Database Reference
In-Depth Information
to do. Actually there's a lot of parallels, which is kind of surprising because
they're completely different, but it's kind of fun when you find these parallels in
unexpected places like that. It's also handy when it comes to recruiting people
who have relevant knowledge.
Gutierrez:
What's something interesting that you and your data science
colleagues are currently talking about?
Heineike:
One thing that's been really interesting is how much our conversa-
tions keep coming back to ethics and concerns over use of data. I think that
reflects the fact that a lot of the data science that's being done is really about
analyzing people, and maybe about analyzing people when they don't want to
be analyzed or don't know that they're being analyzed. I'm quite a private per-
son in general, and the thought of having my browser history tracked is slightly
unnerving to me, and I think it's probably true for a lot of people as well. I
think there are definitely things that are possible to do now that are getting
kind of creepy. And I think that there's an onus on us and on this community
to really think carefully about what we're doing and about being wise about
the problems we choose to solve and the consequences of what we do.
I do think that there are a lot of problems to solve, which do not involve
tracking people and getting them to buy stuff that perhaps they don't want to
buy. There are a lot of problems that are very important to solve that will help
people do more of what they want and need. When you think about it this
way, it's getting harder and harder to understand what's happening globally—
specifically, things that might affect major decisions that politicians are making
or things that help us understand big social changes that we should already be
on top of and care about. There are big global issues that we should worry
about for which there's data that would help us unlock and understand a bit
better what's going on, so we can actually tackle them more effectively.
There are some great groups out there who are encouraging people to use
data science skills for solving problems for government or for nonprofits
problems where, when we think about what the impact could and should be,
we can feel much happier about it. And so I think that there are three parts
to this. One, don't assume that everything in data science is about tracking you
and being kind of nefarious. There are other uses. Two, if you're getting a job,
expect that there are going to be some really cool use cases out there for using
data, and so don't settle for something where you don't feel comfortable with
what you're doing. Finally, keep questioning and considering the consequences
of what you're doing.
