I extend work from Krakauer et al. (2020), who propose a conception of individuality as the capacity to propagate information through time. From this conception, they develop information-theoretic measures. I identify several shortcomings with these measures—in particular, that they are associative rather than causal. I rectify this shortcoming by deriving a causal information-theoretic measure of individuality. I then illustrate how this measure can be implemented and extended in the context of evolutionary transitions in individuality.

The recent literature on causality has seen the introduction of several distinctions within causality, which are thought to be important for understanding the widespread scientific practice of focusing causal explanations on a subset of the factors that are causally relevant for a phenomenon. Concepts used to draw such distinctions include, among others, stability, specificity, proportionality, or actual-difference making. In this contribution, I propose a new distinction that picks out an explanatorily salient class of causes in biological systems. Some select causes (...) in complex biological systems, I argue, have the property of enabling coherent causal control of these systems. Examples of such control variables include hormones and other signaling molecules, e.g., TOR (target of rapamycin), morphogens or the products of homeotic selector genes in embryonic pattern formation. I propose an analysis of this notion based on concepts borrowed from causal graph theory. (shrink)

Binding specificity is a centrally important concept in molecular biology, yet it has received little philosophical attention. Here I aim to remedy this by analyzing binding specificity as a causal property. I focus on the concept’s role in drug design, where it is highly prized and hence directly studied. From a causal perspective, understanding why binding specificity is a valuable property of drugs contributes to an understanding of causal selection—of how and why scientists distinguish between causes, not just causes from (...) noncauses. In particular, the specificity of drugs is precisely what underwrites their value as experimental interventions on biological processes. (shrink)

The idea that good explanations come with strong changes in probabilities has been very common. This criterion is called probabilistic difference-making. Since it is an intuitive criterion and has a long tradition in the literature on scientific explanation, it comes as a surprise that probabilistic difference-making is rarely discussed in the context of interventionist causal explanation. Specificity, proportionality, and stability are usually employed to measure explanatory power instead. This paper is a first step into the larger project of connecting difference-making (...) to the interventionist debate, and it starts by investigating whether probabilistic difference-making is contained in the notion of specificity. The choice of specificity is motivated by the observation that both probabilistic difference-making and specificity build on similar underlying intuitions. When comparing measures for both specificity and probabilistic difference-making, it turns out that the measures are not strictly correlated, and so the thesis that probabilistic difference-making is encoded within specificity has to be rejected. Some consequences of this result are discussed as well. (shrink)

Goldman (1967) proposed that a subject s knows p if and only if p is appropriately causally connected to s’s believing p. He later on abandoned this theory (Goldman, 1976). The main objection to the theory is that the causal connection required by Goldman is compatible with certain problematic forms of luck. In this paper we argue that Goldman’s causal theory of knowledge can overcome the luck problem if causation is understood along interventionist lines. We also show that the modified (...) theory leads to the correct results in contexts involving other prominent forms of epistemic luck and compare it with other accounts on the market. (shrink)

Supporters of the autonomy of higher-level causation (or explanation) often appeal to proportionality, arguing that higher-level causes are more proportional than their lower-level realizers. Recently, measures based on information theory and causal modeling have been proposed that allow one to shed new light on proportionality and the related notion of specificity. In this paper we apply ideas from this literature to the issue of higher vs. lower-level causation (and explanation). Surprisingly, proportionality turns out to be irrelevant for the question of (...) whether higher-level causes (or explanations) can be autonomous; specificity is a much more informative notion for this purpose. (shrink)

The concept of causal specificity is drawing considerable attention from philosophers of biology. It became the rationale for rejecting (and occasionally, accepting) a thesis of causal parity of developmental factors. This literature assumes that attributing specificity to causal relations is at least in principle a straightforward (if not systematic) task. However, the parity debate in philosophy of biology seems to be stuck at a point where it is not the biological details that will help move forward. In this paper, I (...) take a step back to reexamine the very idea of causal specificity and its intended role in the parity dispute in philosophy of biology. I contend that the idea of causal specificity across variations as currently discussed in the literature is irreducibly twofold in nature: it is about two independent components that are not mutually entailed. I show this to be the source of prior complications with the notion of specificity itself that ultimately affect the purposes for which it is often invoked, notably to settle the parity dispute. (shrink)

I respond to recent criticism of my analysis of the permissive-instructive distinction and outline problems with the alternative analysis on offer. Amongst other problems, I argue that the use of formal measures is unclear and unmotivated, that the distinction is conflated with others that are not equivalent, and that no good reasons are provided for thinking the alternative model or formal measure tracks what biologists are interested in. I also clarify my own analysis where it has been misunderstood or ignored.

I respond to recent criticism of my analysis of the permissive-instructive distinction and outline problems with the alternative analysis on offer. Amongst other problems, I argue that the use of formal measures is unclear and unmotivated, that the distinction is conflated with others that are not equivalent, and that no good reasons are provided for thinking the alternative model or formal measure tracks what biologists are interested in. I also clarify my own analysis where it has been misunderstood or ignored.

I argue that Calcott :481–505, Calcott 2017) mischaracterizes in an important way the notion of causal specificity proposed by Woodward :287–318, Woodward 2010). This leads him to rely too heavily on one single aspect of Woodward’s analysis on causal specificity; propose an information-theoretic measure he calls ‘precision’ which is partly redundant with, but less general than one of the dimensions in Woodward’s analysis of specificity, without acknowledging Woodward’s analysis; and claim that comparing the specificities of two or more causes under (...) what he calls a competitive analysis of causes, does not permit to capture the distinction between permissive and instructive causes. After having restated Woodward’s analysis of causal specificity, I present an information-theoretic measure which, although related to Calcott’s measure, is more general than his and corresponds to the notion of specificity he missed in Woodward's analysis. I then show how this measure can be used, together with mutual causal information, to distinguish permissive from instructive causes in a competitive analysis of causes. (shrink)

Heritability is routinely interpreted causally. Yet, what such an interpretation amounts to is often unclear. Here, I provide a causal interpretation of this concept in terms of range of causal influence, one of several causal dimensions proposed within the interventionist account of causation. An information-theoretic measure of range of causal influence has recently been put forward in the literature. Starting from this formalization and relying upon Woodward’s analysis, I show that an important problem associated with interpreting heritability causally, namely the (...) locality problem, amounts, at least partly, to a low invariance and low stability between the genotype/environment and the phenotype of individuals. In light of this, I plead for a causal interpretation of heritability that takes the notions of Woodward’s invariance and stability into consideration. In doing so, I defuse naive causal interpretations of heritability. (shrink)

Genome-wide association studies of human complex traits have provided us with new estimates of heritability. These estimates foreground the question of genetic causation. After having presen...

Following from my criticisms of Calcott’s analysis on the permissive/instructive distinction, I rebut his claims that 1) he clarifies my measure one-to-one specificity; 2) for all intents and purposes of his analysis his notion of precision is different from my measure of one- to-one specificity; 3) Waddington box is a better and different model than the extension of Woodward’s radio I propose.

Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how (...) invariance could be qualified for such variables. (shrink)