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Brent Mittelstadt
Oxford University
  1. 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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  2. 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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  3. The Ethics of Algorithms: Mapping the Debate.Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter & Luciano Floridi - 2016 - Big Data and Society 3 (2).
    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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  4. The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts.Brent 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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  5. 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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    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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    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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    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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    How to Shape a Better Future? Epistemic Difficulties for Ethical Assessment and Anticipatory Governance of Emerging Technologies.Brent 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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    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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