This article focuses specifically on issues related to data-driven research, which is an area where the notion of harm is still hotly debated and both benefit and risk are typically intangible.
This essay helps push forward the growing discourse on the ethics of big data research by disclosing critical conceptual gaps that often hamper how researchers and IRBs think about privacy, personal information, consent, and harm in the context of big data.
The application of the regulatory model of IRBs to research using big-data, particularly in the for-profit sector, raises a host of issues.
Traditionally, the ethical principles that guide scientific studies involving people are primarily intended to cover direct human--‐centered research.
Secondary research using health information is on the rise. Not all informational research presents equal burdens.
Privacy advocates have spent the better part of a decade teaching people that their data is precious and that once it’s online, it’s online forever.
Big Data Research is something new, a practice rooted in large-scale data collection that frequently combines aspects of research, experimentation, and entertainment.
Over the last decade, research on the privacy of user information has shown that often a) ordinary users pay little attention to privacy policies and b) when considering policies, people have a hard time understanding their meaning and practical implications
The Institutional Review Board process, while not perfect, has been fairly effective in balancing the progress of research and protection to human subjects.
This paper argues that we should learn from practice: that researchers working with open and online datasets are converging around norms for responsible research practice that can help guide IRBs or alternative arrangements interested in regulating research ethics.