Ethics generally works on the principles of do no harm. Although research protocols to protect human beings have been in place for a while now, the pervasiveness of multiple types of data and their use make it less clear where the impact on human beings is in the data life cycle. Thus, harm is not only direct based on exposing identifiable data for individuals, but also indirect resulting from the reuse of easily available data and combining multiple datasets.
Advances in drug development and neurotechnology over the last century have noticeably increased our ability to target cognitive-behavioral networks and help those with physical disabilities. These and future advances could potentially provide a pathway by which to use drugs and/or devices to consistently enhance human cognition and behavior, rather than just treat or manage the symptoms of medical conditions.
With 2.5 quintillion records of data created every day, people are being defined by how they travel, surf the Internet, eat, and live their lives. We are in the midst of a “data revolution,” where individuals and organizations can store and analyze massive amounts of information.
Many universities and federal agencies have research integrity policies that focus on misconduct and improper behaviors, whereas few provide principles of research integrity explaining model behaviors to which researchers can aspire and why such behaviors are important to the research process. By focusing on the negative aspects, research integrity becomes a punitive action associated with compliance and policing. Putting a positive spin on research integrity is an opportunity for providing professional development to researchers.