Kevin Mitchell

While the free will debate tends to focus primarily on the implications of determinism for freedom, a long line of philosophers have also argued that free will would not be compatible with indeterminism either. These arguments typically take the form of a so-called Luck Objection: a family of related arguments which all seek to show, roughly, that if an action is not causally pre-determined then it must be a sort of random happening, over which the agent lacks the control required for free will. If successful, these arguments are fatal for libertarian accounts of free will, which are committed to the view that free actions must be both undetermined and under the agent’s control. In this paper, we defend libertarian free will against this challenge from luck. We argue that most formulations of the Luck Objection presuppose a conceptual model of indeterministic decision-making that is not well aligned with recent advances in the natural sciences; specifically, we argue that they make assumptions about the nature of indeterminacy and about the causal structure of decision-making, which libertarians have good empirical reason (from both physics and neuroscience) to reject. We develop a more empirically plausible model of agential decision-making and apply this to the problem of luck. We argue that, under such a model, it is entirely natural to think of an agent’s actions as both ‘undetermined’ (in the sense of being under-determined) and under their own control. We conclude that indeterminism poses no threat to a more naturalistic version of libertarian free will.

The concept of representations is widely used across the cognitive sciences, but its meaning is highly contested. Representations are often thought of as “vehicles” with “content” – that is, internal physical patterns that are correlated with some state of affairs and that usefully convey that state of affairs to the rest of the neural system or the cognitive economy at large. This raises a number of problems: how does an internal pattern come to be correlated with something else? How does the rest of the system know what the pattern means? How does the system know what to do with that information? I suggest that thinking of representations as vehicles with content presents a stumbling block to answering these questions. Instead, thinking of them simply as meaningful patterns offers a more naturalistic framework for understanding their roles in perception, behavioural control, and cognition. Meaning is not contained within a vehicle – it is relational, contextual, and interpretive. Here, I explore the origins of meaningful patterns in simple behavioural control policies and the subsequent evolution of internalised representations, decoupled from obligate action. This transition from pragmatic to semantic meaning demystifies the notion of “content”, situates talk of grounding in referential, consequential, and relational terms, and highlights the dual roles of current activity and stored context.

The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.

In neuroscience, the search for the causes of behaviour is often just taken to be the search for neural mechanisms. This view typically involves three forms of causal reduction: first, from the ontological level of cognitive processes to that of neural mechanisms; second, from the activity of the whole brain to that of isolated parts; and third, from a consideration of temporally extended, historical processes to a focus on synchronic states. While modern neuroscience has made impressive progress in identifying synchronic neural mechanisms, providing unprecedented real-time control of behaviour, we contend that this does not amount to a full causal explanation. In particular, there is an attendant danger of eliminating the cognitive from our explanatory framework, and even eliminating the organism itself. To fully understand the causes of behaviour, we need to understand not just what happens when different neurons are activated, but why those things happen. In this paper, we introduce a range of well-developed, non-reductive, and temporally extended notions of causality from philosophy, which neuroscientists may be able to draw on in order to build more complete causal explanations of behaviour. These include concepts of criterial causation, triggering versus structuring causes, constraints, macroscopic causation, historicity, and semantic causation—all of which, we argue, can be used to undergird a naturalistic understanding of mental causation and agent causation. These concepts can, collectively, help bring cognition and the organism itself back into the picture, as a causal agent unto itself, while still grounding causation in respectable scientific terms.

Free will discourse is primarily centred around the thesis of determinism. Much of the literature takes determinism as its starting premise, assuming it true “for the sake of discussion”, and then proceeds to present arguments for why, if determinism is true, free will would be either possible or impossible. This is reflected in the theoretical terrain of the debate, with the primary distinction currently being between compatibilists and incompatibilists and not, as one might expect, between free will realists and skeptics. The aim of this paper is twofold. First, we argue that there is no reason to accept such a framing. We show that, on the basis of modern physics, there is no good evidence that physical determinism (of any variety) provides an accurate description of our universe and lots of evidence against such a view. Moreover, we show that this analysis extends equally to the sort of ‘indeterministic’ worldviews endorsed by many libertarian philosophers (and their skeptics) – a worldview which we refer to as determinism-plus-randomness. The paper’s secondary aim is therefore to present an alternative conception of indeterminism, which is more in line with the empirical evidence from physics. It is this indeterministic worldview, we suggest, that ought to be the central focus of a reframed philosophy of free will.

Traditional models of synaesthesia seek to explain the experience of additional percepts or associations in response to inducing stimuli by proposing either excess connections between cortical areas or disinhibition of existing circuits. These models ignore an essential property of synaesthesia, however, namely that it is developmental. To get a full understanding of the nature of synaesthesia it is important to consider not only static endpoints, but also the developmental processes that have led to them. Here, I examine synaesthesia from a neurodevelopmental perspective, present evidence that it involves widespread differences in connectivity and consider this in light of the dynamic processes that shape cortical specialisation and connectivity over development.