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A NEW ZEITGEIST
One emerging job title aims to clarify some
of these ambiguities. Much as the term “data
scientist” was relatively obscure 15 years ago,
“data ethicist” has yet to hit zeitgeist status.
But the role, designed to help companies
consider the ethical implications of their practices,
is slowly gaining traction. In some cases,
it’s already taken off.
Reid Blackman, Ph.D., is the founder of
Virtue Consultants, a firm of more than 60 ethicists
spread across the globe. With expertise in
data and AI, the Virtue network advises corporations
in areas such as privacy, fairness (including
bias), trust, and respect. “I want companies
to do better,” Blackman explains, “and now, they
have a financial incentive, because consumers
and employees are demanding it.”
Virtue’s client services go beyond assessing
simple cases of data misuse. For instance, the
company is currently in talks with a facial-recognition
startup to determine the ethical ramifications
of each function of its API, including
how data is stored, disclosed, and shared.
One of Virtue’s objectives is to instill confidence
in corporate decision makers who are
responsible for data missteps. “Companies are
intimidated by the topic. They think it’s going
to require a whole bunch of technical chops—
but making certain kinds of decisions doesn’t
require deep technological knowledge,” Blackman
says. “Leaders should be educated about
what the issues are so that they feel empowered
to make decisions in a responsible way.”
As organizations continue to make data
central to their operations, experts like Blackman
predict that moral crossroads will only
continue to crop up. What’s more, efforts to
clearly define just who answers such questions
often do not keep pace with the rate
of innovation.
Lisa Spelman,vice president, Data Center
Group, and general manager, Intel Xeon Processors
and Data Center Marketing, cautions
against assigning ethical oversight solely to
the data science team. “A data scientist is a
mathematician, a deeply technical resource—
not necessarily an ethicist,” says Spelman.
“So, if you are putting all of that responsibility
on your data science team, it’s too big
of a burden, and can slow down the path
to success.”
Instead, Blackman suggests that every
employee who touches data should have
basic knowledge of its ethical implications. A
chief privacy officer or chief data officer, for
instance, must not only work with a development
team to enact privacy policies and best
practices, but he or she must also educate
other executives to ensure their buy-in.
THE INTERSECTION OF
AI AND DATA ETHICS
Moral quandaries associated with AI open a
whole new can of worms, ethically speaking,
explains Blackman. “There was data well
before there was artificial intelligence. But
because AI is all about data, data ethics is
almost—not quite, but almost—a subset of
the discipline,” he notes.
As such, ethics around training AI are
becoming increasingly salient. AI algorithms
present a twofold challenge: Companies must
consider both input (are algorithms biased in
any way?) as well as output (where and with
whom is the resulting data shared, and is it
leading to a valuable outcome?).
Spelman suggests this is where the data
ethicist can facilitate honest conversations
as they’re building out AI capabilities—from
the very earliest stages of algorithm development.
“This will give you the capability to