Guido Löhr

How can we capture the intuitive distinction between lying and misleading? According to a traditional view, the difference boils down to whether the speaker is saying (as opposed to implying) something that they believe to be false. This view is subject to known objections; to overcome them, an alternative view has emerged. For the alternative view, what matters is whether the speaker can consistently deny that they are committed to knowing the relevant proposition. We point out serious flaws for this alternative view, and sketch a simpler alternative that incorporates key insights of the traditional view.

Advancements in artificial intelligence and (social) robotics raise pertinent questions as to how these technologies may help shape the society of the future. The main aim of the chapter is to consider the social and conceptual disruptions that might be associated with social robots, and humanoid social robots in particular. This chapter starts by comparing the concepts of robots and artificial intelligence and briefly explores the origins of these expressions. It then explains the definition of a social robot, as well as the definition of humanoid robots. A key notion in this context is the idea of anthropomorphism: the human tendency to attribute human qualities, not only to our fellow human beings, but also to parts of nature and to technologies. This tendency to anthropomorphize technologies by responding to and interacting with them as if they have human qualities is one of the reasons why social robots (in particular social robots designed to look and behave like human beings) can be socially disruptive. As is explained in the chapter, while some ethics researchers believe that anthropomorphization is a mistake that can lead to various forms of deception, others — including both ethics researchers and social roboticists — believe it can be useful or fitting to treat robots in anthropomorphizing ways. The chapter explores that disagreement by, among other things, considering recent philosophical debates about whether social robots can be moral patients, that is, whether it can make sense to treat them with moral consideration. Where one stands on this issue will depend either on one’s views about whether social robots can have, imitate, or represent morally relevant properties, or on how people relate to social robots in their interactions with them. Lastly, the chapter urges that the ethics of social robots should explore intercultural perspectives, and highlights some recent research on Ubuntu ethics and social robots.

The claim I want to explore in this paper is simple. In social ontology, Margaret Gilbert, Abe Roth, Michael Bratman, Antonie Meijers, Facundo Alonso and others talk about rights or entitlements against other participants in joint action. I employ several intuition pumps to argue that we have reason to assume that such entitlements or rights can be ascribed even to non-sentient robots that we collaborate with. Importantly, such entitlements are primarily identified in terms of our normative discourse. Justified criticism, for example, presupposes that another person acted wrongly, i.e., was not entitled to this action. Praise is supposed to encourage another person and acknowledge that one did more than one was obligated to. I show that such normative talk serves the same function when cooperating with robots. This, I argue, suggests that they have the same kind of entitlements and duties at least in the context of a joint action.

Recent evidence suggests that participants without extensive training in philosophy (so-called lay people) have difficulties responding consistently when confronted with Robert Nozick’s Experience Machine thought experiment. For example, some of the participants who reject the experience machine for themselves would still advise a stranger to enter the machine permanently. This and similar findings have been interpreted as evidence for implicit biases that prevent lay people from making rational decisions about whether the experience machine is preferable to real life, which might have consequences for one of the strongest objections to philosophical hedonism (the view that pleasure is the only intrinsic value). Against this consequence, it has been argued that expert philosophers are immune to such biases (the so-called expertise defense). In this paper, I report empirical evidence against this expertise defense.

A philosopher argues that state-sponsored cyberattacks against central military or civilian targets are always acts of war. What is this philosopher doing? According to conceptual analysts, the philosopher is making a claim about our concept of war. According to philosophical realists, the philosopher is making a claim about war per se. In a quickly developing literature, a third option is being explored: the philosopher is engineering the concept of war. On this view, the philosopher is making a proposal about which concept we should have – even if it deviates from the extant concept, and even if it does not capture ‘what war really is’. The activity or method of proposing such revisionary definitions, as well as the metaphilosophical reflection on it, has become known as conceptual engineering.

I discuss Edouard Machery’s claim that philosophers and psychologists when using the term ‘concept’ are really theorizing about different things. This view is not new, but it has never been developed or defended in detail. Once spelled out, we can see that Machery is right that the psychological literature uses a different notion of concept. However, Machery fails to acknowledge that the two notions are not only compatible but complementary. This fits more with the traditional view according to which philosophers and psychologists are merely interested in different aspects of the same kind. The main aim of this paper is then to show how precisely the two notions of ‘concept’ relate. Distinguishing them resolves the long-standing debate on whether concepts can be prototypes and allows me to formulate success conditions of a theory of categorization that are independent of the success conditions of a theory of concepts.

On a representationalist view, conceptual engineering is the practice of changing the extensions and intensions of the devices we use to speak and think. But if this view holds true, conceptual engineering has a bad rationale. Extensions and intensions are not the sorts of things that are better or worse as such. A representationalist account of conceptual engineering thus falls prey to the objection that the practice has a bad rationale. To account for the assumption that conceptual engineering is worthwhile, we propose to view what is being engineered as inferential devices, as opposed to representational devices. The objective is not to establish that being or having an inferential role is all there is to meaning or conceptual content. Rather, our agenda is to recommend a shift of focus from the representational features of content to the inferential features of content for the purposes of doing and thinking about conceptual engineering. Inferentialism about conceptual engineering makes better sense of the practice than a representationalist approach: In addition to accounting for the rationality of engaging in conceptual engineering, inferentialism provides a sound interpretation of what is at stake in concrete examples of conceptual engineering.

It is largely assumed that conceptual engineering is essentially about revising, introducing, or eliminating representational devices, in particular the intension and extension of words and concepts. However, tying conceptual engineering too closely to representations is risky. Not everyone endorses the notion of representation as theoretically helpful or even real. Not everyone thinks that concepts or meanings should be understood in terms of the notion of representation. Does this mean that conceptual engineering is not interesting or relevant for these skeptics? In this paper, I motivate and propose a non-representationalist construal of conceptual engineering. I argue that conceptual engineers can be understood as primarily engineering linguistic entitlements and commitments rather than representational devices. Note that this account is non-representationalist, but explicitly not anti-representationalist. Representations may play a significant role when it comes to justifying and completing commitment engineering projects.

Invariantists argue that the notion of concept in psychology should be reserved for knowledge that is retrieved in a context-insensitive manner. Contextualists argue that concepts are to be understood in terms of context-sensitive ad hoc constructions. I review the central empirical evidence for and against both views and show that their conclusions are based on a common mischaracterization of both theories. When the difference between contextualism and invariantism is properly understood, it becomes apparent that the way the question of stability is currently investigated will not lead to a consensus. Instead of focusing directly on stability, we should turn our attention to other desiderata on a theory of concepts. In particular, I show that invariantism, but not contextualism, fails to account for compositionality and abstract concepts.

An explanation of how we acquire concepts of kinds if they are socially constructed is a desideratum both for a successful account of concept acquisition and a successful account of social constructionism. Both face the so-called “mismatch problem” that is based on the observation that that there is often a mismatch between the descriptions proficient speakers associate with a word and the properties that its referents have in common. I argue that externalist theories of reference provide a plausible and attractive account of concept acquisition, including the acquisition of concepts of social constructs, that avoids the mismatch problem. However, externalist theories are ontologically and psychologically highly demanding, which places strong constraints on accounts of the metaphysics of socially constructed kinds. In particular, they require a rather strong form of realism that is incompatible with some but not all theories of social constructionism. Finally, I show that these demands can be met by means of adopting a homeostatic property cluster view of natural kinds.

Polysemy has only recently entered the debate on semantic minimalism and contextualism. This is surprising considering that the key linguistic examples discussed in the debate, such as ‘John cut the grass’ or ‘The leaf is green’ appear to be prime examples of polysemy. Moreover, François Recanati recently argued that the mere existence of polysemy falsi!es semantic minimalism and supports radical contextualism. The aim of this paper is to discuss how the minimalism-contextualism debate relates to polysemy. This connection turns out to be far from clear-cut. This is partly due to the fact that the term ‘polysemy’ is used in a number of different ways in the literature, which will be reviewed in this paper. Finally, I discuss and reject Recanati’s claim that the existence of polysemy supports radical contextualism against moderate versions and semantic minimalism. I show that minimalism has a number of plausible options to account for polysemy.

In psycholinguistics, concepts are considered abstract if they do not apply to physical objects that we can touch, see, feel, hear, smell or taste. Psychologists usually distinguish concrete from abstract concepts by means of so-called _concreteness ratings_. In concreteness rating studies, laypeople are asked to rate the concreteness of words based on the above criterion. The wide use of concreteness ratings motivates an assessment of them. I point out two problems: First, most current concreteness ratings test the intuited concreteness of word forms as opposed to concepts. This ignores the ubiquitous phenomenon of lexical ambiguity. Second, the criterion of abstract concepts that the instruction texts of rating studies rely on does not capture the notion that psychologists working on abstract concepts are normally interested in, i.e., concepts that could reasonably be sensorimotor representations. For many concepts that pick out physical objects, this is not reasonable. In this paper, I propose a characterization of concrete and abstract concepts that avoids these two problems and that may be useful for future studies in psychology.

New technologies have the potential to severely “challenge” or “disrupt” not only our established social practices but our most fundamental concepts and distinctions like person versus object, nature versus artificial or being dead versus being alive. But does this disruption also change these concepts? Or does it merely change our operationalizations and applications of the same concepts? In this paper, I argue that instead of focusing on individual conceptual change, philosophers of socially disruptive technologies (SDTs) should think about conceptual change as a change in a network of interrelated concepts. What really generates a potential social disruption are changes of inferential relations between concepts – whether or not this entails a change of the respective individual concepts. Philosophers of socially disruptive technologies are therefore in the privileged position of being able to avoid commitments regarding the individuation of individual concepts.

There are two general views that social ontologists currently defend concerning the nature of joint intentional action. According to ‘non-normativists’, for a joint action to be established, we need to align certain psychological states in certain ways. ‘Normativists’ argue that joint action essentially involves normative relations that cannot be reduced to the intentional states of individuals. In two ground-breaking publications, Javier Gomez-Lavin and Matthew Rachar empirically investigate the relation between normativity and joint action in several survey studies. They argue that people's intuitions support neither current normativists nor current non-normativists. They suggest that there is a need for a ‘new normativism of joint action’. I first explore what a new normativism could amount to and conclude that the authors’ findings cannot support a demand for such a view. Finally, I suggest some ideas about how to move the field forward.

Conceptual Engineering (CE) is thought to be generally aimed at ameliorating deficient concepts. In this paper, we challenge this assumption: we argue that CE is frequently undertaken with the orthogonal aim of _conceptual adaptation_. We develop this thesis with reference to the interplay between technology and concepts. Emerging technologies can exert significant pressure on conceptual systems and spark ‘conceptual disruption’. For example, advances in Artificial Intelligence raise the question of whether AIs are agents or mere objects, which can be construed as a CE question regarding the concepts AGENT and OBJECT. We distinguish between three types of conceptual disruption (conceptual gaps, conceptual overlaps, and conceptual misalignments) and argue that when CE occurs to address these disruptions, its primary aim is not to improve concepts, but to retain their functional quality, or to prevent them from degrading. This is the characteristic aim of CE when undertaken in philosophy of technology: to _preserve_ the functional role of a concept or conceptual scheme, rather than _improving_ how a concept fulfills its respective function.

Several authors in psychology and philosophy have recently raised the following question: when is it permissible to intentionally change the meaning and use of our words and concepts? I argue that an arguably prior question has received much less attention: Even if there were good moral or epistemic reasons for conceptual or semantic changes, this does not yet justify pushing or lobbying for such changes if they are socially and conceptually disruptive. In this paper, I develop the beginnings of an ethics of conceptual disruption as well as a set of norms of linguistic interventions based on it.

According to predictive processing, an increasingly influential paradigm in cognitive science, the function of the brain is to minimize the prediction error of its sensory input. Conceptual engineering is the practice of assessing and changing concepts or word meanings. We contribute to both strands of research by proposing the first cognitive account of conceptual engineering, using the predictive processing framework. Our model reveals a new kind of implementation problem as prediction errors are only minimized if enough agents embrace conceptual changes. This problem can be overcome by emphasizing the importance of social norms and conceptual pluralism.

Concept eliminativists argue that we should eliminate the term ‘concept’ from our vocabulary in psychology because there is no single natural kind that is picked out by it. I argue that the most developed version of concept eliminativism by Edouard Machery depends on the assumption that concepts are defined as stable and context-independent bodies of information. It is this assumption that leads Machery to eliminativism and it is an assumption we have reason to reject. Another assumption that leads to the eliminativist conclusion and that we have reason to reject is that the type of content represented in long-term memory is the relevant property based on which we should individuate certain natural kinds in cognitive psychology. Finally, I argue that certain pieces of information are functionally integrated enough to meet the conditions for being a natural kind.

Many psychologists currently assume that there is a psychologically real distinction to be made between concepts that are abstract and concepts that are concrete. It is for example largely agreed that concepts and words are more easily processed if they are concrete. Moreover, it is assumed that this isbecausethese words and concepts are concrete. It is thought that interesting generalizations can be made about certain conceptsbecausethey are concrete. I argue that we have surprisingly little reason to believe that the abstract‐concrete distinction is psychologically real.

Emerging technologies can have profound conceptual implications. Their emergence frequently calls for the articulation of new concepts, or for modifications and novel applications of concepts that are already entrenched in communication and thought. In this paper, we introduce the notion of “conceptual appropriation” to capture the dynamics between concepts and emerging technologies. By conceptual appropriation, we mean the novel application of a value-laden concept to lay a contestable claim on an underdetermined phenomenon. We illustrate the dynamics of conceptual appropriation by analyzing the concept NATURE and its uptake in three discourses of emerging technology: cellular agriculture, solar geo-engineering, and biomimicry. We argue that NATURE and its cognate NATURALNESS are strongly valanced concepts upon which different stakeholders lay a claim. In doing so, stakeholders advance distinct conceptions of nature, typically to suit their own interests. Our case-studies illustrate how in discourses on emerging technology, the application of value-concepts is entangled with ideological stakes and power dynamics.

In Löhr and Michel (2022), we proposed a neurocognitive model within the predictive processing paradigm for acceptability intuitions about copredication sentences. We also addressed “predicate order effects,” the phenomenon that the acceptability of copredication sentences can vary with the order in which the predicates occur. We discussed Murphy's interpretation of order preferences based on a hierarchy of semantic complexity and tried to motivate that other interpretations are worthwhile pursuing. In a reply letter, Murphy (2022) takes issue with our approach, putting forward several purported methodological and conceptual issues with our paper. In this reply, we first clarify where exactly we agree and disagree. Second, we focus on a crucial equivocation and some misrepresentations of our proposal by Murphy.

The aim of this commentary is to underpin Duffley’s notion of a stable mental content that corresponds to the literal word meaning with a computationally plausible cognitive theory. Our approach is to investigate what these stable contents could be according to the so-called Predictive Processing architecture. We argue that recent advances in cognitive science can make at least two contributions to the debate. First, they can provide some underpinning of Duffley's ideas of a stable linguistic meaning associated with the sign. Second, they provide resources to understand how the semiological principle is compatible with a dynamic and flexible notion of "meaning".