Slow Science

You likely have not heard about the Slow Science manifesto. They don't blog. They don't tweet. They give a broken link to their Facebook Page which has no posts. But they do have a point.

Science needs time to think. Science needs time to read, and time to fail. Science does not always know what it might be at right now. Science develops unsteadily, with jerky moves and unpredictable leaps forward—at the same time, however, it creeps about on a very slow time scale, for which there must be room and to which justice must be done.

Computer Science is inherently a fast discipline. Technology changes quickly and if you don't publish quickly your research may become irrelevant. We created a culture with conferences and deadlines that push us, even those of us on more theoretical end, to finish our projects quickly and publish the best we have at the next due date.



But we need to step back and take a while to view the great challenges we have in computing. Issues like privacy, big data, the Internet of things and cloud computing need time to really think of the right approach, not just short term projects. In computational complexity we have grand challenges in understanding the power of efficient computation but too often we just tweak a model to eke out another publication.



Andrew Wiles solved Fermat's last theorem by toiling on the problem by himself for several years right before the Internet revolution. Will we see a slow science success again in this new age?