also tend to
look in health care, where it’s relatively
easy to get good problem definitions
and good deployment coverage.
[COntinUed frOm p. 112]
is it difficult to get funding?
What about your wireless hypothesis,
which posits that it’s more useful to
provide communications and computing capabilities to developing nations
than more traditional infrastructure?
In terms of the percentages, I think
there are signs that the wireless hypothesis is coming true—that countries that have cellular infrastructure
are getting things like roads, too. It’s
hard to know what it means, but it’s
certainly correlated, and we’ll probably
know in another 10 years or so.
What’s your take on the larger iCtd
I’m very happy with our progress.
There’s the ACM SIGDEV [ACM’s Symposium on Computing for Development, Univ. of London, Dec. 17–18,
2011) that’s coming, and ACM India
has interest in this space. There are
also several conferences that cover
different disciplines, as well as workshops from many different fields—for
AI, for networking and systems, for
HCI. This is the right model, because
we’re trying to solve problems that
require many disciplines. So people
in this space have both a community
position and a position in which they
specialize and teach and do traditional
work in their discipline.
how can scientists balance those two
It varies by discipline. I would say
that HCI is the easiest because they
have a long history of looking at their
users as part of the focus of the domain. For other fields that are perhaps
needs to be a part
of almost every
and it’s not clear
to me that computer
stepped up to
that role yet.”
more narrowly defined, I would say
these projects tend to be about 20%
new technology and 80% other stuff.
You need a nugget and a strong insight
for your domain, and then you have to
do all this other work like understanding the problem, maybe even discovering the problem, and trying something
in the field, because that’s the litmus
test. It’s unpredictable how things are
going to work.
earlier this year, you began a two-year
stint at google. how did that happen?
I was doing some consulting with
Google, and in particular with Google.
org, which is its philanthropic arm.
Some of the senior Google management asked me about my opinion on
some things, and I guess they wanted
my opinion on a lot more things, which
led to an offer I couldn’t refuse.
What are you working on?
I’m looking quite broadly at ways
that Google can improve its own infra-
structure to make it more innovative in
the long term. There’s great hardware
coming, and things like flash storage
that really change some of the equa-
tions. Looking long term, I would also
like to see how we can provide the cloud
to another billion or two billion people.
There’s bandwidth coming into Africa
at unprecedented levels, particularly
to east Africa, because of the undersea
cables. We still have to figure out how
to get it inland, and we need to figure
out how to build and operate mobile
phone and cloud-based services in de-
veloping countries. Right now there are
very few data centers in Africa. You end
up having to go to Europe and the U.S.,
and that’s a long way to go for every ob-
ject on a Web page.
You’ve been involved with a good range
of environments throughout your ca-
reer, from startups to academia to tra-
I like both academia and industry
for different reasons. There are certain things where academia is a better
place to have an impact, where things
are a little longer term or where there’s
not a clear market yet. There are other
places where I prefer industry, especially when you want to get something
from an idea stage to affecting a billion
people. So I will continue to cross that
line back and forth.
What are some of the things you think
the field still needs to work on?
One thing that needs more thought
is how to make computer science a
good player in multi-disciplinary research. Computer science needs to be
a part of almost every discipline now,
and it’s not clear to me that computer
scientists have stepped up to that role
yet. It’s not easy to do. Tenure cases
are still based on a single discipline.
Funding at NSF is single discipline. As I
mentioned earlier, a lot of projects end
up being 20% technology and 80% other stuff—so you need reviewers that respect that other stuff and understand
what’s hard or valuable about it.
i imagine you’ve learned a lot about in-
terdisciplinary research through your
I’ve learned that it’s hard. It’s harder
for faculty than for grad students. Here
at Berkeley, we’ve been able to train a
generation of graduate students that
really know both social science and
computer science. It’s much easier to
learn in grad school, when you have the
time. I’ve been learning as I go—
learning from my students, from colleagues,
sometimes sitting in on classes. But the
future of multi-disciplinary research
will be through students who have been
trained in multiple disciplines.
Leah hoffmann is a technology writer in brooklyn, ny.