The introduction to a special issue of New Literary History titled “Culture, Theory, Data,” which explores the consequences of computation for cultural theory—and vice-versa.

The introduction begins by explaining how we came to a historical juncture where “culture” and “data” seem to be opposed terms. Then it offers some reasons for believing t…[Read more]

The introduction to a special issue of New Literary History titled “Culture, Theory, Data,” which explores the consequences of computation for cultural theory—and vice-versa.

The introduction begins by explaining how we came to a historical juncture where “culture” and “data” seem to be opposed terms. Then it offers some reasons for believing t…[Read more]

As neural language models begin to change aspects of everyday life, they understandably attract criticism. This position paper was commissioned for a roundtable at Princeton University, dedicated to one of the most influential critiques: “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” by Emily M. Bender, Timnit Gebru,…[Read more]

As neural language models begin to change aspects of everyday life, they understandably attract criticism. This position paper was commissioned for a roundtable at Princeton University, dedicated to one of the most influential critiques: “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” by Emily M. Bender, Timnit Gebru,…[Read more]

As neural language models begin to change aspects of everyday life, they understandably attract criticism. This position paper was commissioned for a roundtable at Princeton University, dedicated to one of the most influential critiques: “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” by Emily M. Bender, Timnit Gebru,…[Read more]

Projects that bridge the humanities and sciences often attract attention from journalists, but evoke dismay from humanists who feel that their subjects of expertise have been misinterpreted. For the humanities to reclaim a place of pride in public conversation, humanists themselves need to embrace interdisciplinarity and take the lead in this…[Read more]

Projects that bridge the humanities and sciences often attract attention from journalists, but evoke dismay from humanists who feel that their subjects of expertise have been misinterpreted. For the humanities to reclaim a place of pride in public conversation, humanists themselves need to embrace interdisciplinarity and take the lead in this…[Read more]

Projects that bridge the humanities and sciences often attract attention from journalists, but evoke dismay from humanists who feel that their subjects of expertise have been misinterpreted. For the humanities to reclaim a place of pride in public conversation, humanists themselves need to embrace interdisciplinarity and take the lead in this…[Read more]

Some literary scholars have claimed that predictive models can measure the strength of the boundaries that separate different cultural categories—genres, for instance, or market segments. But interpreting textual models as evidence about the strength of a cultural distinction has seemed a questionable move to many readers. We use book reviews to t…[Read more]

Some literary scholars have claimed that predictive models can measure the strength of the boundaries that separate different cultural categories—genres, for instance, or market segments. But interpreting textual models as evidence about the strength of a cultural distinction has seemed a questionable move to many readers. We use book reviews to t…[Read more]

Some literary scholars have claimed that predictive models can measure the strength of the boundaries that separate different cultural categories—genres, for instance, or market segments. But interpreting textual models as evidence about the strength of a cultural distinction has seemed a questionable move to many readers. We use book reviews to t…[Read more]

Numbers appear to have limited value for literary study, since our discipline is usually more concerned to explore differences of interpretation than to describe the objective features of literary works. But it may be time to re-examine the assumption that numbers are only useful for objective description. Machine learning algorithms are actually…[Read more]

Numbers appear to have limited value for literary study, since our discipline is usually more concerned to explore differences of interpretation than to describe the objective features of literary works. But it may be time to re-examine the assumption that numbers are only useful for objective description. Machine learning algorithms are actually…[Read more]

Numbers appear to have limited value for literary study, since our discipline is usually more concerned to explore differences of interpretation than to describe the objective features of literary works. But it may be time to re-examine the assumption that numbers are only useful for objective description. Machine learning algorithms are actually…[Read more]

Numbers appear to have limited value for literary study, since our discipline is usually more concerned to explore differences of interpretation than to describe the objective features of literary works. But it may be time to re-examine the assumption that numbers are only useful for objective description. Machine learning algorithms are actually…[Read more]