Algorithmic Transparency
We are examining medical algorithms to characterize their transparency and evaluate to what extent the results the algorithms produce can be verified. We’re interested to understand how transparency and verifiability affect consent.
Photo by James Haworth on Unsplash
Project Team:
James Scheibner
Julia Amann
Alessandro Blasimme
Ferretti, A., Schneider, M., & Blasimme, A. (2018). Machine learning in medicine: opening the new data protection black box. Eur. Data Prot. L. Rev., 4, 320. DOI external pagehttps://doi.org/10.21552/edpl/2018/3/10