Brent Mittelstadt, Oxford Internet Institute, University of Oxford
In biomedical research, the analysis of large datasets (Big Data) has become a major driver of innovation and success. Data analytics provides huge opportunities to improve private and public life, especially in the health sector (biomedical data analytics, henceforth BDA). Machine learning and algorithmic categorisation can increasingly make sense of the seemingly endless data emerging from sensors, wearable devices, clinical observations, clinical trials, social and online platforms which provide insight into the behaviours and physiology of individuals.
BDA is expected to provide new ways of understanding health and well-being at the level of the individual and society, for example by predicting behaviours, monitoring diseases and outbreaks, and providing risk stratification for individual patients. Epidemiology, infectious disease research, and genomics and genetics are already deeply affected. Such a potentially highly positive impact is coupled to significant ethical challenges. The extensive use of increasingly more data (Big Data), the growing reliance on algorithms to analyse them and to reach decisions (machine learning), as well as the gradual reduction of human oversight over many automatic processes pose pressing issues of fairness, responsibility, and respect of human rights.
These issues can be addressed successfully. However, if they are overlooked, underestimated or left unresolved, they risk hindering the innovation and the progress that BDA can bring to society at large and to future generations. Furthermore, as recent events involving the NHS care.data programme show, BDA projects may face a double bottleneck: ethical mistakes or misunderstandings may lead to social rejection and/or distorted legislation and policies, which in turn may cripple the acceptance and advancement of data science. Clearly, ethical analysis should be incorporated at all stages of any BDA project and since the beginning, in order to understand impact, anticipate risks of unethical consequences, suggest early interventions to avoid or mitigate them, foster resilience, reinforce ethical goals and outcomes, and ensure that ethical best practices are developed, implemented, and appreciated.
To contribute to this critical step, this special issue of Philosophy and Technology aims to map new, under-researched but important issues, concepts and cases that should inform proactive ethical assessment of emerging BDA applications and services.
We request the submission of research articles addressing topics including:
- Theories and concepts critical to the ethical assessment of BDA in particular
- Required modifications to informed consent in response to the scale and complexity of BDA
- Alternatives to informed consent for BDA governance
- Challenges introduced by the opacity and complexity of BDA methods, particularly deep learning, neural networks and similar methods
- Group-level protections, harms and benefits
- Ethical principles for governance of BDA platforms
- Applicability of traditional medical research ethics principles to BDA
- Privacy, de-identification and research subject rights to data access
- Ownership of intellectual property generated from BDA
- Uses of BDA for empowerment or improvement of patient experiences
- Implications of data-intensive clinical experiences for the doctor-patient relationship
- Implications of the crossover between personal health devices and BDA research, e.g. Apple HealthKit
- Impact of the General Data Protection Regulation on both biomedical research and personal health/wellness services
- Policy recommendations and requirements for poorly regulated BDA practices
- Empirical studies/cases of existing Big Data practices that demonstrate critical ethical issues, concepts and solutions
- February 24, 2017: Deadline for paper submissions
- April 28, 2017: Deadline reviews papers
- May 26, 2017: Deadline revised papers
- 2017: Publication of the special issue
To submit a paper for this special issue, authors should go to the journal’s Editorial Manager http://www.editorialmanager.com/phte/.
The journal’s submission guidelines and instructions for authors can be found here.
Articles should be written in English and not exceed 10,000 words.
The author (or a corresponding author for each submission in case of co- authored papers) must register into EM.
The author must then select the special article type: “Special Issue on Ethics of Biomedical Data Analytics” from the selection provided in the submission process.
All submissions are subject to double-blind peer review. Submissions will be assessed according to the following procedure:
New Submission => Journal Editorial Office => Guest Editor(s) => Reviewers => Reviewers’ Recommendations => Guest Editor(s)’ Recommendation => Editor-in-Chief’s Final Decision => Author Notification of the Decision.
For any further information please contact: