittelstadt & Luciano Floridi - 2017 - Science (Robotics) 2 (6):eaan6080.
    To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.
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  7.  2
    Principles alone cannot guarantee ethical AI.Brent Mittelstadt - 2019 - Nature Machine Intelligence 1 (11):501-507.
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  8. The Ethical Implications of Personal Health Monitoring.Brent Mittelstadt - 2014 - International Journal of Technoethics 5 (2):37-60.
    Personal Health Monitoring (PHM) uses electronic devices which monitor and record health-related data outside a hospital, usually within the home. This paper examines the ethical issues raised by PHM. Eight themes describing the ethical implications of PHM are identified through a review of 68 academic articles concerning PHM. The identified themes include privacy, autonomy, obtrusiveness and visibility, stigma and identity, medicalisation, social isolation, delivery of care, and safety and technological need. The issues around each of these are discussed. The system (...)
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  9. Ethics of the health-related internet of things: a narrative review.Brent Mittelstadt - 2017 - Ethics and Information Technology 19 (3):1-19.
    The internet of things is increasingly spreading into the domain of medical and social care. Internet-enabled devices for monitoring and managing the health and well-being of users outside of traditional medical institutions have rapidly become common tools to support healthcare. Health-related internet of things (H-IoT) technologies increasingly play a key role in health management, for purposes including disease prevention, real-time tele-monitoring of patient’s functions, testing of treatments, fitness and well-being monitoring, medication dispensation, and health research data collection. H-IoT promises many (...)
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  10. From Individual to Group Privacy in Big Data Analytics.Brent Mittelstadt - 2017 - Philosophy and Technology 30 (4):475-494.
    Mature information societies are characterised by mass production of data that provide insight into human behaviour. Analytics has arisen as a practice to make sense of the data trails generated through interactions with networked devices, platforms and organisations. Persistent knowledge describing the behaviours and characteristics of people can be constructed over time, linking individuals into groups or classes of interest to the platform. Analytics allows for a new type of algorithmically assembled group to be formed that does not necessarily align (...)
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  11.  43
    The Ethics of Biomedical ‘Big Data’ Analytics.Brent Mittelstadt - 2019 - Philosophy and Technology 32 (1):17-21.
  12. Designing the Health-related Internet of Things: Ethical Principles and Guidelines.Brent Mittelstadt - 2017 - Information 8 (3):77.
    The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be (...)
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  13.  73
    How to Shape a Better Future? Epistemic Difficulties for Ethical Assessment and Anticipatory Governance of Emerging Technologies.Brent Daniel Mittelstadt, Bernd Carsten Stahl & N. Ben Fairweather - 2015 - Ethical Theory and Moral Practice 18 (5):1027-1047.
    Empirical research into the ethics of emerging technologies, often involving foresight studies, technology assessment or application of the precautionary principle, raises significant epistemological challenges by failing to explain the relative epistemic status of contentious normative claims about future states. This weakness means that it is unclear why the conclusions reached by these approaches should be considered valid, for example in anticipatory ethical assessment or governance of emerging technologies. This paper explains and responds to this problem by proposing an account of (...)
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  14.  29
    Is there a duty to participate in digital epidemiology?Brent Mittelstadt, Justus Benzler, Lukas Engelmann, Barbara Prainsack & Effy Vayena - 2018 - Life Sciences, Society and Policy 14 (1):1-24.
    This paper poses the question of whether people have a duty to participate in digital epidemiology. While an implied duty to participate has been argued for in relation to biomedical research in general, digital epidemiology involves processing of non-medical, granular and proprietary data types that pose different risks to participants. We first describe traditional justifications for epidemiology that imply a duty to participate for the general public, which take account of the immediacy and plausibility of threats, and the identifiability of (...)
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  15.  28
    Near-term ethical challenges of digital twins.Brent Mittelstadt - 2021 - Journal of Medical Ethics 47 (6):405-406.
    In ‘Represent me: please! Towards an ethics of digital twins in medicine’,1 Braun analyses the potential for simulations of human organs and bodies, or ‘digital twins,’ to faithfully a person. Drawing from several French philosophers, he introduces ‘first conditions for digital twins to take on an ethically justifiable form of representation’.1 The analysis predominantly focuses on challenges that arise in terms of representation, embodiment, control by the patients after which the twin is modelled. Many challenges are posited on the existence (...)
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  16.  17
    Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it.Alice Liefgreen, Netta Weinstein, Sandra Wachter & Brent Mittelstadt - forthcoming - AI and Society:1-17.
    Artificial intelligence (AI) is increasingly relied upon by clinicians for making diagnostic and treatment decisions, playing an important role in imaging, diagnosis, risk analysis, lifestyle monitoring, and health information management. While research has identified biases in healthcare AI systems and proposed technical solutions to address these, we argue that effective solutions require human engagement. Furthermore, there is a lack of research on how to motivate the adoption of these solutions and promote investment in designing AI systems that align with values (...)
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  17.  13
    Protecting Health Privacy through Reasonable Inferences.Brent Mittelstadt - 2022 - American Journal of Bioethics 22 (7):65-68.
    In the digital age individuals face key choices about whether and how to share intimate details of their lives, “images of the body, biological data in general and diagnostic information” (Pyrrho,...
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  18.  9
    The Concentration-after-Personalisation Index (CAPI): Governing effects of personalisation using the example of targeted online advertising.Brent Mittelstadt, Sandra Wachter, Chris Russell, Fabian Stephany & Johann Laux - 2022 - Big Data and Society 9 (2).
    Firms are increasingly personalising their offers and services, leading to an ever finer-grained segmentation of consumers online. Targeted online advertising and online price discrimination are salient examples of this development. While personalisation's overall effects on consumer welfare are expectably ambiguous, it can lead to concentration in the distribution of advertising and commercial offers. Constellations are possible in which a market is generally open to competition, but the targeted consumer is only made aware of one possible seller. For the consumer, such (...)
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  19.  14
    Epistemic fragmentation poses a threat to the governance of online targeting.Silvia Milano, Brent Mittelstadt, Sandra Wachter & Christopher Russell - 2021 - Nature Machine Intelligence 3 (June 2021):466–472.
    Online targeting isolates individual consumers, causing what we call epistemic fragmentation. This phenomenon amplifies the harms of advertising and inflicts structural damage to the public forum. The two natural strategies to tackle the problem of regulating online targeted advertising, increasing consumer awareness and extending proactive monitoring, fail because even sophisticated individual consumers are vulnerable in isolation, and the contextual knowledge needed for effective proactive monitoring remains largely inaccessible to platforms and external regulators. The limitations of both consumer awareness and of (...)
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  20. Legitimate Power, Illegitimate Automation: The problem of ignoring legitimacy in automated decision systems.Jake Iain Stone & Brent Mittelstadt - forthcoming - The Association for Computing Machinery Conference on Fairness, Accountability, and Transparency 2024.
    Progress in machine learning and artificial intelligence has spurred the widespread adoption of automated decision systems (ADS). An extensive literature explores what conditions must be met for these systems' decisions to be fair. However, questions of legitimacy -- why those in control of ADS are entitled to make such decisions -- have received comparatively little attention. This paper shows that when such questions are raised theorists often incorrectly conflate legitimacy with either public acceptance or other substantive values such as fairness, (...)
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  21.  3
    The Ethics of Biomedical Big Data.Luciano Floridi & Brent Daniel Mittelstadt (eds.) - 2016 - Cham: Imprint: Springer.
    This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. 'Biomedical Big Data' refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address (...)
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