Albert Newen

If we want to account for mental representations (MRs) as being used in scientific explanations and realized by neural correlates in biological systems, then we have to give up the traditional Fodorian view of rigid symbolic MRs. However, we do not have to throw out the baby with the bathwater and accept anti-representationalism. Instead this chapter offers a new account of mental representations as _real, nonstable, use-dependent, and situated_. As such, they can be pivotal constituents of scientific explanations. The chapter demonstrates the empirical adequacy of this account by discussing cases of birds and rats relying on what-where-when memory. It argues that we need to involve nonlinguistic MRs to adequately account for their abilities. In this way, the alternative theory presented here provides a detailed description of _situated mental representations_: it combines a _functionalist account of MR with a relational dimension that can vary with the situation type and that allows for nonstatic constructions of MRs in specific contexts._.

Trust is a basic feeling and attitude. It shapes human relations as the glue that holds groups and even societies together. Now that AI is increasingly prevalent in our daily lives, the extent to which we can trust these systems has become a key question. It can be discussed from a psychological person perspective (“Under which conditions are we inclined to trust AI systems?”) or from an objective systems perspective (“Under which conditions is a system worthy of trust, and to what degree?”). To offer a general framework for comparing different systems, we adopt a system-level perspective, abstracting from subjective psychological conditions. An especially innovative aspect of this comparative framework is its integration of two dimensions: uncertainty (currently a hot topic in AI research) and commitment (a rather new one for AI systems). This allows us compare certain AI systems, like ChatGPT or autonomous cars, to more familiar systems, like classical (non-autonomous) cars and (prototypical) democratic institutions. We can therefore clarify in which dimensions they differ. This overview can be used both to understand specific features of AI systems and to reveal deficits in their trustworthiness that must be overcome to make AI systems acceptable. Despite intense and widespread discussion of whether and to what degree we can trust AI systems, we still lack a general framework for any systematic comparison of trustworthiness. Our account is supposed to develop further and improve the famous analysis of Glikson & Wooley (2020) by proposing a multidimensional framework of trustworthiness, with three central steps. First, drawing on noteworthy articles in the existing literature, we identify six central dimensions of trust from a general perspective: objective functionality, transparency, uncertainty (quantification), embodiment, immediacy behaviors, and commitment. Second, we develop a more detailed perspective, partially characterizing each dimension by detailing several of its specific features. Finally, we show how we can evaluate each feature of any dimension (implemented as low, medium, or high) and thereby calculate an average value for each dimension a system has. This results in a multidimensional account of trust that allows us compare different systems’ trustworthiness as a basis for the future development of AI systems.

We develop a version of a direct perception account of emotion recognition on the basis of a metaphysical claim that emotions are individuated as patterns of characteristic features. On our account, emotion recognition relies on the same type of pattern recognition as is described for object recognition. The analogy allows us to distinguish two forms of directly perceiving emotions, namely perceiving an emotion in the absence of any top-down processes, and perceiving an emotion in a way that significantly involves some top-down processes ; and, in addition, an inference-based evaluation of an emotion. Our model clarifies the epistemology of emotion recognition

Studies in economic decision-making have demonstrated that individuals appreciate social values supporting equity and disapprove unfairness when distributing goods between two or more parties. However, this seems to critically depend on psychological mechanisms partly pertaining to the ingroup–outgroup distinction. Little is known as to what extent economic bargaining can be manipulated by means of psychological interventions such has hypnosis. Here we show that a hypnotic ingroup versus outgroup suggestion impacts the tolerance of unfairness in an Ultimatum Game. Specifically, the ingroup suggestion was associated with significantly greater acceptance rates of unfair offers than the outgroup suggestion, whereas hypnosis alone exerted only small effects on unfairness tolerance. These findings indicate that psychological interventions such as hypnotic suggestion can contribute to ingroup favoritism and outgroup rejection.

How can we develop an adequate scientific understanding of the minds of nonhuman animals? We argue for a methodology based on multi-dimensional profile accounts. Such accounts are already used for the comparative study of norm cognition, consciousness, empathy and causal cognition, among others. This methodology demands that a cognitive capacity is characterized by a set of independent dimensions where each dimension is connected to operationalizable empirical indicators. Based on the level of realization for each indicator the level of implementation of a dimension is determined for a species, resulting in a multi-dimensional profile for each species. We analyze what this methodology is committed to. Then, we argue that this methodology has several benefits over competing unidimensional methodologies, by overcoming intractable disagreements, capturing the evolutionary continuity of cognition, alleviating anthropocentrism, and delivering more informative accounts of animal cognition. By demonstrating how this multidimensional methodology can be fruitfully combined with a methodology which focuses on the search for natural kinds in comparative cognition, we address the most important objection to the multidimensional profile methodology. We conclude that multidimensional profile accounts of all complex cognitive capacities should be developed and then used to facilitate scientific understanding of animal minds.

The science of animal consciousness investigates (i) which animal species are conscious (the distribution question) and (ii) how conscious experience differs in detail between species (the quality question). We propose a framework which clearly distinguishes both questions and tackles both of them. This two-tier account distinguishes consciousness along ten dimensions and suggests cognitive capacities which serve as distinct operationalizations for each dimension. The two-tier account achieves three valuable aims: First, it separates strong and weak indicators of the presence of consciousness. Second, these indicators include not only different specific contents but also differences in the way particular contents are processed (by processes of learning, reasoning or abstraction). Third, evidence of consciousness from each dimension can be combined to derive the distinctive multi-dimensional consciousness profile of various species. Thus, the two-tier account shows how the kind of conscious experience of different species can be systematically compared.

What are the main features that influence our attribution of moral responsibility? It is widely accepted that there are various factors which strongly influence our moral judgments, such as the agent’s intentions, the consequences of the action, the causal involvement of the agent, and the agent’s freedom and ability to do otherwise. In this paper, we argue that this picture is incomplete: We argue that social roles are an additional key factor that is radically underestimated in the extant literature. We will present an experiment to support this claim.

In recent years, theories of social understanding have moved away from arguing that just one epistemic strategy, such as theory-based inference or simulation constitutes our ability of social understanding. Empirical observations speak against any monistic view and have given rise to pluralistic accounts arguing that humans rely on a large variety of epistemic strategies in social understanding. We agree with this promising pluralist approach, but highlight two open questions: what is the residual role of mindreading, i.e. the indirect attribution of mental states to others within this framework, and how do different strategies of social understanding relate to each other? In a first step, we aim to clarify the arguments that might be considered in evaluating the role that epistemic strategies play in a pluralistic framework. On this basis, we argue that mindreading constitutes a core epiststrategy in human social life that opens new central spheres of social understanding. In a second step, we provide an account of the relation between different epistemic strategies which integrates and demarks the important role of mindreading for social understanding.

In recent years, theories of social understanding have moved away from arguing that just one epistemic strategy, such as theory-based inference or simulation constitutes our ability of social understanding. Empirical observations speak against any monistic view and have given rise to pluralistic accounts arguing that humans rely on a large variety of epistemic strategies in social understanding. We agree with this promising pluralist approach, but highlight two open questions: what is the residual role of mindreading, i.e. the indirect attribution of mental states to others within this framework, and how do different strategies of social understanding relate to each other? In a first step, we aim to clarify the arguments that might be considered in evaluating the role that epistemic strategies play in a pluralistic framework. On this basis, we argue that mindreading constitutes a core epiststrategy in human social life that opens new central spheres of social understanding. In a second step, we provide an account of the relation between different epistemic strategies which integrates and demarks the important role of mindreading for social understanding.

This paper presents arguments from empirical research and from philosophical considerations to the effect that phenomenality and content are two distinct and independent features of mental representations, which are both relational. Thus, it is argued, classical arguments that infer phenomenality from content have to be rejected. Likewise, theories that try to explain the phenomenal character of experiences by appeal to specific types of content cannot succeed. Instead, a dynamic view of consciousness has to be adopted that seeks to explain consciousness by certain ways of processing representations. Therefore, only empirical methods that are able to investigate the dynamics of the mind can be used for the “quest for consciousness” proper. Moreover, the central intuitions about consciousness are best explained when phenomenality and content are clearly distinguished.

Glenn Carruthers presents a very detailed and thorough critique of our multi-factorial twostep account of agency to the effect that it would not succeed in being superior and more general as the comparator model (CM). This critique gives us the opportunity to refine some of our points and to make the overall argument clearer. As Carruthers notes, “This move [the distinction between a feeling of agency (FoA) and a judgment of agency (JoA)] usefully limits the explanatory target of the CM to FoA”. This is exactly right in our view but contrasts with a lot of views present in the empirical literature which neglect this important difference. As a paradigmatic example see the claim by Jeannerod that “agency judgements made by the subject are based on the state of the comparator (Jeannerod, 1999, pp. 17-18) (for further experimental conflation of feeling and judgement of agency see e.g.Daprati et al., 1997; Farrer et al., 2003b). Thus, with this point we are not only fighting straw men but show severe limits of the explanatory force of the comparator model

There is an increasing amount of empirical work investigating the sense of agency, i.e. the registration that we are the initiators of our own actions. Many studies try to relate the sense of agency to an internal feed-forward mechanism, called the ‘‘comparator model’’. In this paper, we draw a sharp distinction between a non-conceptual level of feeling of agency and a conceptual level of judgement of agency. By analyzing recent empirical studies, we show that the comparator model is not able to explain either. Rather, we argue for a two-step account: a multifactorial weighting process of different agency indicators accounts for the feeling of agency, which is, in a second step, further processed by conceptual modules to form an attribution judgement. This new framework is then applied to disruptions of agency in schizophrenia, for which the comparator model also fails. Two further extensions are discussed: We show that the comparator model can neither be extended to account for the sense of ownership (which also has to be differentiated into a feeling and a judgement of ownership) nor for the sense of agency for thoughts. Our framework, however, is able to provide a unified account for the sense of agency for both actions and thoughts.