Machine learning can offer new tools, fresh insights for the humanities


Truly revolutionary political transformations are naturally of great interest to historians, and the French Revolution at the end of the 18th century is widely regarded as one of the most influential, serving as a model for building other European democracies. A paper published last summer in the Proceedings of the National Academy of Sciences, offers new insight into how the members of the first National Constituent Assembly hammered out the details of this new type of governance. Specifically, rhetorical innovations by key influential figures (like Robespierre) played a critical role in persuading others to accept what were, at the time, audacious principles of governance, according to co-author Simon DeDeo, a former physicist who now applies mathematical techniques to the study of historical and current cultural phenomena. And the cutting-edge machine learning methods he developed to reach that conclusion are now being employed by other scholars of history and literature. As more and more archives are digitized, scholars are applying various analytical tools to those rich datasets, such as Google N-gram, Bookworm, and WordNet.

When the humanities meet big data


Being a voracious reader is a prerequisite for academics in the humanities, but even the most dedicated bookworm needs to eat, sleep, and socialize. Not so for computers, which are known for being tireless, thorough, and very fast. And, when asked the right kinds of questions, these electronic speed-readers can grasp patterns that would otherwise lie beyond the reach of human scholars. That's exactly what happened when a team of researchers used machine-learning techniques to plow through transcripts of 40,000 speeches in a parliamentary assembly during the first two years of the French Revolution, according to a paper published in the Proceedings of the National Academy of Sciences last month. By quantifying the novelty of speech patterns and the extent to which those patterns were copied by subsequent speakers, the researchers illustrated how much of the important intellectual work of the revolution was initially carried out in committees, rather than in the whole assembly.



The French Revolution was one of the most important political transformations in history. Even today, more than 200 years later, it's held up as a model of democratic nation-building. But for years, historians and political scientists have wondered just how the democratic trailblazers of the French Revolution managed to pull off the creation of an entirely new kind of governance. New research from an interdisciplinary collaboration among historians, political scientists, and statisticians suggest that rhetorical innovations may have played a significant role in winning acceptance for the new principles of governance that built the French republic's foundation -- and inspired future democracies around the world. The study, published today in PNAS, used machine learning techniques to comb through transcripts of 40,000 speeches from the deliberations of the makeshift assembly formed during the revolution's early days to hash out the laws and institutions of the new government.

When People Are as Predictable as Water - Facts So Romantic


Can we apply a physics-like reductionism to people? That's a question we asked Simon DeDeo, a professor of social and decision sciences at Carnegie Mellon University, who also heads the Laboratory for Social Minds at the Santa Fe Institute. DeDeo was well suited to the question. With a background in astrophysics, studying galaxy formation, he's applied a similar, mathematical approach to both contemporary and historical social phenomena (see his Nautilus feature on shifting attitudes toward violent crime, "When Theft Was Worse Than Murder"). "One of the bugbears of the social sciences--and the study of groups and the origins and development of civilization--is this notion of human nature," DeDeo told Nautilus editor in chief Michael Segal.

Academic expert says Google and Facebook's AI researchers aren't doing science


The field of artificial intelligence, to those on the outside, must appear to be an orderly gathering of intellectuals collaborating at the cutting edge of technology. If you dig beyond the hyperbole of Elon Musk and the wonders promised by Google, there's a number of gnashing dissenters who're happy to toss shade at the entire industry. These people are called academics. And, I'll be up front, I think they have a point. But more on that later, for now let's talk about Simon DeDeo.