Recent cognitive research has indicated that free-indirect discourse (FID) can promote empathy in readers. We broaden and refine this research by distinguishing between two formal features of FID: (1) its pivot from the third person into the first, and (2) its pivot back out of the first person into the third. We then suggest that a historical survey of literature provides grounds for hypothesizing that the second formal feature of FID might have a very different cognitive effect from empathy: an acceptance of alterity. We provide some supporting evidence for our hypothesis through an original psychology study and conclude by proposing that our identification of a second cognitive effect of FID reveals how scientific reduction might be used to develop multiple, even divergent, models of rhetorical function.

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Creativity is a major source of innovation, growth, adaptability, and psychological resilience, making it a top priority of governments, global corporations, educational institutions, and other organizations that collectively invest hundreds of millions of dollars annually into training. The current foundation of creativity training is the technique known as divergent thinking; yet for decades, concerns have been raised about the adequacy of divergent thinking: it is incongruent with the creative processes of children and most adult creatives, and it has failed to yield expected downstream results in creative production. In this article, we present an alternative approach to creativity training, based in neural processes different from those involved in divergent thinking and drawing upon a previously unused resource for creativity research: narrative theory. We outline a narrative theory of creativity training; illustrate with examples of training and assessment from our ongoing work with the U.S. Department of Defense, Fortune 50 companies, and graduate and professional schools; and explain how the theory can help fill prominent lacunae and gaps in existing creativity research, including the creativity of children, the psychological mechanisms of scientific and technological innovation, and the failure of computer artificial intelligence to replicate human creativity.

In response to Franco Moretti's project of distant reading and other recent developments in the Digital Humanities, this article offers a proof that computers will never learn to read or write literature. The proof has three main components: (1) computer artificial intelligences (including machine-learning algorithms) run on the CPU's Arithmetic Logic Unit, which performs all of its computations using symbolic logic; (2) symbolic logic is incapable of causal reasoning; and (3) causal reasoning is required for processing the narrative components of literature, including plot, character, style, and voice. This proof is presented both in logical form and as a narrative. The narrative's beginning traces the origin of automated symbolic-logic literature processors back before modern computing to the 1930s Cambridge scholar I. A. Richards. The middle recounts how these processors became a basis of New Criticism, Cultural Poetics, and other twentieth-and twenty-first-century theories of literary "interpretation. " And the end explores how those theories' preference for symbolic logic over causal reasoning leaves them vulnerable to the same blind spot that early modern scientists detected in medieval universities: the inability to explain why literature (or anything else) works-and therefore the inability to comprehend how to use it.

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