J. P. Grodniewicz

Autistic people often hide or alter their behavior in order to meet societal expectations and fit in—a phenomenon known as masking. Masking has important benefits for neurodivergent individuals, from increasing social acceptance to enhancing their career opportunities and ability to navigate social hierarchies. But it also comes with significant costs. It often leads to mental and emotional exhaustion, increased anxiety, delayed or missed diagnosis, or even suicidal ideation. In this paper, we focus on a relatively underexplored cost of masking, namely, its negative impact on subjects’ self-understanding. We appeal to the framework of mindshaping, which suggests that our thoughts, behaviors, and mental states are shaped by the social norms and expectations to which we are exposed, and argue that masking can be conceptualized as a natural reaction of neurodivergent individuals to neurotypical mindshaping. As a result, we suggest, masking commonly leads to an experience that can be characterized as “self-mask ambiguity”—a failure to demarcate and differentiate oneself from one’s mask. In light of this, we consider ways in which masking and self-mask ambiguity can diminish individuals’ self-understanding. We finish by discussing how diagnosis and unmasking can lead to a deepening of one’s self-understanding.

By offering explanations, we help each other understand the world. But not all explanations are created equal. In this paper, we argue that, while the practice of explaining is unified by its function—the dissemination of understanding—there are different ways to engage in it. We can do so by offering what we call a minimal explanation, a customized explanation, or an interactive explanation. Each of them is appropriate in different contexts and comes with a set of relevant expectations. Moreover, each is guided by a specific norm. Only when we take all these ways of participating in the practice of explaining into account will we be able to spell out what is expected from explainers in different situations. As a result, we will be able to tell good explainers from bad ones by assessing whether they fulfill the relevant norm and thus offer explanations appropriate for a given context.

Psychotherapy is a form of psychological service that involves a collaborative process based on the relationship between a psychotherapist and a client/patient. The epistemic interdependence between psychotherapists and clients raises important questions concerning epistemic authority and power, as well as epistemic injustice, i.e., a kind of injustice that arises when one’s capacity as an epistemic agent is wrongfully denied. In this paper, we characterize, categorize, and discuss how epistemic injustice can be perpetrated in psychotherapy. To this end, we provide scenarios that illustrate ways in which three forms of epistemic injustice (testimonial, hermeneutical, and participatory) can arise in psychotherapeutic encounters, and explain how these forms of epistemic injustice threaten one’s ability to achieve self-understanding through psychotherapy. We finish by making some qualifications and briefly enumerating some ways to mitigate the risk of epistemic injustice in psychotherapy.

Most psychotherapeutic approaches are, to a greater or lesser extent, rooted in the theories and principles of scientific psychology. Nevertheless, in-session psychotherapeutic interaction between a therapist and a client is, at its core, a folk-psychological practice. As such, it is based on folk-psychological skills and competencies. But which ones exactly? This chapter argues that, while we may initially be inclined to perceive the practice of psychotherapy as primarily involving sophisticated mindreading on the part of both the therapist and the client/patient, a complete characterization of psychotherapy must give at least the same amount of attention to different forms of therapeutic mindshaping. Using examples drawn from multiple therapeutic traditions, I illustrate how therapeutic mindreading and mindshaping interact. I conclude by highlighting some of the consequences of this perspective for the ethics and politics of psychotherapy.

According to the cognitive model of psychopathology, maladaptive beliefs about oneself, others, and the world are the main factors contributing to the development and persistence of various forms of mental suffering. Therefore, the key therapeutic process of Cognitive Behavioral Therapy (CBT)—a therapeutic approach rooted in the cognitive model—is cognitive restructuring, i.e., a process of revision of such maladaptive beliefs. In this paper, I examine the philosophical assumptions underlying CBT and offer theoretical reasons to think that the effectiveness of belief revision in psychotherapy is very limited. This is the case, I argue, because the cognitive model wrongly assumes that our body of beliefs is unified, while it is in fact fragmented.

Conversational Artificial Intelligence (CAI) systems (also known as AI “chatbots”) are among the most promising examples of the use of technology in mental health care. With already millions of users worldwide, CAI is likely to change the landscape of psychological help. Most researchers agree that existing CAIs are not “digital therapists” and using them is not a substitute for psychotherapy delivered by a human. But if they are not therapists, what are they, and what role can they play in mental health care? To answer these questions, we appeal to two well-established and widely discussed concepts: cognitive and affective artifacts. Cognitive artifacts are artificial devices contributing functionally to the performance of a cognitive task. Affective artifacts are objects which have the capacity to alter subjects’ affective state. We argue that therapeutic CAIs are a kind of cognitive-affective artifacts which contribute to positive therapeutic change by (i) simulating a (quasi-)therapeutic interaction, (ii) supporting the performance of cognitive tasks, and (iii) altering the affective condition of their users. This sheds new light on why virtually all existing mental health CAIs implement principles and techniques of Cognitive Behavioral Therapy — a therapeutic orientation according to which affective change and, ultimately, positive therapeutic change is mediated by cognitive change. Simultaneously, it allows us to conceptualize better the potential and limitations of applying these technologies in therapy.

The nature of linguistic understanding is a much-debated topic. Among the issues that have been discussed, two questions have recently received a lot of attention: (Q1) ‘Are states of understanding direct (i.e. represent solely what is said) or indirect (i.e. represent what is said as being said/asserted)?’ and (Q2) ‘What kind of mental attitude is linguistic understanding (e.g. knowledge, belief, seeming)?’ This paper argues that, contrary to what is commonly assumed, there is no straightforward answer to either of these questions. This is because linguistic understanding cannot be identified with a single mental attitude towards a particular representation. Instead, we should characterize states of linguistic understanding as involving complex representational structures generated by a dual-stream process. The first stream operates on direct representations of what is said, while the second operates on representations of what is said as being said/asserted by a given source. Both these streams feed a situation model, i.e. a complex representation of a state of affairs described by a given piece of discourse.

Growing demand for broadly accessible mental health care, together with the rapid development of new technologies, trigger discussions about the feasibility of psychotherapeutic interventions based on interactions with Conversational Artificial Intelligence (CAI). Many authors argue that while currently available CAI can be a useful supplement for human-delivered psychotherapy, it is not yet capable of delivering fully fledged psychotherapy on its own. The goal of this paper is to investigate what are the most important obstacles on our way to developing CAI systems capable of delivering psychotherapy in the future. To this end, we formulate and discuss three challenges central to this quest. Firstly, we might not be able to develop effective AI-based psychotherapy unless we deepen our understanding of what makes human-delivered psychotherapy effective. Secondly, assuming that it requires building a therapeutic relationship, it is not clear whether psychotherapy can be delivered by non-human agents. Thirdly, conducting psychotherapy might be a problem too complicated for narrow AI, i.e., AI proficient in dealing with only relatively simple and well-delineated tasks. If this is the case, we should not expect CAI to be capable of delivering fully-fledged psychotherapy until the so-called “general” or “human-like” AI is developed. While we believe that all these challenges can ultimately be overcome, we think that being mindful of them is crucial to ensure well-balanced and steady progress on our path to AI-based psychotherapy.

In their thought-provoking article, Sedlakova and Trachsel (2023) defend the view that the status—both epistemic and ethical—of Conversational Artificial Intelligence (CAI) used in psychotherapy is complicated. While therapeutic CAI seems to be more than a mere tool implementing particular therapeutic techniques, it falls short of being a “digital therapist.” One of the main arguments supporting the latter claim is that even though “the interaction with CAI happens in the course of conversation… the conversation is profoundly different from a conversation with a human therapist” (Sedlakova and Trachsel 2023, 8). In particular, unlike a human therapist, CAI cannot help its users gain new insight and self-understanding (Sedlakova and Trachsel 2023). We agree that currently available therapeutic CAI cannot be considered a “digital therapist,” however, we think that the issue surrounding the acquisition of new self-understanding in the interaction with therapeutic CAI is more complicated than Sedlakova and Trachsel suggest.

It is often suggested that we are equipped with a set of cognitive tools that help us to filter out unreliable testimony. But are these tools effective? I answer this question in two steps. Firstly, I argue that they are not real-time effective. The process of filtering, which takes place simultaneously with or right after language comprehension, does not prevent a particular hearer on a particular occasion from forming beliefs based on false testimony. Secondly, I argue that they are long-term effective. Some hearers sometimes detect false testimony, which increases speakers’ incentives for honesty and stabilizes the practice of human communication in which deception is risky and costly. In short, filtering prevents us from forming a large number of beliefs based on false testimony, not by turning each of us into a high-functioning polygraph but by turning the social environment of human communication into one in which such polygraphs are not required. Finally, I argue that these considerations support strong anti-reductionism about testimonial entitlement.

What justifies our beliefs about what other people say? According to epistemic inferentialism​, the justification of comprehension-based beliefs depends on the justification of other beliefs, e.g., beliefs about what words the speaker uttered or even what sounds they produced. According to epistemic non-inferentialism, the justification of comprehension-based beliefs ​does not depend on the justification of other beliefs. This paper offers a new defense of epistemic non-inferentialism. First, I discuss three counterexamples to epistemic non-inferentialism provided recently by Brendan Balcerak Jackson. I argue that only one of Balcerak Jackson’s counterexamples is effective, and that it is effective against only one version of epistemic non-inferentialism, viz. language comprehension dogmatism. Second, I propose an alternative version of epistemic non-inferentialism, viz. comprehension-process reliabilism, which is immune to these counterexamples. I conclude that we should follow Balcerak Jackson in his rejection of language comprehension dogmatism but not all the way to the endorsement of epistemic inferentialism. Comprehension-process reliabilism is superior to both these alternatives.

The majority of our linguistic exchanges, such as everyday conversations, are divided into turns; one party usually talks at a time, with only relatively rare occurrences of brief overlaps in which there are two simultaneous speakers. Moreover, conversational turn-taking tends to be very fast. We typically start producing our responses before the previous turn has finished, i.e., before we are confronted with the full content of our interlocutor’s utterance. This raises interesting questions about the nature of linguistic understanding. Philosophical theories typically focus on linguistic understanding characterized either as an ability to grasp the contents of utterances in a given language or as outputs of this ability—mental states of one type or another. In this paper, I supplement these theories by developing an account of the process of understanding. I argue that it enables us to capture the dynamic and temporal aspect of understanding and reconcile philosophical investigations with empirical research on language comprehension.

This paper offers a critical review of the notion of a “singular cognitive role”, which is central to some recent theories of singular thought. According to those theories, whether a thought is singular depends on the role it plays in the subject’s cognitive activity. We compare the two most developed accounts of this type: Crane’s :21–43 2011, The Objects of Thought2013) and Jeshion’s. Both theories aim to capture the notion of a singular cognitive role in terms of mental files. We argue that Jeshion’s theory is much more promising as it provides a more detailed and non-circular characterization of the mental files responsible for singular thinking. We examine the prospects for enhancing that account in light of three major concerns about it present in the literature. First, we discuss whether the weakest aspect of the whole proposal, i.e. the condition for the initiation of mental files, can be replaced without debilitating the rest of the theory. Second, we examine Goodman’s : 437–461 2014, The Philosophical Quarterly2015) argument against mental file theories of singular thought and show that it does not affect Jeshion’s account. Third, we argue against Sawyer :264–283 2012) that Jeshion’s notion of a singular cognitive role is in strong opposition to acquaintance-based theories of singular thought and cannot be incorporated into any of them. Thus, the paper concludes that Jeshion’s proposal, despite its shortcomings, is currently the most promising account of a singular cognitive role.