Cumulative cultural knowledge [CCK], the knowledge we acquire via social learning and has been refined by previous generations, is of central importance to our species’ flourishing. Considering its importance, we should expect that our best epistemological theories can account for how this happens. Perhaps surprisingly, CCK and how we acquire it via cultural learning has only received little attention from social epistemologists. Here, I focus on how we should epistemically evaluate how agents acquire CCK. After sampling some reasons why extant (...) theories cannot account for CCK, I suggest that things aren’t as bleak as they might look. I explain how agents deserve epistemic credit for how CCK is transmitted in cultural learning by promoting a central need of their social group: The efficient and safe transmission of CCK. A good initial fit exists between this observation and Greco’s knowledge-economy framework. Ultimately, however, Greco’s account doesn’t straightforwardly account for CCK because of its strict focus on testimony. I point out two issues in the framework due to this focus. The resulting view advocates giving epistemic credit to agents when they act to promote their communities’ epistemic needs in the right way and highlights the various ways in which agents come to do this. (shrink)

The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can (...) give testimony. In section 3, I identify three assumptions underlying the view that rejects conversational AIs – AI-based technologies that converse, as testifiers: conversational AIs (1) lack intentions, (2) cannot be normatively assessed, and (3) cannot constitute an object in trust relations, while humans can. In section 4, I propose the concept ‘AI-testimony’ for analyzing outputs of conversational AIs, suggesting three conditions for technologies to deliver AI-testimony: (1) content is propositional, (2) generated and delivered with no other human directly involved, (3) the output is perceived as phenomenologically similar to that of a human. I conclude that this concept overcomes the limitations of the anthropocentric concept of testimony, opening future directions of research without associating conversational AIs with human-like agency. (shrink)

[Author note: There is a video explainer of this paper on youtube at the new work in philosophy channel (search for surname+deepfakes).] -/- It is widely thought that deepfake videos are a significant and unprecedented threat to our epistemic practices. In some writing about deepfakes, manipulated videos appear as the harbingers of an unprecedented _epistemic apocalypse_. In this paper I want to take a critical look at some of the more catastrophic predictions about deepfake videos. I will argue for three (...) claims: (1) that once we recognise the role of social norms in the epistemology of recordings, deepfakes are much less concerning, (2) that the history of photographic manipulation reveals some important precedents, correcting claims about the novelty of deepfakes, and (3) that proposed solutions to deepfakes have been overly focused on technological interventions. My overall goal is not so much to argue that deepfakes are not a problem, but to argue that behind concerns around deepfakes lie a more general class of social problems about the organisation of our epistemic practices. (shrink)

Deep learning (DL) has become increasingly central to science, primarily due to its capacity to quickly, efficiently, and accurately predict and classify phenomena of scientific interest. This paper seeks to understand the principles that underwrite scientists’ epistemic entitlement to rely on DL in the first place and argues that these principles are philosophically novel. The question of this paper is not whether scientists can be justified in trusting in the reliability of DL. While today’s artificial intelligence exhibits characteristics common to (...) both scientific instruments and scientific experts, this paper argues that the familiar epistemic categories that justify belief in the reliability of instruments and experts are distinct, and that belief in the reliability of DL cannot be reduced to either. Understanding what can justify belief in AI reliability represents an occasion and opportunity for exciting, new philosophy of science. (shrink)

The COVID-19 pandemic has been accompanied by an “infodemic” of misinformation and conspiracy theory. This article points to three explanatory factors: the challenge of forming accurate beliefs when overwhelmed with information, an implausibly individualistic conception of epistemic virtue, and an adversarial information environment that suborns epistemic dependence. Normally we cope with the problems of informational excess by relying on other people, including sociotechnical systems that mediate testimony and evidence. But when we attempt to engage in epistemic “superheroics” - withholding trust (...) from others and trying to figure it all out for ourselves – these can malfunction in ways that make us vulnerable to forming irrational beliefs. Some epistemic systems are prone to coalescing audiences around false conspiracy theories. This analysis affords a new perspective on philosophical efforts to understand conspiracy theories and other epistemic projects prone to collective irrationality. (shrink)

Clark and Chalmers propose that the mind extends further than skin and skull. If they are right, then we should expect this to have some effect on our way of knowing our own mental states. If the content of my notebook can be part of my belief system, then looking at the notebook seems to be a way to get to know my own beliefs. However, it is at least not obvious whether self-ascribing a belief by looking at my notebook (...) is a case of introspection the same way that knowing my non-extended beliefs is. Traditionally this sort of introspection is thought to be privileged and special in ways that the extended introspection case seems not to be. There is nothing privileged about looking at my notebook. Anyone could do it. The aim of the paper is to find out how to understand extended introspection and whether there is something privileged and special about knowing one’s own extended beliefs. Moreover, the notebook case has close analogs using twenty-first century technology. It seems possible to know our beliefs that are extended to smartphones, wearable technology or a cloud-based data store. First, I present the case of extended introspection. I then discuss whether it should be understood as ordinary introspection or as mind-reading. Both seem to be bad fits, which finally prompts an original account for extended introspection based on epistemic rules. (shrink)

According to most accounts of trust, you can only trust other people (or groups of people). To trust is to think that another has goodwill, or something to that effect. I sketch a different form of trust: the unquestioning attitude. What it is to trust, in this sense, is to settle one’s mind about something, to stop questioning it. To trust is to rely on a resource while suspending deliberation over its reliability. Trust lowers the barrier of monitoring, challenging, checking, (...) and questioning. Trust sets up open pipelines between yourself and parts of the external world. Trust permits external resources to have a similar relationship to one as one’s internal cognitive faculties. This creates efficiency, but at the price of exquisite vulnerability. We must trust in this way because we are cognitively limited beings in a cognitively overwhelming world. Crucially, we can hold the unquestioning attitude towards objects and technologies. When I trust my climbing rope, I stop worrying about its reliability. When I trust my online calendaring system, I simply go to the events indicated, without question. But, one might worry, how could one ever hold such a normatively loaded attitude as trust towards mere objects? How could it ever make sense to feel betrayed by an object? Trust is our engine for expanding and outsourcing our agency — for binding external processes into our practical selves. Thus, we can be betrayed by our smartphones in the same way that we can be betrayed by our memory. When we trust, we try to make something a part of our agency, and we are betrayed when our part lets us down. To unquestioningly trust something is to let it in—to attempt to bring it inside one’s practical functioning. This suggests a new form of gullibility: agential gullibility, which occurs when agents too hastily and carelessly integrate external resources into their own agency. (shrink)

Elsewhere I and others have argued that evidence one should have had can bear on the justification of one's belief, in the form of defeating one's justification. In this paper, I am interested in knowing how evidence one should have had (on the one hand) and one's higher-order evidence (on the other) interact in determinations of the justification of belief. In doing so I aim to address two types of scenario that previous discussions have left open. In one type of (...) scenario, there is a clash between a subject's higher-order evidence and the evidence she should have had: S's higher-order evidence is misleading as to the existence or likely epistemic bearing of further evidence she should have. In the other, while there is further evidence S should have had, this evidence would only have offered additional support for S's belief that p. The picture I offer derives from two “epistemic ceiling” principles linking evidence to justification: one's justification for the belief that p can be no higher than it is on one's total evidence, nor can it be higher than what it would have been had one had all of the evidence one should have had. Together, these two principles entail what I call the doctrine of Epistemic Strict Liability: insofar as one fails to have evidence one should have had, one is epistemically answerable to that evidence whatever reasons one happened to have regarding the likely epistemic bearing of that evidence. I suggest that such a position can account for the battery of intuitions elicited in the full range of cases I will be considering. (shrink)

Social epistemology is the study of the social dimensions of knowledge or information. There is little consensus, however, on what the term "knowledge" comprehends, what is the scope of the "social", or what the style or purpose of the study should be. According to some writers, social epistemology should retain the same general mission as classical epistemology, revamped in the recognition that classical epistemology was too individualistic. According to other writers, social epistemology should be a more radical departure from classical (...) epistemology, a successor discipline that would replace epistemology as traditionally conceived. The classical approach could be realized in at least two forms. One would emphasize the traditional epistemic goal of acquiring true beliefs. It would study social practices in terms of their impact on the truth-values of agents' beliefs. A second version of the classical approach would focus on the epistemic goal of having justified or rational beliefs. Applied to the social realm, it might concentrate, for example, on when a cognitive agent is justified or warranted in accepting the statements and opinions of others. Proponents of the anti-classical approach have little or no use for concepts like truth and justification. In addressing the social dimensions of knowledge, they understand "knowledge" as simply what is believed, or what beliefs are "institutionalized" in this or that community, culture, or context. They seek to identify the social forces and influences responsible for knowledge production so conceived. Social epistemology is theoretically significant because of the central role of society in the knowledge-forming process. It also has practical importance because of its possible role in the redesign of information-related social institutions. (shrink)

In the social epistemology of scientific knowledge, it is largely accepted that relationships of trust, not just reliance, are necessary in contemporary collaborative science characterised by relationships of opaque epistemic dependence. Such relationships of trust are taken to be possible only between agents who can be held accountable for their actions. But today, knowledge production in many fields makes use of AI applications that are epistemically opaque in an essential manner. This creates a problem for the social epistemology of scientific (...) knowledge, as scientists are now epistemically dependent on AI applications that are not agents, and therefore not appropriate candidates for trust. (shrink)