Thinking ‘oat’ of the box: Technology to resolve the ‘Goldilocks Data Dilemma’

Marielle Gross Robert Miller By ROBERT C. MILLER, JR. and MARIELLE S. GROSS, MD, MBE The problem with porridge Today, we regularly hear stories of research teams using artificial intelligence to detect and diagnose diseases earlier with more accuracy and speed than a human would have ever dreamed of. Increasingly, we are called to contribute to these efforts by sharing our data with the teams crafting these algorithms, sometimes by healthcare organizations relying on altruistic motivations. A crop of startups have even appeared to let you monetize your data to that end. But given the sensitivity of your health data, you might be skeptical of this—doubly so when you take into account tech’s privacy track record. We have begun to recognize the flaws in our current privacy-protecting paradigm which relies on thin notions of “notice and consent” that inappropriately places the responsibility data stewardship on individuals who remain extremely limited in their ability to exercise meaningful control over their own data. Emblematic of a broader trend, the “Health Data Goldilocks Dilemma” series calls attention to the tension and necessary tradeoffs between privacy and the goals of our modern healthcare technology systems. Not sharing our data at all would be “too cold,” but sharing freely would be “too hot.” We have been looking for policies “just right” to strike the balance between protecting individuals’ rights and interests while makin...
Source: The Health Care Blog - Category: Consumer Health News Authors: Tags: Artificial Intelligence Data Health Policy Tech The Health Data Goldilocks Dilemma: Sharing? Privacy? Both? AI Blockchain Federated Learning health data privacy Marielle Gross Robert Miller Zero Knowledge Proofs Source Type: blogs