All Together Now: Data Work to Advance Privacy, Science,
and Health in the Age of Synthetic Data
Workshop Description
Transparency alone is
insufficient to bridge the gap between data practices and public understanding
in an era of synthetic data and artificial intelligence. “Data work” is needed
to have scientific data be deemed trustworthy, meaningful and actionable–not
only for scientists but also for the individuals from whom those data were
derived or to whom those data relate. This workshop is intended to nurture
a discussion of these issues and describe the interdisciplinary
competencies necessary to become equipped to embed ethical, legal and social
considerations into their research.
Contacts: Lindsay
Fernandez-Rhodes, PhD (fernandez-rhodes
at psu.edu) and Jennifer K. Wagner, JD PhD (jkw131 at psu.edu)
The 3-hour workshop will
consist of three parts:
Structure
·
Part 1: We will begin
the workshop with presentations from four experts, Randi Foraker, PhD; Jason
Moore, PhD; Anjali Deshmukh, MD, JD; and
·
Part 2: Will focus on
ethics and data communication with five renowned scholars in community
engagement, ethics and science communication: Meg Doerr, MS; Maile Tauali‘i,
PhD; Melissa Creary, MPH, PhD; Jasmine McNealy, PhD, JD; and Samira Kiani, MD.
At the beginning of this section, Meg Doerr, MS will facilitate an interactive
discussion of how community harms can be identified and addressed through
improved community-engagement.
·
Part 3: After all
scholars have presented, Jennifer Wagner, JD, PhD will facilitate a discussion
panel about what they would like to see from data scientists who use synthetic
data in the near future. Finally, all contributors will be invited to the floor
for a final question and answer session co-led by the organizers.
Learning
Objectives
By the end of
the workshop participants will have gained additional:
·
Experience in
understanding how new data technologies that use obfuscation are being
implemented in the biomedical sciences,
·
Awareness of
the potential opportunities and concerns related to these practices with
respect to participant and community engagement, and
·
Exposure to the
best practices for fostering community engagement and science communication,
while simultaneously embracing these new data practices.
Presenter
Information
· Randi Foraker, PhD, MA, FAHA, FAMIA, FACMI, Professor of
Medicine within the Division of General Medical Sciences at Washington
University in St. Louis.
· Jason Moore,
PhD, FACMI, FIAHSI, FASA, Professor and
Chair of the Department of Computational Medicine at Cedars-Sinai Medical
Center.
· Anjali
Deshmukh, MD, JD, Assistant Professor
of Law at Georgia State University.
· John Wilbanks, Head of Product, Data Sciences Platform at the Broad
Institute of Massachusetts Institute of Technology and Harvard University.
· Meg Doerr, MS,
LGC,
Director at Sage Bionetworks.
· Maile Tauali‘i,
PhD MPH, Collaborative Investigator, Hawaii
Permanente Medical Group.
· Melissa S.
Creary, PhD, MPH, Assistant
Professor of Health Management and Policy and Assistant Professor of Global
Public Health at the University of Michigan.
· Jasmine
McNealy, PhD JD, Associate Professor in the Department of Media Production, Management,
and Technology.
· Samira Kiani,
MD, Associate Professor of Pathology and Bioengineering
at University of Pittsburgh.
Workshop
Organizers
· Lindsay Fernandez-Rhodes,
PhD, MSPH, Assistant Professor of Biobehavioral
Health at Penn State University, conducts interdisciplinary research to examine how biologic factors (i.e.
genetic, epigenetic) and social determinants can interact and compound each
other’s effect on complex diseases, namely obesity, cardiometabolic or
reproductive health. She has published 50+ articles in the areas of
genetic, social epidemiology and health disparities. She is MPI on a R01 to
conduct genome-wide association studies of cardiovascular diseases and collect
gene expression profiles in Hispanic/Latino populations. More recently she was
awarded R21 to conduct secondary data analyses of socio-epigenomic loci of
obesity. She was awarded one of two inaugural Early Career Investigator Awards
by ASHG’s Human Genetics and Genomics
Advances for her work promoting genomic studies of understudied and
marginalized populations. She currently serves as an Associate Editor in
Applied Genetic Epidemiology for Frontiers in Genetics. She is a member of the
Diversity and Inclusion committee at the Society of Epidemiologic Research,
which has allowed her analyze society-level survey data to describe how
structural determinants of health also impact the public health workforce and
COVID-19 related experiences of research active epidemiologists.
· Jennifer K.
Wagner, JD, PhD, Assistant
Professor of Law, Policy, and Engineering and Anthropology at Penn State
University, is an expert in ethical,
legal, and social implications (ELSI) research including matters of privacy and
nondiscrimination rights as well as the international human right to science as
they relate to two technical domains (genetic/omic and digital health
technologies). She has contributed to human-centered design and participant
engagement for the NIH All of UsSM
Research Program and Geisinger’s MyCode(R) Community Health
Initiative. She has published more than 65 articles, and her work has been
cited by the U.S. Supreme Court in a landmark case involving genetic privacy.
Her research has been funded through several NIH awards, including relevant
K99/R00 and R01 projects funded by NHGRI, bioethics administrative supplements
funded by NIH OD/NIDCR and NIH OD/NIBIB, and her current R21 award from NIH
OD/NIBIB for “Bioethical, Legal, and Anthropological Study of Technologies
(BLAST).” She currently serves as an Associate Editor for Human Genetics and Genomics Advances, as a member of the
Pennsylvania Bar Association’s Cybersecurity and Data Privacy Committee; and as
a member of the founding board of directors for DNA Bridge (a 501(c)(3)
organization). Through her research and other professional experiences, she has
observed a syndemic building from existing health disparities and emerging data
disparities, associated data justice vulnerabilities (such as
hyper-surveillance of the data rich and hypo-surveillance of the data poor),
and potential opportunities to promote equity (through, for example, community
engagement; responsible use of synthetic data and digital twins; and open
science initiatives).