Trust in the Privacy Concerns of Brain Recordings

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 the privacy vulnerabilities that this uncertainty creates for research subjects – requires that participants put trust in BRT researchers. I argue that “trust as reliability” is insufficient to understand the obligations of BRT researchers and that a more robust understanding of trust is needed. The populous deserves to know the possibility for privacy losses in neuroscientific research.

There is a growing body of literature addressing how developing neurotechnologies may change, harm, or undermine our senses of self,^8,9 and there are potential deleterious effects of neurotechnology on privacy.¹⁰ Technologies like positron emission tomography (PET), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and electrocorticography (ECoG) present numerous ways that scientists can “look into” the brain. Here, I will not address all the concerns that arise with technologies that peer through the skull; my more limited focus is the idea that brain recordings produced as part of research protocols now may one day be used to decipher mental states of individual research participants. This narrow topic will serve as the groundwork for examining the importance of trust in brain recording research (and perhaps beyond).

Privacy, Brain Recording Technologies & Big Data

Image courtesy of Flickr.

Privacy scholars have described multiple types of privacy, such as physical, informational, decisional, and associational.^11-13 I will focus on informational privacy because it is tied to the control of personal information. This broad category can be distilled to information about yourself that you may wish to withhold from certain parties. Such information can be as common as your social security number or as pertinent as possible unconscious racial biases. The concern with informational privacy for brain recording technology is it might allow for the discovery and revelation of mental content “hidden” within recorded brain data. In other words, research subjects may lose the ability to withhold personal mental information.

This topic is nothing new, as the ability to draw additional information from brain data is already of philosophical intrigue.^14,15 As I have said, intentions, moral attitudes, and visual imaging¹⁶

can be deciphered through the collection and interpretation of brain signals from various neurotechnologies (like the electroencephalogram recorded on the exterior of the cranium or, electrocorticography recorded on the surface of the brain).^* Depending on which BRT is used, what kind of mental states the study is examining, and by what means researchers look to interpret brain recordings, a research team could discover different things (i.e. emotions and intentions). The type of procedure could also change what kind of brain recordings are collected (from which area of the brain) and the quantity of recordings collected.

The notion of “big data”¹⁸ might come to mind when considering the vast amount of brain recordings collected by use of these technologies. In research contexts, brain data is actively shared amongst researchers to “spread the wealth.”¹⁹ This practice proves efficient to allow multiple types of research to be done when the costs of conducting research are high. However, the tension rises if/when such data can be re-identified. Although currently this has a low probability of occurring from publicity and small sample groups,^20,21 the chance that it could happen highlights the concerns for the future privacy of brain recordings. If brain recordings are left in a free state of movement and can hypothetically be read to infer the identity (among other things) of the subject, the privacy concerns seem obvious. Therefore, future unknown privacy vulnerabilities of using such BRTs for subjects needs some guidance to aid in the balance between current capabilities for decoding brain data and what could be around the bend for brain recording interpretation.^† 

Trust

Image courtesy of The Blue Diamond Gallery.

Trust is an important, if often under-theorized, feature of medical research ^22-24 and of the patient-physician relationship.^25,26 It is defined as the knowledge or feeling that we can place something of significance in another’s control. Philosophically, one important aspect in the nature of trust lies in the vulnerability of the truster to the trustee.²⁷ We have all experienced this in some form or another when building relationships. In a sense, we “open ourselves up” to others and feel hurt if we are rejected. This rejection should be thought of as being synonymous with feeling betrayed and hints at the importance of a relationship dynamic in this trust schema.^28,29 I will focus on our relationships with researchers (participant-researcher relationship) here.

Reliability is generally the attribute we associate with those people who follow through on their actions. There is an important distinction between trust and reliability in that the social understanding of trust can assist in clarifying. Here, I will define reliability as following an agreed upon contract,^29-31 while trust is associated with more implicit standards of situations not explicitly stated.^28,32 For example, a researcher failing to follow the regulations set by HIPAA is being unreliable with someone’s brain recordings. But if that researcher then sold such information to marketing companies, a more implicit understanding of what should not be done with brain recordings, it would produce a feeling of betrayal. The importance here is the ability of trust to be used in the implicit vulnerabilities of privacy that could be exploited in the future of brain recordings. As the previous section stressed, the future for what brain recordings could tell about us is largely unknown. Therefore, since a patient cannot consent to such exhaustive hypothetical practices completely, an amount of trust between researcher and subject needs to be in place to account for these unknown vulnerabilities. Learning about this part of the research process will allow participants to have more knowledge of when they are vulnerable to better foster the informed consent process.

Clinical Application

Image courtesy of Wikimedia Commons.

The implementation of trust in the patient-researcher relationship is an epistemological question; that is, how can you know who you can trust? Initially, the satisfaction of reliably is used to classify trustworthiness: does what the researchers say they are going to do, happen? The more difficult step is creating the knowledge and feeling that if something does go wrong, then the researchers have your well-being in mind. A topic that addresses this, while not intended for such a use, is the notion of ancillary care. Ancillary care is the care allotted to study participants if something medically concerning is discovered while a participant is in a study. Research obligations are grounded in a kind of implicit understanding of participant-researcher relationship.³³ Lessons about trust found in the ancillary care debates can be applied to BRT research. This may provide a way to understand the activities of researchers accessing, tracking, and possibly controlling brain data as taking place within trusting relationships. So, while it may be premature to speak of codifying trust-based guidelines for BRT research, this may be an avenue worth exploring. This way, while participants might not meet the holders of their brain data, they can still trust them.

^*It is important to note that in these practices patients are consenting to have such information recorded.¹⁷ And since ethically such a practice is sound, recording brain states that a patient is unaware of is an important distinction to make about informational privacy. ²¹ Such a practice does require further ethical evaluation but for this paper, the important point to extrapolate is a subject’s vulnerabilities. 

^† Unknown vulnerabilities are common in scientific research. Will a patient be harmed by the side effects of this drug? Can this plastic be safe around children? Such unknowns are usually the original motivation to conduct research. However, I will only analyze possible harms to privacy in brain recordings. Future literature could explore how trust could work with unknown physical harms in other research fields. 

Acknowledgements



I want to thank the Neuroethics Thrust at the Center for Sensorimotor Neural Engineering for having me as an intern this summer and especially Dr. Eran Klein and Dr. Sara Goering for mentoring me.

References

1. Bonaci, T., Herron, J., Matlack, C. & Chizeck, H. J. Securing the exocortex: A twenty-first century cybernetics challenge. in 2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW) 1–8 (2014). doi:10.1109/NORBERT.2014.6893912


2. Klein, E. & Rubel, A. Privacy and ethics in brai-computer interface research. in Brain-Computer Interfaces Handbook: Technological and Theoretical Advances (eds. Nam, C., Nijholt, A. & Fabien, L.) 653–668 (Taylor & Francis).


3. Bonaci, T., Calo, R. & Chizeck, H. J. App Stores for the Brain?: Privacy and Security in Brain-Computer Interfaces. IEEE Technol. Soc. Mag. 34, 32–39 (2015).


4. BiddleMay 22 2017, S. B. & A.m, 9:26. Facebook Won’t Say If It Will Use Your Brain Activity for Advertisements. The Intercept Available at: https://theintercept.com/2017/05/22/facebook-wont-say-if-theyll-use-your-brain-activity-for-advertisements/. (Accessed: 10th July 2017)


5. Daly, I. et al. Affective brain–computer music interfacing. J. Neural Eng. 13, 46022 (2016).


6. Greene, J. D., Sommerville, R. B., Nystrom, L. E., Darley, J. M. & Cohen, J. D. An fMRI Investigation of Emotional Engagement in Moral Judgment. Science 293, 2105–2108 (2001).


7. Haynes, J.-D. et al. Reading Hidden Intentions in the Human Brain. Curr. Biol. 17, 323–328 (2007).


8. Mecacci, G. & Haselager, W. F. G. (Pim). Stimulating the Self: The Influence of Conceptual Frameworks on Reactions to Deep Brain Stimulation. AJOB Neurosci. 5, 30–39 (2014).


9. de Haan, S., Rietveld, E., Stokhof, M. & Denys, D. Becoming more oneself? Changes in personality following DBS treatment for psychiatric disorders: Experiences of OCD patients and general considerations. PloS One 12, e0175748 (2017).


10. Ahmadi, M. & Ahmadi, L. Privacy Aspects of Nanoneuroimplants from the Point of View of a Human Dignity Perspective in Related International Conventions. J. Biomater. Tissue Eng. 4, 315–337 (2014).


11. Decew, J. W. In Pursuit of Privacy: Law, Ethics, and the Rise of Technology. (Cornell University Press, 1997).


12. Allen, A. L. Uneasy Access: Privacy for Women in a Free Society. (Rowman & Littlefield Publishers, 1988).


13. Nissenbaum, H. Privacy in Context: Technology, Policy, and the Integrity of Social Life. (Stanford University Press, 2009).


14. The Oxford Centre for Neuroethics - Neil Levy. Available at: http://www.neuroethics.ox.ac.uk/our_members/neil_levy. (Accessed: 28th July 2017)


15. Edwards, S. D. R. R. J. L. I Know What You’re Thinking: Brain imaging and mental privacy by Sarah D. Richmond. (Oxford University Press, 2012).


16. Schoenmakers, S., Barth, M., Heskes, T. & van Gerven, M. Linear reconstruction of perceived images from human brain activity. NeuroImage 83, 951–961 (2013).


17. I Know What You’re Thinking: Brain imaging and mental privacy. (Oxford University Press, 2012).


18. Mittelstadt, B. D. & Floridi, L. The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts. Sci. Eng. Ethics 22, 303–341 (2016).


19. Poldrack, R. A. & Gorgolewski, K. J. Making big data open: data sharing in neuroimaging. Nat. Neurosci. 17, 1510–1517 (2014).


20. Obama shakes mind-controlled robot hand wired to sense touch. US News & World Report Available at: https://www.usnews.com/news/news/articles/2016-10-13/paralyzed-man-feels-touch-through-mind-controlled-robot-hand. (Accessed: 28th July 2017)


21. May 16, S. P. C. N., 2012 & Pm, 8:41. Paralyzed woman uses mind-control technology to operate robotic arm. Available at: http://www.cbsnews.com/news/paralyzed-woman-uses-mind-control-technology-to-operate-robotic-arm/. (Accessed: 28th July 2017)


22. Perusco, L. & Michael, K. Control, trust, privacy, and security: evaluating location-based services. IEEE Technol. Soc. Mag. 26, 4–16 (2007).


23. Kerasidou, A. Trust me, I’m a researcher!: The role of trust in biomedical research. Med. Health Care Philos. 20, 43–50 (2017).


24. Kass, N. E., Sugarman, J., Faden, R. & Schoch-Spana, M. Trust The Fragile Foundation of Contemporary Biomedical Research. Hastings Cent. Rep. 26, 25–29 (1996).


25. Mainous, A. G., Baker, R., Love, M. M., Gray, D. P. & Gill, J. M. Continuity of care and trust in one’s physician: evidence from primary care in the United States and the United Kingdom. Fam. Med. 33, 22–27 (2001).


26. Anderson, L. A. & Dedrick, R. F. Development of the Trust in Physician Scale: A Measure to Assess Interpersonal Trust in Patient-Physician Relationships. Psychol. Rep. 67, 1091–1100 (1990).


27. McLeod, C. Trust. in The Stanford Encyclopedia of Philosophy (ed. Zalta, E. N.) (Metaphysics Research Lab, Stanford University, 2015).


28. Baier, A. Trust and Antitrust. Ethics 96, 231–260 (1986).


29. Hardin, R. Trust and Trustworthiness. (Russell Sage Foundation, 2002).


30. Black, D. Autonomy and Trust in Bioethics. J. R. Soc. Med. 95, 423–424 (2002).


31. Dasgupta, P. Trust as a Commodity. in Trust: Making and Breaking Cooperative Relations (ed. Gambetta, D.) 49–72 (Blackwell, 1988).


32. Jones, K. Trust as an Affective Attitude. Ethics 107, 4–25 (1996).


33. Richardson, H. S. Gradations of Researchers’ Obligation to Provide Ancillary Care for HIV/AIDS in Developing Countries. Am. J. Public Health 97, 1956–1961 (2007).

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Stevens, I. (2018). Trust in the Privacy Concerns of Brain Recordings. The Neuroethics Blog. Retrieved on , from http://www.theneuroethicsblog.com/2018/05/trust-in-privacy-concerns-of-brain.html

Mental Privacy in the Age of Big Data

By Jessie Ginsberg

Jessie Ginsberg is a second year student in the Master of Arts in Bioethics program and a third year law student at Emory University. 

A father stood at the door of his local Minneapolis Target, fuming, and demanding to speak to the store manager. Holding coupons for maternity clothes and nursing furniture in front of the manager, the father exclaimed, “My daughter got this in the mail! She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

Target was not trying to get her pregnant. Unbeknownst to the father, his daughter was due in August.  

In his February 16, 2012 New York Times article entitled, “How Companies Learn Your Secrets,” Charles Duhigg reported on this Minneapolis father and daughter and how companies like Target use marketing analytics teams to develop algorithms to anticipate consumers’ current and future needs. Accumulating data from prior purchases, coupon use, surveys submitted, emails from Target that were opened, and demographics, a team of analysts render each consumer’s decision patterns into neatly packaged data sets tailored to predict their future buying choices. 

Flash forward to 2017, a time where online stores like Amazon dominate the market and cell phones are reservoirs of personal information, storing intimate details ranging from your location to your desired body weight to your mood. Furthermore, data analysis algorithms are more sophisticated than ever before, gobbling up volumes of information to generate highly specific and precise profiles of current and potential consumers. For example, plugging information into an algorithm ranging from social media activity to Internet searches to data collected from smart phone applications unlocks a goldmine of sensitive information that reveal the proclivities, thought processes, self-perception, habits, emotional state, political affiliations, obligations, health status, and triggers of each consumer. We must then ask ourselves, in the age of Big Data, can we expect mental privacy? That is, in a society replete with widespread data collection about individuals, what safeguards are in place to protect the use and analysis of information gathered from our virtual presence? 

In addition to the information deliberately submitted to our phones and computers, we must also worry about the data we subconsciously supply. Take, for example, the brain training program Lumosity. Over the past 10 years, this website has lured over 70 million subscribers with promises that their product will “bring better brain health,” delay conditions like Alzheimer’s and dementia, and help players “learn faster,” be sharper.” Though Lumosity and other similar companies like LearningRx were sued by the Federal Trade Commission for false advertising and must now offer a disclaimer about the lack of scientific support backing their product, has the damage already been done? 

Image courtesy of Pixabay.

More troubling than a brain training company’s use of unsubstantiated claims to tap into consumer fears of losing mental acuity for financial gain, the information collected by these brain training programs may serve as yet another puzzle piece for big data firms. Now, not only can applications and search engine histories provide a robust portfolio of what an individual consciously purchases and searches, but now these brain training websites can provide deeper insights into how individuals reason and analyze information. In their article entitled “Internet-Based Brain Training Games, Citizen Scientists, and Big Data: Ethical Issues in Unprecedented Virtual Territories,” Dr. Purcell and Dr. Rommelfanger express this concern: brain training program (BTP) data “are being interpreted as current demonstrations of existing behaviors and predispositions, and not just correlations or future predictions of human cognitive capacity and performance. Yet, the vulnerability of cognitive performance data collected from BTPs has been overlooked, and we believe the rapid consumption of such games warrants a sense of immediacy to safeguarding these data” (Purcell & Rommelfanger 2015, 357). The article proceeds to question how the data collected through brain training programs will be “secured, interpreted, and used in the near and long term given evolving security threats and rapidly advancing methods of data analysis” (Purcell & Rommelfanger, 357). 

Even more worrisome are the lack of protections currently afforded to those who turn to websites and phone applications for guidance in coping with mental health issues. According to a 2014 article entitled “Mental Health Apps: Innovations, Risks and Ethical Considerations,” research shows a majority of young adults with mental health problems do not seek professional help, despite the existence of effective psychological and pharmacological treatments (Giota & Kleftaras 2014, 20). Instead, many of these individuals turn to mental health websites and phone applications, which “are youth-friendly, easily accessible and flexible to use” (Giota & Kleftaras 2014, 20). Applications such as Mobile Therapy and MyCompass collect and monitor data ranging from lifestyle information, such as food consumption, exercise and eating habits, to mood, energy levels, and requests for psychological treatments to reduce anxiety, depression, and stress (Proudfoot et al 2013). Alarmingly, users of these programs are not guaranteed absolute protection from the developers. That is, current legal mechanisms in the United States do not fully prevent developers from selling personal health information submitted into apps to third party marketers and advertisers. 

Justice Allen E. Broussard of the Supreme Court of California declared in a 1986 opinion, “If there is a quintessential zone of human privacy it is the mind” (Long Beach City Emps. Ass'n. v. City of Long Beach). Indeed, with the advent of cell phones, widespread use of the internet, data analysts, and complex algorithms that predict future behaviors, our claim to privacy is waning. Until laws and regulations are designed to protect information collected from phone applications and Internet use, it is crucial that consumers become fully aware of just how much of themselves they share when engaging in Internet and phone activity.

References 

Giota, K.G. and Kleftaras, G. 2014. Mental Health Apps: Innovations, Risks and Ethical Considerations. E-Health Telecommunication Systems and Networks, 3, 19-23. 

Long Beach City Emps. Ass'n. v. City of Long Beach, 719 P.2d 660, 663 (Cal. 1986). 

Proudfoot, J., Clarke, J., Birch, M.R., Whitton, A.E., Parker, G., Manicavasagar, V., et al. (2013) Impact of a Mobile Phone and Web Program on Symptom and Functional Outcomes for People with Mild-to-Moderate Depression, Anxiety and Stress: A Randomised Controlled Trial. BMC Psychiatry, 13, 312. 

Purcell, R. H., & Rommelfanger, K. S. 2015. Internet-based brain training games, citizen scientists, and big data: ethical issues in unprecedented virtual territories. Neuron, 86(2), 356-359.

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Ginsberg, J. (2017). Mental Privacy in the Age of Big Data. The Neuroethics Blog. Retrieved on , from http://www.theneuroethicsblog.com/2017/06/mental-privacy-in-age-of-big-data.html

Meet Tomorrow's World: A Meeting on the Ethics of Emerging Technologies

By Marcello Ienca

Marcello Ienca, M.Sc., M.A., is a PhD candidate and research assistant at the Institute for Biomedical Ethics, University of Basel, Switzerland. His current projects include the assessment of intelligent assistive technologies for people with dementia and other neurocognitive disabilities, the regulation of pervasive neurotechnology, and the neurosecurity of human-machine interfaces. He is the chair of the Student/Postdoc Committee of the International Neuroethics Society and the current coordinator of the Swiss Network for Neuroscience, Ethics and Law.

Technology is rapidly reshaping the world we live in. In the past few decades, mankind has not significantly changed biologically, but human societies have undergone continuous and unprecedented developments through technological innovation. Today, most human activities—from messaging to geolocation, from financial transactions to medical therapies— are computer-mediated. In the next decades, the quantity and variety of activities mediated by digital technology is bound to increase exponentially. In parallel, with advancements in artificial intelligence (AI), robotics and microcomputing, the friction between man and machine is set to vanish and the boundaries at the human-machine interface are bound to blur. In an attempt to anticipate our technological futures as well as their impact on our societies and our systems of values, the International Neuroethics Society (jointly with the Temporal Dynamics of Learning Center, the Science Collaboratory of the University of California, San Diego, and the National Science Foundation) sponsored a public event on the Ethics of Emerging Technologies as part of the 2016 annual INS meeting in San Diego, California. The event was organized by INS President Judy Illes, INS Executive Director Karen Graham, Dr. Rachel Wurzman of the INS Public Session Program Committee and Prof. Andrea Chiba, Dr. Roger Bingham and Prof. Deborah Forster of UCSD. A panel of international experts in various areas of science and ethics gathered in San Diego on November 9 to discuss various critical issues emerging at the human-machine interface with possible disruptive implications for ethics and society. The first perspective was provided by Dr. William D. Casebeer, career intelligence analyst and Lieutenant Colonel in the US Air Force. His short talk proposed an interesting analogy between pervasive technology and the art of storytelling to show how technology could be actually used, in the near future, to raise empathy, deliver personalized experiences and facilitate human interaction.

Image courtesy of Wikimedia Commons

The second talk, delivered by Dr. Kate Darling, research specialist at the MIT Media Lab, focused on the near-term effects of robotic technology, with a particular interest in their legal, social, and ethical issues. Her analysis took a first step from the common observation that people often treat robots like they are alive, despite consciously knowing that they are not living beings in any significant sense. A paradigmatic example is the confirmed report of soldiers having held funerals for fallen robots. The reason for that, Darling argued, presumably stems from the fact that robots embody physicality and movement, two qualities that are essential to animated beings. This phenomenon shows that robots can also be effectively used for supporting empathic activities such as therapy, assistance and social interaction. However, Dr. Darling also anticipated possible risks associated with robotics-assisted activities, in particular the risk that such engaging technologies may become manipulative technologies. This risk appears particularly relevant in the context of using anthropomorphic, or at least animalomorphic, assistive robotics for people with neurocognitive disabilities, including Paro and iCat. Due to their cognitive impairments, users of these technologies may lack the capacity to discern the robotic nature of these devices, and hence fail to draw the line between the biophysical and in-silico world.

Similar risks of physical-digital conflation were addressed at a deeper neurobiological level by Prof. Mayank Mehta, lab head at the W. M. Keck Center for Neurophysics at University of California, Los Angeles. His research results showed that a brain region involved in spatial learning produces a pattern of activity when it processes virtual reality (VR) that is completely different than the pattern of activity produced when it processes activity in the real world. In particular, more than half of all neurons in the space mapping brain region shut down when processing VR and the remaining maps are scrambled. In addition to space mapping, this part of the brain is crucial for many forms of learning and is directly involved in several neurological diseases invluding Alzheimer's disease, epilepsy, post-traumtic stress disorder (PTSD) and depression. Mehta's research has also shown that this part of the brain is very plastic, even in adults and seniors, suggesting that abnormal activity patterns in VR could potentially rewire this part of the brain. As the use of VR is rapidly becoming pervasive for communication and entertainment purposes, Mehta emphasized the urgent need of understanding the long-term consequences of VR use on this improtant and delicate part of the brain.



VR and assistive robotics not only raise the risk of eroding our awareness of the physical-digital distinction, but raise privacy and identity concerns, too. In fact, emerging technologies can also be used to collect personal data and even influence a person’s behavior. These privacy risks were well exemplified by Jay Giedd, Professor of Psychiatry at the University of California, San Diego. He introduced the notion of “penetration technology” to refer to the phenomenon where technology advances faster than society can adapt in terms of governance and regulation. For example, he reported that the number of events in which people participate on Facebook was demonstrated to be a good predictor of depression. However, he observed that conducting big-data research on large volumes of publicly available information on social media opens up fundamental research ethics dilemmas. In particular, there is an ethical issue of privacy and confidentiality: is a person’s informational privacy respected if researchers mine data from his or her social media profile without explicit authorization? On the one hand, the answer to this question seems to be affirmative because that information was posted publicly by the user and after acceptance of the social media’s terms and conditions. On the other hand, however, no explicit request for the acquisition of informed consent was advanced by the researchers. In parallel, neuroscientist and entrepreneur Vivienne Ming emphasized the positive dimension of such big-data trends: although collecting large volumes of data for research purposes may be questionable from a privacy perspective, it can also be extremely beneficial for science and society. Going back to Giedd’s example, the application of predictive analytics techniques to large volumes of social media data might predict depression or a manic episode, possibly saving lives that could not be saved otherwise.

Image courtesy of Jisc

These critical ethical questions were further analyzed in depth by Dr. Hannah Maslen and Prof. Julian Savulescu of the University of Oxford. Dr. Maslen called for an open debate on determining the principles that should govern the use of health technology in educational contexts. She introduced the idea of a child’s “right to future openness” to emphasize the duty of parents to keep a sufficient number of options open for their children. Moving from the educational context to a larger societal perspective, Prof. Savulescu underlined the role of human morality in enabling social interaction within groups. From his perspective, technology can be coopted as an efficient tool to achieve these prosocial goals, particularly if it is used to provide cognitive and moral enhancement both at the individual and collective level. Such enhancement, however, may cause structural transformations to critical aspects of our modern societies, including the political dimension.

On the whole, all panelists were optimistic about future advancements in technological innovation and dissemination. However, they called for a cooperative effort to anticipate the ethical and social implications of emerging technologies and to open a public debate on these issues. This debate has been successfully initiated with the Meeting on the Ethics of Emerging Technologies. It is now up to all of us to shape the technological future we want to live in.

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Ienca, M. (2016). Meet Tomorrow's World: A Meeting on the Ethics of Emerging Technologies. The Neuroethics Blog. Retrieved on , from http://www.theneuroethicsblog.com/2016/12/meet-tomorrows-worlda-meeting-on-ethics.html

Hot off the presses! Ethical issues with direct-to-consumer neuroscience

Ethical issues with Lumosity and other Direct-to-Consumer Brain Training
Games by Emory Neuroethics Program Director and AJOB Neuroscience Editor-in-Residence, Dr. Karen Rommelfanger and AJOB Neuroscience editorial intern Ryan Purcell.



Article is open access here for the next 50 days until June 11, 2015.

"Internet brain training programs, where consumers serve as both subjects and funders of the research, represent the closest engagement many individuals have with neuroscience. Safeguards are needed to protect participants’ privacy and the evolving scientific enterprise of big data."