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By Dr. John Torous Image courtesy of Flickr user Integrated Change We often hear much about the potential of digital health to revolutionize medicine and transform care – but less about the risks and harms associated with the same technology-based monitoring and care. “It’s a smartphone app … how much harm can it really cause?” is a common thought today, but also the starting point for a deeper conversation. That conversation is increasingly happening at Institutional Review Boards (IRBs) as they are faced with an expanding number of research protocols feature digital- and smartphone-based technologies. In our article, ‘Assessment of Risk Associated with Digital and Smartphone Health Research: a New Challenge for IRBs” published in the Journal of Technology and Behavioral Science [1], we explore the evolving ethical challenges in evaluating digital health risk, and here expand on them. While risk and harm in our 21 st century digital era are themselves evolving topics that chang...

By Cliodhna O’Connor Image courtesy of Wikimedia Commons The investigation of intergroup difference is a ubiquitous dimension of biological and behavioural research involving human subjects. Understanding almost any aspect of human variation involves the comparison of a group of people, who are defined by some common attribute, with a reference group which does not share that attribute. This is an inescapable corollary of applying the scientific method to study human minds, bodies and societies. However, this scientific practice can have unanticipated – and undesirable – social consequences. As my own research has shown in the contexts of psychiatric diagnosis (O’Connor, Kadianaki, Maunder, & McNicholas, in press), gender (O’Connor & Joffe, 2014) and sexual orientation (O’Connor, 2017), scientific accounts of intergroup differences can often function to reinforce long-established stereotypes, exaggerate the homogeneity of social groups, and impose overly sharp divisions between...

By Elisabeth Hildt Image courtesy of  Pixabay . Research is not an isolated activity. It takes place in a social context, sometimes influenced by value assumptions and sometimes accompanied by social and ethical implications. A recent example of this complex interplay is an article, “ Deep neural networks can detect sexual orientation from faces ” by Yilun Wang and Michal Kosinski, accepted in 2017 for publication in the J ournal of Personality and Social Psychology. In this study on face recognition, the researchers used deep neural networks to classify the sexual orientations of persons depicted in facial images uploaded on a dating website. While the discriminatory power of the system was limited, the algorithm was reported to have achieved higher accuracy in the setting than human subjects. The study can be seen in the context of the “prenatal hormone theory of sexual orientation,” which claims that gay men and women tend to have gender-atypical facial morphology. The abstract ...

By Phoebe Friesen Image courtesy of  Pixabay . In the last few decades, there has been an increasing push towards making science more participatory by engaging those who are part of or invested in the community that will be impacted by the research in the actual research process, from determining the questions that are worth asking, to contributing to experimental design, to communicating findings to the public. Some of this push stems from the recognition that research is always value-laden and that the values guiding science have long been those of an elite and unrepresentative few (Longino, 1990). This push also has roots in feminist standpoint theory, which recognizes the way in which marginalized individuals may have an epistemic advantage when it comes to identifying problematic assumptions within a relevant knowledge project (Wylie, 2003). Additionally, many have noted how including the voices of those likely to be impacted by research can support the process itself (e.g. by...

By Molly Ann Kluck Image courtesy of Wikimedia Commons . When my neuroethics mentor approached me with a publication from Trends in Cognitive Science called “Functional Connectivity of the Human Brain in Utero” (1) in hand, I was immediately delighted by the idea of performing an ethical analysis on the use of functional Magnetic Resonance Imaging (fMRI) on fetuses in utero. As of right now, I’m still conducting this ethical analysis.  Using fMRI to look at human brains as they develop in utero is groundbreaking for a couple reasons. For one, there is a vast difference between the fMRI method currently used to investigate developing brains and previous methods that were used to examine fetal brain development. Research on developing brains had utilized preterm neonates, or babies born prematurely. While these data are valuable, there are issues with validity associated with this method: early exposure to an abnormal environment (e.g. being in the intensive care unit, where many pre...

By Ian Stevens Ian is a 4th year undergraduate student at Northern Arizona University. He is majoring in Biomedical Sciences with minors in Psychological Sciences and Philosophy to pursue interdisciplinary research on how medicine, neuroscience, and philosophy connect.  Introduction Brain recording technologies (BRTs), such as brain-computer interfaces (BCIs) that collect various types of brain signals from on and around the brain could be creating privacy vulnerabilities in their users. 1,2 These privacy concerns have been discussed in the marketplace as BCIs move from medical and research uses to novel consumer purposes. 3,4  Privacy concerns are grounded in the fact that brain signals can currently be decoded to interpret mental states such as emotions, 5 moral attitudes, 6 and intentions. 7 However, what can be interpreted from these brain signals in the future is ambiguous. The current uncertainty that surrounds future capacities to decode complex mental states – and ...