Philosophy & Technology

Branching Is Not a Bug; It's a Feature: Personal Identity and Legal (and Moral) Responsibility Abstract Prospective developments in computer and nanotechnology suggest that there is some possibility—perhaps as early as this century—that we will have the technological means to attempt to duplicate people. For example, it has been speculated that the psychology of individuals might be emulated on a computer platform to create a personality duplicate—an "upload." Physical duplicates might be created by advanced nanobots tasked with creating molecule-for-molecule copies of individuals. Such possibilities are discussed in the philosophical literature as (putative) cases of "fission": one person "splitting" into two. Many philosophers, perhaps most, reject the idea of fission, appealing to some form of a "no-branching" condition to rule out such possibilities. I argue, to the contrary, that there are good moral reasons to think that any account of personal identity that does not permit fission is deeply problematic, especially in connection with theorizing about criminal punishment. I discuss and reject David Lewis' famous account of personal identity that invokes "multiple occupancy" to allow for branching. In contrast, I offer an account of personal identity that permits branching using the type/token distinction to help with such puzzling cases.

Dark Data as the New Challenge for Big Data Science and the Introduction of the Scientific Data Officer Abstract Many studies in big data focus on the uses of data available to researchers, leaving without treatment data that is on the servers but of which researchers are unaware. We call this dark data, and in this article, we present and discuss it in the context of high-performance computing (HPC) facilities. To this end, we provide statistics of a major HPC facility in Europe, the High-Performance Computing Center Stuttgart (HLRS). We also propose a new position tailor-made for coping with dark data and general data management. We call it the scientific data officer (SDO) and we distinguish it from other standard positions in HPC facilities such as chief data officers, system administrators, and security officers. In order to understand the role of the SDO in HPC facilities, we discuss two kinds of responsibilities, namely, technical responsibilities and ethical responsibilities. While the former are intended to characterize the position, the latter raise concerns—and proposes solutions—to the control and authority that the SDO would acquire.

The Ethics of Biomedical 'Big Data' Analytics

The Digital Phenotype: a Philosophical and Ethical Exploration Abstract The concept of the digital phenotype has been used to refer to digital data prognostic or diagnostic of disease conditions. Medical conditions may be inferred from the time pattern in an insomniac's tweets, the Facebook posts of a depressed individual, or the web searches of a hypochondriac. This paper conceptualizes digital data as an extended phenotype of humans, that is as digital information produced by humans and affecting human behavior and culture. It argues that there are ethical obligations to persons affected by generalizable knowledge of a digital phenotype, not only those who are personally identifiable or involved in data generation. This claim is illustrated by considering the health-related digital phenotypes of precision medicine and digital epidemiology.

What the Near Future of Artificial Intelligence Could Be

The Challenge of the Digital and the Future Archive: Through the Lens of The National Archives UK Abstract On the 7th of June 2018, The National Archives UK held its inaugural digital lecture, delivered by Professor Luciano Floridi entitled "Semantic Capital: What it is and how to protect it". The lecture was followed by a poster exhibition, showcasing nine cutting-edge digital research projects at The National Archives (You can listen to the lecture's podcast and see the posters at: https://media.nationalarchives.gov.uk/index.php/digital-lecture-semantic-capital/ Accessed on 12 July 2018). This paper aims at giving a distinct overview of The National Archives' digital research priorities, drawing on examples from the active and recently completed research projects, which were displayed at the exhibition on the 7th of June 2018. The focus of this paper is to discuss the research challenges that we are facing as we seek to become a second-generation digital archive, that is digital by instinct and design. By placing a particular emphasis on the conceptual and epistemological challenges relating to trust and openness, the paper suggests that research is the key for us as a rapidly evolving digital archive; enabling us not only to inform but also innovate around the forthcoming digital challenges, and helping us to define future directions and lead the shaping of the future archive.

Accessing Online Data for Youth Mental Health Research: Meeting the Ethical Challenges Abstract This article addresses the general ethical issues of accessing online personal data for research purposes. The authors discuss the practical aspects of online research with a specific case study that illustrates the ethical challenges encountered when accessing data from Kooth, an online youth web-counselling service. This paper firstly highlights the relevance of a process-based approach to ethics (Markham and Buchanan 2012) when accessing highly sensitive data and then discusses the ethical considerations and potential challenges regarding the accessing of public data from Digital Mental Health (DMH) services. It presents solutions that aim to protect young DMH service users as well as the DMH providers and researchers mining such data. Special consideration is given to service users' expectations of what their data might be used for, as well as their perceptions of whether the data they post is public, private or open. We provide recommendations for planning and designing online research that includes vulnerable young people as research participants in an ethical manner. We emphasise the distinction between public, private and open data, which is crucial to comprehend the ethical challenges in accessing DMH data. Among our key recommendations, we foreground the need to consider a collaborative approach with the DMH providers while respecting service users' control over personal data, and we propose the implementation of digital solutions embedded within the platform for explicit opt-out/opt-in recruitment strategies and 'read more' options (Bergin and Harding 2016).

Between Minimal and Greater Than Minimal Risk: How Research Participants and Oncologists Assess Data-Sharing and the Risk of Re-identification in Genomic Research Abstract Data-sharing among genomic researchers is promoted for its potential to accelerate our understanding of the molecular basis of cancer. However, with genomic data sharing the risks of re-identifying study participants, revealing personal genomic information and data misuse might increase. This study aims at exploring perceptions of patients and physicians in Oncology regarding their assessment of the informational risks resulting from participating in whole genomic research studies in order to improve the informed consent process. For this purpose, we conducted a qualitative focus group study at the National Center for Tumor Diseases (NCT). Patients and oncologists assessed the informational risks either as minimal or as greater than minimal, depending on the context factors of occupational status, age, and patients' prognosis. Interestingly, even patients who assumed a greater risk did not refrain from participating in genomic research, provided that certain informational and institutional safeguards are implemented. Moreover, they expected comprehensive disclosure of the risks resulting from genomic data sharing. These results suggest (1) comprehensive disclosure of the risks of genomic research to potential study participants in genomic research to facilitate risk assessment and sound decision making, (2) establishing independent governance entities in order to minimize the informational risks of genomic research, and (3) implementing data sharing policies which offer guidance for physicians and researchers involved in genomic research.

Trust and Justice in Big Data Analytics: Bringing the Philosophical Literature on Trust to Bear on the Ethics of Consent Abstract Much bioethical literature and policy guidances for big data analytics in biomedical research emphasize the importance of trust. It is essential that potential participants trust so they will allow their data to be used to further research. However, comparatively, little guidance is offered as to what trustworthy oversight mechanisms are, or how policy should support them, as data are collected, shared, and used. Generally, "trust" is not characterized well enough, or meaningfully enough, for the term to be systematically applied in policy development. Yet points made in the philosophical literature on trust can help. They allow us, not only to better distinguish the different ways the term "trust" may be interpreted, but also to better determine how different approaches to trust can align with policy and governance—in what ways they may relate to key bioethical concepts and related laws, and in what ways they can help to balance individual and group interests in data sharing. This article draws from the philosophical literature on trust to identify a relationship among consent, trust, and justice. Specifically, parallels are drawn between "character-trustworthiness" and "natural justice," a set of widely held legal safeguards intended to ensure decision-makers follow a pattern of procedural fairness which protects the rights of the individual and thereby maintains public confidence in the decision-making process. Relevance to traditional bioethical principles, established laws, and consent procedures are addressed throughout. In conclusion, policy actions are suggested.

Social Justice, Equality and Primary Care: (How) Can 'Big Data' Help? Abstract A growing body of research emphasises the role of 'social determinants of health' in generating inequalities in health outcomes. How, if at all, should primary care providers respond? In this paper, I want to shed light on this issue by focusing on the role that 'big data' might play in allowing primary care providers to respond to the social determinants that affect individual patients' health. The general idea has been proposed and endorsed by the Institute of Medicine, and the idea has been developed in more detail by Bazemore et al. (2016). In Bazemore et al.'s proposal, patients' addresses are used to generate information about the patients' neighbourhood; this information is then included in patients' health care records and made available to providers. This allows primary care providers to take this information into account when interacting with, and providing care to, patients. I explore three issues arising from this proposal. First, while questions of privacy have been central to discussions about big data, Bazemore et al.'s proposal also allows us to see that there might be costs to not making certain information available. Second, I consider some of the questions arising for primary care from the influence of social factors on health outcomes: given that we know these factors to be significant contributors to social inequalities in health, what precisely should be done about this in the primary care context? Finally, I address problems arising from the use of population level data when dealing with individuals.