There can be tension or even at times ill will between social scientists and computer scientists.
When presented with the same figures, social scientists are likely to caution that the quality of a conclusion is only as good as the quality of the data, whereas computer scientists — often called data scientists — are likely to warn against perfection standing in the way of information. Both of these groups can pursue the growing field of data science, and how they approach their work and cooperation can bring out the best of these two perspectives, or create environments of ambiguity or animosity in the global development industry.
“Social science has always relied on a combination of statistics and models or theories. The increase in available data and the increasingly powerful and sophisticated means of automated analysis changes this equation,” said Lambert Hogenhout, chief of data analytics at the United Nations. “Over the long term, we will be able to explain and predict social dynamics much better. Getting there will require collaboration between social scientists and data scientists.”
About the author
Catherine Cheneycatherinecheney
Catherine Cheney is the Senior Editor for Special Coverage at Devex. She leads the editorial vision of Devex’s news events and editorial coverage of key moments on the global development calendar. Catherine joined Devex as a reporter, focusing on technology and innovation in making progress on the Sustainable Development Goals. Prior to joining Devex, Catherine earned her bachelor’s and master’s degrees from Yale University, and worked as a web producer for POLITICO, a reporter for World Politics Review, and special projects editor at NationSwell. She has reported domestically and internationally for outlets including The Atlantic and the Washington Post. Catherine also works for the Solutions Journalism Network, a non profit organization that supports journalists and news organizations to report on responses to problems.