How will your organization adapt to the flowing tide of mHealth technology? What are the ethical implications of technology-driven data collection? Quorum Review IRB and the Northwest Association for Biomedical Research (NWABR) are co-presenting the Ethics & Regulation in the Digital Age Conference, which will address these questions and many more.
We have packed this one-day conference with discussions about the intersection of digital technology, medical research, and ethics. At last year’s conference we opened the discussion on technology and informed consent. This year, we are expanding that conversation to encompass the entire research field.
The keynote speaker is mathematician, programmer, and researcher Max Little, PhD. He will share what he sees as the primary ethical challenges posed by innovations in mobile device hardware, data gathering, and algorithm design. He also will consider how our approach to mobile technology and to research should rely on improving the patient experience.
Dr. Little has been on a personal and professional mission to improve the diagnosis and treatment of Parkinson’s disease. He designed the algorithm at the core of the Parkinson’s Voice Initiative, a study which aimed to tease out early signs of Parkinson’s by gathering and analyzing 10,000 recorded voice messages. (Check out Dr. Little’s 2012 TED talk about the Parkinson’s Voice Initiative.)
This week we had a chance to ask Dr. Little a few questions about his work.
Quorum Review: In 2012, the Parkinson’s Voice Initiative gathered recordings from thousands of volunteers. What insights did you gain about communicating with that large of a study group? Did you encounter any particular challenges with recruitment, consent, or follow-up?
Max Little: Recruitment for that study was novel because the scientific purpose was to cast the net as wide as possible. Pretty much anyone could pick up the telephone and take part. This entirely remote recruitment and consent process was quite pioneering at the time and has since been replicated and refined in studies using smartphones because this is really the only way to make such very large-scale data collection efforts feasible. It relies heavily on automation. There are some low-level risks with that approach which need to be considered, particularly around the knotty issues of confirming participant identity and characteristics. Suffice to say, this is an exciting and evolving area where there is much to be gained and still to be understood.
QR: What is the most important ethical question that researchers face regarding device technologies, data gathering, and data analysis?
ML: In my view, it is about really understanding what this revolutionary technology can do. There is enormous potential which should not be withheld from the public, but there are risks which are as yet poorly defined and understood. I advocate that researchers and ethicists need to become more conversant with areas such as hardware and mathematical data analysis, and that engineers become more actively involved with ethics communities.
QR: What is the first thing you would like to improve about the current state of hardware, big data, and research?
ML: There is much confusion about what “big data” means and there are many parasitic organizations who are trying to sell unreliable analysis dressed up as genuine science. Their sales pitches have muddied the waters so much that very few really understand what the analysis of this large scale data can actually achieve, and perhaps more importantly, what it cannot do. Given that, my aim is to attempt to inject some much-needed realism.
Attend the conference to hear more from Dr. Little and to engage in conversations about ethics and regulation in the digital age.
Can’t make the live event? Join us via webcast!