Francesco Pierini

Philosophers who take maps to have a semantics (i.e., rules that assign contents to cartographic marks) also typically hold that semantics fully determines the truth‐conditional meaning of maps. In this paper, I tackle this form of literalism, which assigns no truth‐conditional role to pragmatics, by investigating the semantics‐pragmatics divide in cartographic representation. I rely on examples from Google Maps, whose widespread use makes it possible to draw general conclusions about the communicative behavior of maps. This behavior, I argue, supports a form of contextualism, on which pragmatics pervasively influences the truth conditions of maps by altering semantic elements.

A vexed claim in the philosophy of poetry is the form-content unity thesis, which states that the formal features of a poem (e.g., meter and rhyme) and its meaning are inseparable. In this paper, I interpret this thesis as a descriptive claim stating that form and content in poetry are experienced as indissolubly connected while reading silently. My view is that the unity of the experience of form and content can be explained by highlighting the role of inner speech (i.e., the mental production of one’s voice) in the phenomenology of reading poetry. The content of the inner voice is heard as having an auditory aspect and a cognitive one, which are indissolubly connected in the phenomenology: they cannot be experienced in isolation from each other (e.g., by attending to a single aspect). This interpretation explains why form-content unity is revelatory of the specific aesthetic value of poetry: it individuates poetry as the art that produces sonic and semantic effects in a unitary way, through the phenomenology of inner speech. Unity captures the specificity of poetry, since comparable sonic and semantic effects are found in other arts (e.g., music and novels).

This paper aims to provide a foundation for studying the interplay between emoji and linguistic (natural language) expressions; it does so by proposing a formal semantic classification of emoji-text combinations, focusing on two core sets of emoji: face emoji and activity emoji. Based on different data sources (introspective intuitions, naturalistic Twitter examples, and experimental evidence), we argue that activity emoji (case study I) are essentially event descriptions that serve as separate discourse units (similar to free adjuncts) and connect to the accompanying (linguistic) text by virtue of suitable discourse relations. By contrast, face emoji (case study II) are expressive elements that are anchored to an attitude holder and comment on a proposition provided by the accompanying text. We provide further evidence for the distinct behavior of face emoji and activity emoji by looking at their scopal behavior with respect to linguistically-expressed negation. In particular, we probe interactions of emoji and texts that contain clausal negation, and conclude that both face emoji and activity emoji generally do not scope under negation. However, the appearance of such a scope relation arises with activity emoji when the emoji are connected to the accompanying text by virtue of an Explanation discourse relation. With face emoji, scopal interactions seem to appear in cases where the default interpretation would result in a discourse contribution that is pragmatically infelicitous, and also in cases that involve a specialized emoji-repetition construction where a repeated alternation of face emoji with words assumes a scope-marking role.

This paper addresses the question of how emojis are integrated into the text that they occur with. I use the typology of gestural iconic enrichments proposed by Schlenker (2018a, 2018b) to investigate the hypothesis that emojis denoting objects (e.g., ????) and activities (e.g., ????) project (i.e., interact with logical operators) when co-occurring with text in a similar way as gestures do with speech. In particular, I claim that [i.] emojis generate co-suppositions, i.e., assertion-dependent presuppositions, when immediately following text (e.g., the sentence “John didn’t train today ????” gives rise to the inference that “if John had trained today, weightlifting would have been involved”); [ii.] emojis generate supplements (in the sense of Potts, 2005), just like appositive relative clauses, when they are separated from the accompanying text by a pause (e.g., the sentence “John trained today...????” gives rise to the inference that “John trained today, which involved weightlifting”); [iii.] when used as replacements for words (e.g., “Yesterday, John didn’t ???? ”), emojis have an at-issue semantics and can trigger standard presuppositions

In this paper, I present an analysis of the depictive properties of deepfakes. These are videos and pictures produced by deep learning algorithms that automatically modify existing videos and photographs or generate new ones. I argue that deepfakes have an intentional standard of correctness. That is, a deepfake depicts its subject only insofar as its creator intends it to. This is due to the way in which these images are produced, which involves a degree of intentional control similar to that involved in the production of other intentional pictures such as drawings and paintings. This aspect distinguishes deepfakes from real videos and photographs, which instead have a non-intentional standard: their correct interpretation corresponds to the scenes that were recorded by the mechanisms that produced them, and not to what their producers intended them to represent. I show that these depictive properties make deepfakes fit for communicating information in the same way as language and other intentional pictures. That is, they do not provide direct access to the communicated information like non-intentional pictures (e.g., videos and photographs) do. Rather, they convey information indirectly, relying only on the viewer's assumptions about the communicative intentions of the creator of the deepfake. Indirect communication is indeed a prominent function of such media in our society, but it is often overlooked in the philosophical literature. This analysis also explains what is epistemically worrying about deepfakes. With the introduction of this technology, viewers interpreting photorealistic videos and pictures can no longer be sure of which standard to select (i.e., intentional or non-intentional), which makes misinterpretation likely (i.e., they can take an image to have a standard of correctness that it does not have).