Deepfakes are extremely realistic audio/video media. They are produced via a complex machine-learning process, one that centrally involves training an algorithm on hundreds or thousands of audio/video recordings of an object or person, S, with the aim of either creating entirely new audio/video media of S or else altering existing audio/video media of S. Deepfakes are widely predicted to have deleterious consequences (principally, moral and epistemic ones) for both individuals and various of our social practices and institutions. In this introduction (...) to the Topical Collection, I first survey existing philosophical research on deepfakes (Sects. 2 and 3). I then give an overview of the papers that comprise the Collection (Sect. 4). Finally, I conclude with remarks on a line of argument made in a number of papers in the Topical Collection: that deepfakes may cause their own demise (Sect. 5). (shrink)

Predictive processing theorists have claimed PTSD and depression are maladaptive and epistemically distorting because they entail undesirably wide gaps between top-down models and bottom-up information inflows. Without denying this is sometimes so, the “maladaptive” label carries questionable normative assumptions. For instance, trauma survivors facing significant risk of subsequent attacks may overestimate threats to circumvent further trauma, “bringing forth” concretely safer personal spaces, to use enactive terminology, ensuring the desired gap between predicted worries and outcomes. The violation of predictive processing can (...) go in the opposite direction too, as when depression coincides with energy-depletion, and hence objectively strenuous situations in which things look farther away because they are (accurately anticipated to be) harder to reach. These examples partly encapsulate what predictive processing theorists call “active inference,” yet with differences. In the first case, actions fruitfully obviate predictions rather than fulfilling them. In the second, mental models do not dysregulate bodily processes, making coping harder. Instead, problems (e.g., personal obstacles, gastric illness) deplete energy, eliciting a depressive and adaptive slow-down. Some predictive proponents apply correspondence criteria when alleging mismatches between internal models and the world, while incongruously asserting that the brain did not evolve to see things veridically, but to execute actions. An alternative is to adopt pluralistic, pragmatic epistemologies suited to the complexity of mind. The upshot is that mental outlooks can depart from the norm without epistemically being distorted and that mismatches between anticipatory worries and outcomes, when they actually exist, can be a measure of adaptive and epistemic success. (shrink)

This article examines epistemic impacts of social media, merging Gibson’s affordance theory with the notion of selective permeability, which holds people encounter objective differences in a setting because of their distinct capacities, only here applying the idea to online spaces. I start by circumscribing my deployment of “affordances,” taking care not to totally divorce the term from Gibson’s intent, as often happens in information technologies research. I next detail ways that selective permeability characterizes online epistemic landscapes, focusing on how factors (...) (like culture) moderate normative standards for sharing information. This leads to a discussion about selective receptivity and blindness to information in the context of social media—a situation that amplifies political divides and renders antagonists mutually incomprehensible. This segues into my final topic: an exposition of how social media can make the offline world more selectively hostile to some. An additional proposition is that practical habits cultivated on networking apps can modulate what affordances are present in offline arenas, as opposed to just affecting which ones get noticed. Throughout, I suggest that selective permeability answers an increasingly recognized challenge: the difficulty of generalizing conclusions about one app to others and across cultures, ages, etc. Ultimately, my aim is not only to explicate how social media fragments common social knowledge but to defend selective permeability as an epistemic template for comprehending social media. (shrink)