From Aeon: When robots read books

As our understanding of Artificial Intelligence and its relation to our own intelligence is slowly becoming illuminated, one cannot help but to speculate whether machines of the future will be able to replace our role in certain activities. And some feel immediately slighted when such functions are also one’s dearly cherished. Many of these involve literature: reading, creating, and criticizing. Inderjeet Mani at Aeon ponders how algorithms are able to perform certain functions of the critic, such as identifying similarities among different characters in literature, within a fraction of the time it would otherwise take:

The computational linguist David Bamman, now at the University of California, Berkeley, and colleagues, mined a database of more than 15,000 novels to produce a Bayesian statistical model that could predict different character types. They used features such as the actions that a person participates in, the objects they possess, and their attributes. The system was able to identify cases where two characters by the same author happen to be more similar to each other than to a closely related character by a different author. So the system discovered that Wickham in Jane Austens Pride and Prejudice (1813) resembles Willoughby in her Sense and Sensibility (1811),more than either character resembles Mr Rochester in Charlotte Bronts Jane Eyre (1847).

Many of us are of course bristled in protest, yet Mani honorably concedes that the critic serve a much more wide-ranging function than can be dreamt of in the algorithm of such a machine. He labors, however, that computers have shown the rudiments of something which critics would be doing a disservice to their own scholarship by overlooking.

Read his full post at Aeon

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