One of the central questions in the epistemology of conversational AIs is how to classify the beliefs acquired from them. Two promising candidates are instrument-based and testimony-based beliefs. However, the category of instrument-based beliefs faces an intrinsic problem, and a challenge arises in its application. On the other hand, relying solely on the category of testimony-based beliefs does not encompass the totality of our practice of using conversational AIs. To address these limitations, I propose a novel classification of beliefs that (...) shifts the focus from the properties of the conversational AIs themselves to how recipients perceive AI output, specifically whether they take the output at face value. The proposed categories are beliefs by regarding as instruments and beliefs by regarding as testifiers. By using these complementary categories, a more comprehensive understanding of beliefs acquired from conversational AIs can be achieved while avoiding the problems associated with the traditional classification. (shrink)

The Credit Theory of Knowledge (CTK)—as expressed by such figures as John Greco, Wayne Riggs, and Ernest Sosa—holds that knowing that p implies deserving epistemic credit for truly believing that p . Opponents have presented three sorts of counterexamples to CTK: S might know that p without deserving credit in cases of (1) innate knowledge (Lackey, Kvanvig); (2) testimonial knowledge (Lackey); or (3) perceptual knowledge (Pritchard). The arguments of Lackey, Kvanvig and Pritchard, however, are effective only in so far as (...) one is willing to accept a set of controversial background assumptions (for instance, that innate knowledge exists or that doxastic voluntarism is wrong). In this paper I mount a fourth argument against CTK, that doesn’t rest on any such controversial premise, and therefore should convince a much wider audience. In particular, I show that in cases of extended cognition (very broadly conceived), the most salient feature explaining S ’s believing the truth regarding p may well be external to S , that is, it might be a feature of S ’s (non-human, artifactual) environment. If so, the cognitive achievement of knowing that p is not (or only marginally) creditable to S , and hence, CTK is false. (shrink)

Contrary to current individualistic epistemology, Classical rhetoric provides us with a pragmatical and particularly dynamic conception of ‘testimony’ as a source made available for the orator by the particular community in which she acts. In order to count as usable testimony, a testimony to which one could appeal in further communications, any discourse must comply with specific rules of social sanction. A deliberate attention to the social practices in which testimony is given and assessed may offer us a more accurate (...) view of its epistemological role. (shrink)

People increasingly form beliefs based on information gained from automatically filtered Internet ‎sources such as search engines. However, the workings of such sources are often opaque, preventing ‎subjects from knowing whether the information provided is biased or incomplete. Users’ reliance on ‎Internet technologies whose modes of operation are concealed from them raises serious concerns about ‎the justificatory status of the beliefs they end up forming. Yet it is unclear how to address these concerns ‎within standard theories of knowledge and justification. (...) To shed light on the problem, we introduce a ‎novel conceptual framework that clarifies the relations between justified belief, epistemic responsibility, ‎action, and the technological resources available to a subject. We argue that justified belief is subject to ‎certain epistemic responsibilities that accompany the subject’s particular decision-taking circumstances, ‎and that one typical responsibility is to ascertain, so far as one can, whether the information upon which ‎the judgment will rest is biased or incomplete. What this responsibility comprises is partly determined by ‎the inquiry-enabling technologies available to the subject. We argue that a subject’s beliefs that are ‎formed based on Internet-filtered information are less justified than they would be if she either knew how ‎filtering worked or relied on additional sources, and that the subject may have the epistemic ‎responsibility to take measures to enhance the justificatory status of such beliefs.‎. (shrink)

Recently, Dan O’Brien has argued that there are situations in which a hearer can gain testimonial knowledge from a speaker who is lying. In order to make his case, O’Brien presents two examples where a speaker lies to a hearer, but supposedly the hearer comes to have testimonial knowledge on the basis of the lying speaker’s testimony. O’Brien claims that his examples demonstrate that lies can be used to pass on knowledge in a non-inferential fashion. I argue that O’Brien is (...) mistaken. More specifically, I argue that the hearer’s belief in the second example that O’Brien depicts fails to meet two plausible conditions for knowledge. First, the hearer’s belief fails to satisfy the requirements of the epistemic basing relation. Second, the hearer’s belief is not safe. (shrink)

According to widely accepted views in metasemantics, the outputs of chatbots and other artificial text generators should be meaningless. They aren’t produced with communicative intentions and the systems producing them are not following linguistic conventions. Nevertheless, chatbots have assumed roles in customer service and healthcare, they are spreading information and disinformation and, in some cases, it may be more rational to trust the outputs of bots than those of our fellow human beings. To account for the epistemic role of chatbots (...) in our society, we need to reconcile these observations. This paper argues that our engagement with chatbots should be understood as a form of prop-oriented make-believe; the outputs of chatbots are literally meaningless but fictionally meaningful. With the make-believe approach, we can understand how chatbots can provide us with knowledge of the world through quasi-testimony while preserving our metasemantic theories. This account also helps to connect the study of chatbots with the epistemology of scientific instruments. (shrink)

An utterer may convey a message to her intended audience by means of an explicit statement; or by a non‐conventionally mediated one‐off signal from which the audience is able to work out the intended message; or by conversational implicature. I investigate whether the last two are equivalent to explicit testifying, as communicative act and epistemic source. I find that there are important differences between explicit statement and insinuation; only with the first does the utterer assume full responsibility for the truth (...) of what she communicates to her audience. (shrink)

This paper discusses the epistemology of the Internet of Things [IoT] by focusing on the topic of trust. It presents various frameworks of trust, and argues that the ethical framework of trust is what constitutes our responsibility to reveal desired norms and standards and embed them in other frameworks of trust. The first section briefly presents the IoT and scrutinizes the scarce philosophical work that has been done on this subject so far. The second section suggests that the field of (...) epistemology is not sufficiently capable of dealing with technologies, and presents a possible solution to this problem. It is argued that knowledge is not only social phenomena, but also a technological one, and that in order to address epistemological issues in technology, we need to carefully depart from traditional epistemic analysis and form a new approach that is technological (termed here Techno-Epistemology). The third and fourth sections engage in an epistemic analysis of trust by dividing it in to various frameworks. The last section argues that these various frameworks of trust can be understood to form a trustworthy large-scale socio-technological system, emphasizing the place of ethical trust as constituting our commitment to give proper accounts for all of the other frameworks. (shrink)

This paper discusses Richard Moran’s account of testimony. Moran argues for the idea that a person who testifies should be considered as giving assurance rather than providing evidence for her assertion. For Moran, it is the fact that the speaker stands by her assertion P that should be the hearer’s reason for believing P. I argue that, even if this claim is true, the speaker’s assurance should be considered as weak and untenable by itself. I draw my argument from the (...) role of sincerity in testimony. Moran views sincerity as giving access to what the speaker assumes responsibility for, but I contend that the view is too optimistic. Sincerity does not guarantee access to the speaker’s commitment to her own words, and for this reason, it is unclear whether the assurance from sincere testimony is a good reason for belief. (shrink)

In this paper, I outline and investigate the notion of computational beliefs: beliefs formed on the basis of a deliverance from a machine learning algorithm. Given the increased usage of such algorithms through smart devices, such beliefs are becoming increasingly common in everyday life. First, I argue that such beliefs can be successful (i.e. justified and true) by outlining particular examples that possess epistemic properties taken to be indicative of successful beliefs (i.e. being a reason for action, being reliable, being (...) safe, and being sensitive). I then outline how computational beliefs are best understood as a form of what Sosa (2006) describes as instrumental beliefs. As such, it may be thought that computational beliefs hold little epistemological interest insofar as they are reducible to more basic epistemic processes that are already the focus of epistemological attention. However, in the final section, I argue that computational beliefs hold epistemological importance insofar as they have specific epistemically normative repercussions i.e. they give rise to epistemic responsibility gaps. (shrink)