Many computer science departments were spun out of mathematics departments in the 1980s (including Sheffield’s!), but there is a historical connection between the two departments that has meant that dual degrees are relatively common.
In Sheffield, the original main link was between areas such as formal methods and pure mathematics. Verification of code for example. This relates to Godel’s incompleteness theorem and Alan Turing’s “Turing Machine”. The focus was on the computability of numbers.
Recently the nature of the interface has changed a lot. While areas such as theorem proving and verification of code are still very important, a major modern challenge is the overwhelming amount of data that we are generating. This data is generated as a direct consequence of the success of computers. It is also the responsibility of computer scientists to deal with it.
As background reading for this tutorial have a look at the links below:
Article in The Guardian’s media network on Digital Oligarchies in March 2015.
Article in The Guardian’s Media and Tech Network on preventing AI becoming creepy.
Article in The Guardian’s Media and Tech Network on How Africa can benefit from the data science revolution
Consider each of the articles and what the implications are for mathematicians and computer scientists. What does it mean for the future of this interface? Which issues fall within the domain of work in data and which fall outside?