Jiji Zhang

Causal models consisting of structural equations have proved a powerful formalism for approaching theoretical and applied questions on causal reasoning. The standard framework assumes that all variables that appear in a causal model must represent properties or events that are metaphysically independent, with no dependencies more intimate than causal relations, such as conceptual, constitutive, or other ontological dependencies. However, there are important contexts that call for lifting this restriction, such as the debate over high-level causation in philosophy and the task of causal representation learning in artificial intelligence. This paper proposes a natural generalization of structural causal models to accommodate (asymmetric) ontological dependence and provides an interpretation of causal counterfactuals based on such models. We discuss several implications of this generalization and present an axiomatization of the resulting counterfactual logic.

Assuming that the future of human relations will depend critically on whether AI technologies that already mediate and shape personal and professional interactions will be made trustworthy, I examine an apparently daunting challenge to making predictive AI trustworthy, which is the widely observed trade-off between the accuracy and fairness of predictive AI models. I argue that the significance of this trade-off has been misconceived, and the standard rhetoric of balancing accuracy and fairness indicates a misguided route to trustworthy AI. I suggest an alternative way to think about the alleged trade-off and discuss the relevant implications of the reconceptualization, especially the need to have a clear understanding of the intended use of AI, which in turn requires AI users to reflect on their goals and values.

In “Flagpoles anyone? Causal and explanatory asymmetries”, James Woodward supplements his celebrated interventionist account of causation and explanation with a set of new ideas about causal and explanatory asymmetries, which he extracts from some cutting-edge methods for causal discovery from observational data. Among other things, Woodward draws interesting connections between observational causal discovery and interventionist themes that are inspired in the first place by experimental causal discovery, alluding to a sort of unity between observational and experimental causal discovery. In this paper, I make explicit what I take to be the implicated unity. Like experimental causal discovery, observational causal discovery also relies on interventions (or exogenous variations, to be more accurate), albeit interventions that are not carried out by investigators and hence need to be detected as part of the inference. The observational patterns appealed to in observational causal discovery are not only surrogates for would-be interventions, as Woodward sometimes puts it; they also serve to mark relevant interventions that actually happen in the data generating process.

An important component in the interventionist account of causal explanation is an interpretation of counterfactual conditionals as statements about consequences of hypothetical interventions. The interpretation receives a formal treatment in the framework of functional causal models. In Judea Pearl’s influential formulation, functional causal models are assumed to satisfy a “unique-solution” property; this class of Pearlian causal models includes the ones called recursive. Joseph Halpern showed that every recursive causal model is Lewisian, in the sense that there is a possible worlds model in David Lewis’s semantics for counterfactuals that satisfies the exact same formulas as the causal model does in a certain language. Moreover, he demonstrated that some Pearlian (non-recursive) models are not Lewisian in this sense. This raises the question about the exact contour of Lewisian causal models. We address this question in this paper, not only regarding the class of Lewisian causal models, but also regarding an important subclass, that of Stalnakerian causal models, which is closer to Pearlian models, and an important superclass of Lewisian causal models, which results from weakening a constraint imposed by Lewis known as centering, and is in a way more natural than the class of Lewisian causal models. For each of the three classes, we provide a characterization and an axiomatization. Our results have philosophically interesting consequences, especially regarding cycles of counterfactual dependence.

Several of the most prominent theories of actual causation make use of a minimality condition to prevent irrelevant elements from being tacked onto a cause so that the conjunction or sum passes for a cause. Focusing on one theory in particular—the influential Halpern-Pearl definition of actual causation—we argue that either the minimality condition or its rationale ought to be revised. We produce proposals showing that both are live options and demonstrate their potential usefulness within the larger family of counterfactual approaches to causation.

Stephen Yablo’s notion of proportionality, despite controversies surrounding it, has played a significant role in philosophical discussions of mental causation and of high-level causation more generally. In particular, it is invoked in James Woodward’s interventionist account of high-level causation and explanation, and is implicit in a novel approach to constructing variables for causal modeling in the machine learning literature, known as causal feature learning (CFL). In this article, we articulate an account of proportionality inspired by both Yablo’s account of proportionality and the CFL account of variable construction. The resulting account has at least three merits. First, it illuminates an important feature of the notion of proportionality, when it is adapted to a probabilistic and interventionist framework. The feature is that at the center of the notion of proportionality lies the concept of “determinate intervention effects.” Second, it makes manifest a virtue of (common types of) high-level causal/explanatory statements over low-level ones, when relevant intervention effects are determinate. Third, it overcomes a limitation of the CFL framework and thereby also addresses a challenge to interventionist accounts of high-level causation.

© 2015 The Authors.In the heart, augmented Ca 2+ fluxing drives contractility and ATP generation through mitochondrial Ca 2+ loading. Pathologic mitochondrial Ca 2+ overload with ischemic injury triggers mitochondrial permeability transition pore opening and cardiomyocyte death. Mitochondrial Ca 2+ uptake is primarily mediated by the mitochondrial Ca 2+ uniporter. Here, we generated mice with adult and cardiomyocyte-specific deletion of Mcu, which produced mitochondria refractory to acute Ca 2+ uptake, with impaired ATP production, and inhibited MPTP opening upon acute Ca 2+ challenge. Mice lacking Mcu inthe adult heart were also protected from acute ischemia-reperfusion injury. However, resting/basal mitochondrial Ca 2+ levels were normal in hearts of Mcu-deleted mice, and mitochondria lacking MCU eventually loaded with Ca 2+ after stress stimulation. Indeed, Mcu-deleted mice were unable to immediately sprint on a treadmill unless warmed up for 30min. Hence, MCU is a dedicated regulator of short-term mitochondrial Ca 2+ loading underlying a"fight-or-flight" response that acutely matches cardiac workload with ATP production.

Background: In vivo, non-invasive optical coherence tomography permits high-resolution imaging of tissue surfaces and subsurfaces, with the potential capability for detection and mapping of epithelial pathologies. Purpose: To evaluate the clinical capability of non-invasive in vivo OCT for diagnosing oral dysplasia and malignancy. Experimental Design: In 50 patients with oral lesions, conventional clinical examination was followed by OCT imaging, then standard biopsy and histopathology. Two blinded, pre-standardized investigators separately diagnosed each lesion based on OCT and histopathology. Results: Intra- and inter-observer agreement between diagnoses based on histopathology and imaging data was excellent, with λ values between 0.844 and 0.896. Sensitivity and specificity were also very good. Conclusions: These data demonstrate the excellent capability of in vivo OCT for detecting and diagnosing oral premalignancy and malignancy in human subjects. © 2009 Wiley-Liss, Inc.

Purpose: To assess noninvasive optical coherence tomography and optical Doppler tomography for early detection and evaluation of chemotherapy-induced oral mucositis. Experimental Design: Cheek pouches of 10 Syrian golden hamsters were imaged using OCT/ODT during development of chemotherapy-induced mucositis. I.p. injections of 5-fluorouracil and mechanical irritation induced oral lesions. At 2, 4, 7, and 11 days, one hamster was sacrificed and processed for histopathology. OCT images were visually examined; ODT results were semiquantified. Imaging data were compared with histologic findings. Results: During the development of mucositis, OCT/ODT identified the following events: change in epithelial thickness, loss of surface keratinized layer continuity, loss of epithelial and submucosal integrity, changes in axial blood flow velocity, and changes in blood vessel size. The semiquantitative imaging-based scoring system identified the severity of mucositis as defined by histopathology. The combination of imaging criteria used allowed for the detection of early, intermediate, and late mucositic changes. Imaging data gave higher scores compared with clinical scores early on, suggesting that the imaging-based diagnostic scoring was more sensitive to early mucositic change than the clinical scoring system. Once mucositis was established, imaging and clinical scores converged. Conclusion: OCT/ODT identified chemotherapy-induced oral changes before their clinical manifestation, and the proposed scoring system for oral mucositis was validated for the semiquantification of mucositic change. © 2007 American Association for Cancer Research.

Early detection of cancer and its precursors remains the best way to ensure patient survival and quality of life. Our specific aim is to test a multimodality approach to noninvasive diagnostics of oral premalignancy and malignancy. In the hamster cheek pouch model, in vivo optical coherence tomography and optical Doppler tomography map epithelial, subepithelial, and vascular change throughout carcinogenesis. In vivo multiwavelength multiphoton and second-harmonic generated fluorescence techniques provided parallel data on surface and subsurface tissue structure, specifically collagen presence and structure, cellular presence, and vasculature. Images are diagnosed by two blinded, prestandardized investigators using a scale from 0 to 6 for all modalities. After sacrifice, histopathology is evaluated on a scale of 0 to 6. Imaging data are reproducibly obtained with good accuracy. Carcinogenesis-related structural and vascular changes are clearly visible to tissue depths of 2 mm. Sensitivity and specificity compare well with conventional techniques. Our conclusions are that OCT/ODT and MPM/SHG are promising noninvasive in vivo diagnostic modalities for oral dysplasia and malignancy. © 2005 Society of Photo-Optical Instrumentation Engineers.