TRENDS
Meet the
Data Ethicist
When it comes to trust, transparency,
and training algorithms, who makes the call?
06
BY STEPHANIE WALDEN
In 2016, location-based analytics startup
Geofeedia landed in its own position of
scrutiny. The company, a social media
intelligence platform, had been sharing
whereabouts of protesters with local police—a
practice the American Civil Liberties
Union condemned as reckless and having the
potential to facilitate racial profiling.
The rebuke was the first in a series of public
backlash campaigns against companies for
questionable data practices. In 2018, online
outrage culminated in thousands of users
clamoring to #DeleteFacebook in the wake of
the Cambridge Analytica scandal. As a result
of the PR nightmare, Facebook experienced
the worst single-day loss in the history of the
U.S. stock market.
As the volume of collected data stretches to
hundreds of zettabytes in the not-so-distant
future, companies are learning—sometimes
the hard way—that complex data systems
and algorithms require equally intricate ethical
considerations.
Today, companies are faced with the
question: what is “right” and “wrong” when
it comes to collecting, using, analyzing, and
sharing data? And, whose job is it to make
this call?
ILLUSTRATION BY JAMES STEINBERG