The Rules of Contagion

(Greg DeLong) #1

extracted from their data, some might turn away from digital
technology entirely.


If users are uncomfortable with exactly how their data is being
used, researchers and companies have two options. One is to simply
avoid telling them. Faced with concerns about privacy, many tech
companies have downplayed the extent of data collection and
analysis, fearing negative press coverage and uproar from users.
Meanwhile, data brokers (who most of us have never heard of) have
been making money selling data (which we weren’t aware they had)
to external researchers (who we didn’t know were analysing it). In
these cases, the assumption seems to have been that if you tell
people what you’re doing with their data, they won’t let you do it.
Thanks to new privacy laws like Europe’s General Data Protection
Regulation (GDPR) and California’s Consumer Privacy Act, some of
these activities are becoming harder. But if research teams continue
to brush over the ethics of their analysis, there will be further
scandals and lapses in trust. Users will become more reluctant to
share data, even for worthwhile studies, and researchers will shy
away from the effort and controversy of analysing it.[28] As a result,
our understanding of behaviour – and the social and health benefits
that can come from such insights – will stagnate.
The alternative option is to increase transparency. Instead of
analysing people’s lives without their knowledge, let them weigh up
the benefits and risks. Involve them in the debates; think in terms of
permission rather than forgiveness. If social benefits are the aim,
make the research a social effort. When the announced their
‘Care.data’ scheme in 2013, the hope was that better data sharing
could lead to better health research. Three years later, the scheme
was cancelled after the public – and doctors – lost confidence in how
the data were being used. In theory, Care.data could have been
enormously beneficial, but patients didn’t seem to know about the
scheme, or didn’t trust it.[29]


Perhaps nobody would agree to data-intensive research if they
knew what was really involved? In my experience, that’s not
necessarily true. Over the past decade, my collaborators and I have

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