Machine art or machine artists? Dennett, Danto, and the expressive stance

As art produced by autonomous machines becomes increasingly common, and as such machines grow increasingly sophisticated, we risk a confusion between art produced by a person but mediated by a machine, and art produced by what might be legitimately considered a machine artist. This distinction will be examined here. In particular, my argument seeks to close a gap between, on one hand, a philosophically grounded theory of art and, on the other hand, theories concerned with behavior, intentionality, expression, and creativity in natural and artificial agents. This latter set of theories in some cases addresses creative behavior in relation to visual art, music, and literature, in the frequently overlapping contexts of philosophy of mind, artificial intelligence, and cognitive science. However, research in these areas does not typically address problems in the philosophy of art as a central line of inquiry. Similarly, the philosophy of art does not typically address issues pertaining to artificial agents

Unnecessary constraints: a challenge to some assumptions of digital musical instrument design

The enormous range of possibilities for digital musical instrument (DMI) design is often limited by the adoption of unnecessary conceptual constraints. When considered in relation to DMIs, a careful analysis of the underlying concepts makes it possible to reject certain assumptions and thereby to expand the current range of acceptable possibilities for future designs

Investigating the cognitive foundations of collaborative musical free improvisation: Experimental case studies using a novel application of the subsumption architecture

This thesis investigates the cognitive foundations of collaborative musical free improvisation. To explore the cognitive underpinnings of the collaborative process, a series of experimental case studies was undertaken in which expert improvisors performed with an artificial agent. The research connects ecological musicology and subsumption robotics, and builds upon insights from empirical psychology pertaining to the attribution of intentionality. A distinguishing characteristic of free improvisation is that no over-arching framework of formal musical conventions defines it, and it cannot be positively identified by sound alone, which poses difficulties for traditional musicology. Current musicological research has begun to focus on the social dimension of music, including improvisation. Ecological psychology, which focuses on the relation of cognition to agent–environment dynamics using the notion of affordances, has been shown to be a promising approach to understanding musical improvisation. This ecological approach to musicology makes it possible to address the subjective and social aspects of improvised music, as opposed to the common treatment of music as objective and neutral. The subjective dimension of musical listening has been highlighted in music cognition studies of cue abstraction, whereby listeners perceive emergent structures while listening to certain forms of music when no structures are identified in advance. These considerations informed the design of the artificial agent, Odessa, used for this study. In contrast to traditional artificial intelligence (AI), which tends to view the world as objective and neutral, behaviour-based robotics historically developed around ideas similar to those of ecological psychology, focused on agent–environment dynamics and the ability to deal with potentially rapidly changing environments. Behaviour-based systems that are designed using the subsumption architecture are robust and flexible in virtue of their modular, decentralised design comprised of simple interactions between simple mechanisms. The competence of such agents is demonstrated on the basis of their interaction with the environment and ability to cope with unknown and dynamic conditions, which suggests the concept of improvisation. This thesis documents a parsimonious subsumption design for an agent that performs musical free improvisation with human co-performers, as well as the experimental studies conducted with this agent. The empirical component examines the human experience of collaborating with the agent and, more generally, the cognitive psychology of collaborative improvisation. The design was ultimately successful, and yielded insights about cognition in collaborative improvisation, in particular, concerning the central relationship between perceived intentionality and affordances. As a novel application of the subsumption architecture, this research contributes to AI/robotics and to research on interactive improvisation systems. It also contributes to music psychology and cognition, as well as improvisation studies, through its empirical grounding of an ecological model of musical interaction

Interactive intelligence: behaviour-based AI, musical HCI and the Turing Test

The field of behaviour-based artificial intelligence (AI), with its roots in the robotics research of Rodney Brooks, is not predominantly tied to linguistic interaction in the sense of the classic Turing test (or, "imitation game"). Yet, it is worth noting, both are centred on a behavioural model of intelligence. Similarly, there is no intrinsic connection between musical AI and the language-based Turing test, though there have been many attempts to forge connections between them. Nonetheless, there are aspects of musical AI and the Turing test that can be considered in the context of non-language-based interactive environments–-in particular, when dealing with real-time musical AI, especially interactive improvisation software. This paper draws out the threads of intentional agency and human indistinguishability from Turing’s original 1950 characterisation of AI. On the basis of this distinction, it considers different approaches to musical AI. In doing so, it highlights possibilities for non-hierarchical interplay between human and computer agents

Reframing PTSD for computational psychiatry with the active inference framework

Introduction: Recent advances in research on stress and, respectively, on disorders of perception, learning, and behaviour speak to a promising synthesis of current insights from (i) neurobiology, cognitive neuroscience and psychology of stress and post-traumatic stress disorder (PTSD), and (ii) computational psychiatry approaches to pathophysiology (e.g. of schizophrenia and autism). Methods: Specifically, we apply this synthesis to PTSD. The framework of active inference offers an embodied and embedded lens through which to understand neuronal mechanisms, structures, and processes of cognitive function and dysfunction. In turn, this offers an explanatory model of how healthy mental functioning can go awry due to psychopathological conditions that impair inference about our environment and our bodies. In this context, auditory phenomena - known to be especially relevant to studies of PTSD and schizophrenia - and traditional models of auditory function can be viewed from an evolutionary perspective based on active inference. Results: We assess and contextualise a range of evidence on audition, stress, psychosis, and PTSD, and bring some existing partial models of PTSD into multilevel alignment. Conclusions: The novel perspective on PTSD we present aims to serve as a basis for new experimental designs and therapeutic interventions that integrate fundamentally biological, cognitive, behavioural, and environmental factors

Active inference, stressors, and psychological trauma: A neuroethological model of (mal)adaptive explore-exploit dynamics in ecological context

This paper offers a formal account of emotional inference and stress-related behaviour, using the notion of active inference. We formulate responses to stressful scenarios in terms of Bayesian belief-updating and subsequent policy selection; namely, planning as (active) inference. Using a minimal model of how creatures or subjects account for their sensations (and subsequent action), we deconstruct the sequences of belief updating and behaviour that underwrite stress-related responses – and simulate the aberrant responses of the sort seen in post-traumatic stress disorder (PTSD). Crucially, the model used for belief-updating generates predictions in multiple (exteroceptive, proprioceptive and interoceptive) modalities, to provide an integrated account of evidence accumulation and multimodal integration that has consequences for both motor and autonomic responses. The ensuing phenomenology speaks to many constructs in the ecological and clinical literature on stress, which we unpack with reference to simulated inference processes and accompanying neuronal responses. A key insight afforded by this formal approach rests on the trade-off between the epistemic affordance of certain cues (that resolve uncertainty about states of affairs in the environment) and the consequences of epistemic foraging (that may be in conflict with the instrumental or pragmatic value of ‘fleeing’ or ‘freezing’). Starting from first principles, we show how this trade-off is nuanced by prior (subpersonal) beliefs about the outcomes of behaviour – beliefs that, when held with unduly high precision, can lead to (Bayes optimal) responses that closely resemble PTSD

Zoocentrism in the weeds? Cultivating plant models for cognitive yield

It remains at best controversial to claim, non-figuratively, that plants are cognitive agents. At the same time, it is taken as trivially true that many (if not all) animals are cognitive agents, arguably through an implicit or explicit appeal to natural science. Yet, any given definition of cognition implicates at least some further processes, such as perception, action, memory, and learning, which must be observed either behaviorally, psychologically, neuronally, or otherwise physiologically. Crucially, however, for such observations to be intelligible, they must be counted as evidence for some model. These models in turn point to homologies of physiology and behavior that facilitate the attribution of cognition to some non-human animals. But, if one is dealing with a model of animal cognition, it is tautological that only animals can provide evidence, and absurd to claim that plants can. The more substantive claim that, given a general model of cognition, only animals but not plants can provide evidence, must be evaluated on its merits. As evidence mounts that plants meet established criteria of cognition, from physiology to behavior, they continue to be denied entry into the cognitive club. We trace this exclusionary tendency back to Aristotle, and attempt to counter it by drawing on the philosophy of modelling and a range of findings from plant science. Our argument illustrates how a difference in degree between plant and animals is typically mistaken for a difference in kind

On plants and principles

A critical oversight in the authors’ (Birch et al.) UAL framework arises in its stated basis in an “unlimited heredity” (UH) argument. Specifically, the foundational UH claim is that there is a possibility space constrained by the known properties of DNA, and that, within that space, a subset of specific “real” lineages arise. These lineages are actualisations of possibilities, under the assumption that no amount of time would be sufficient to actualise all possibilities. The oversight – already present in UH, but ‘inherited’ by UAL – regards what pressures produce the actual subset of lineages from the in principle possible lineages. Significantly, the subset is neither due solely to the “constraints” granted by Birch et al., nor is it arbitrary. Rather, the subset of actual lineages is the result of a reciprocal process with the environment that has been highlighted in research on the Extended Evolutionary Synthesis (EES) (e.g. Laland et al. 2017). In this commentary, we will underscore how this critical oversight concerning reciprocal pressures poses a core problem for the target article’s characterisation of UAL

The expressive stance: intentionality, expression, and machine art

This paper proposes a new interpretive stance for interpreting artistic works and performances that is relevant to artificial intelligence research but also has broader implications. Termed the expressive stance, this stance makes intelligible a critical distinction between present-day machine art and human art, but allows for the possibility that future machine art could find a place alongside our own. The expressive stance is elaborated as a response to Daniel Dennett's notion of the intentional stance, which is critically examined with respect to his specialized concept of rationality. The paper also shows that temporal scale implicitly serves to select between different modes of explanation in prominent theories of intentionality. It also considers the implications of the phenomenological background for systems that produce art

A Subsumption Agent for Collaborative Free Improvisation

This paper discusses the design and evaluation of an artificial agent for collaborative musical free improvisation. The agent provides a means to investigate the underpinnings of improvisational interaction. In connection with this general goal, the system is also used here to explore the implementation of a collaborative musical agent using a specific robotics architecture, Subsumption. The architecture of the system is explained, and its evaluation in an empirical study with expert improvisors is discussed. A follow-up study using a second iteration of the system is also presented. The system design and connected studies bring together Subsumption robotics, ecological psychology, and musical improvisation, and contribute to an empirical grounding of an ecological theory of improvisation