•  1277
    Causation: Empirical Trends and Future Directions
    with David Rose
    Philosophy Compass 7 (9): 643-653. 2012.
    Empirical research has recently emerged as a key method for understanding the nature of causation, and our concept of causation. One thread of research aims to test intuitions about the nature of causation in a variety of classic cases. These experiments have principally been used to try to resolve certain debates within analytic philosophy, most notably that between proponents of transference and dependence views of causation. The other major thread of empirical research on our concept of causa…Read more
  •  1277
    In Defense of a Broad Conception of Experimental Philosophy
    with David Rose
    Metaphilosophy 44 (4): 512-532. 2013.
    Experimental philosophy is often presented as a new movement that avoids many of the difficulties that face traditional philosophy. This article distinguishes two views of experimental philosophy: a narrow view in which philosophers conduct empirical investigations of intuitions, and a broad view which says that experimental philosophy is just the colocation in the same body of (i) philosophical naturalism and (ii) the actual practice of cognitive science. These two positions are rarely clearly …Read more
  •  1123
    Demoralizing causation
    Philosophical Studies (2): 1-27. 2013.
    There have recently been a number of strong claims that normative considerations, broadly construed, influence many philosophically important folk concepts and perhaps are even a constitutive component of various cognitive processes. Many such claims have been made about the influence of such factors on our folk notion of causation. In this paper, we argue that the strong claims found in the recent literature on causal cognition are overstated, as they are based on one narrow type of data about …Read more
  •  960
    In the latter half of the twentieth century, philosophers of science have argued (implicitly and explicitly) that epistemically rational individuals might compose epistemically irrational groups and that, conversely, epistemically rational groups might be composed of epistemically irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they together imply that methodological prescriptions for scientific communities and those for individual scientists might…Read more
  •  719
    Wisdom of the Crowds vs. Groupthink: Learning in Groups and in Isolation
    with Conor Mayo-Wilson and Kevin Zollman
    International Journal of Game Theory 42 (3): 695-723. 2013.
    We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, commo…Read more
  •  601
    Diversity in Representations; Uniformity in Learning
    with David Rose
    Behavioral and Brain Sciences 33 (2-3): 330-331. 2010.
    Henrich et al.'s conclusion that psychologists ought not assume uniformity of psychological phenomena depends on their descriptive claim that there is no pattern to the great diversity in psychological phenomena. We argue that there is a pattern: uniformity of learning processes (broadly construed), and diversity of (some) mental contents (broadly construed)
  •  263
    Algorithmic bias: Senses, sources, solutions
    Philosophy Compass 16 (8). 2021.
    Data‐driven algorithms are widely used to make or assist decisions in sensitive domains, including healthcare, social services, education, hiring, and criminal justice. In various cases, such algorithms have preserved or even exacerbated biases against vulnerable communities, sparking a vibrant field of research focused on so‐called algorithmic biases. This research includes work on identification, diagnosis, and response to biases in algorithm‐based decision‐making. This paper aims to facilitat…Read more
  •  199
    We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) "neuron" and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial…Read more
  •  195
    Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue that their purported confirmation largely relies on a methodology that depends on premises that are inconsistent with the claim that people are Bayesian about learning and inference. Bayesian models in cognitive science derive their appeal from their normative claim that the modeled inference is in some sense rational. Standard accounts of the rationality of Bayesian inference imply predictions tha…Read more
  •  164
    Scientific coherence and the fusion of experimental results
    British Journal for the Philosophy of Science 56 (4): 791-807. 2005.
    A pervasive feature of the sciences, particularly the applied sciences, is an experimental focus on a few (often only one) possible causal connections. At the same time, scientists often advance and apply relatively broad models that incorporate many different causal mechanisms. We are naturally led to ask whether there are normative rules for integrating multiple local experimental conclusions into models covering many additional variables. In this paper, we provide a positive answer to this qu…Read more
  •  152
    Reasons as Causes in Bayesian Epistemology
    Journal of Philosophy 104 (9): 464-474. 2007.
    In everyday matters, as well as in law, we allow that someone’s reasons can be causes of her actions, and often are. That correct reasoning accords with Bayesian principles is now so widely held in philosophy, psychology, computer science and elsewhere that the contrary is beginning to seem obtuse, or at best quaint. And that rational agents should learn about the world from energies striking sensory inputs nerves in people—seems beyond question. Even rats seem to recognize the difference betwee…Read more
  •  146
    Explaining norms and norms explained
    Behavioral and Brain Sciences 32 (1): 86-87. 2009.
    Oaksford & Chater (O&C) aim to provide teleological explanations of behavior by giving an appropriate normative standard: Bayesian inference. We argue that there is no uncontroversial independent justification for the normativity of Bayesian inference, and that O&C fail to satisfy a necessary condition for teleological explanations: demonstration that the normative prescription played a causal role in the behavior's existence
  •  125
    A Theory of Causal Learning in Children: Causal Maps and Bayes Nets
    with Alison Gopnik, Clark Glymour, Laura Schulz, and Tamar Kushnir
    Psychological Review 111 (1): 3-32. 2004.
    We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimen…Read more
  •  121
    Normative moral theories are frequently invoked to serve one of two distinct purposes: (1) explicate a criterion of rightness, or (2) provide an ethical decision-making procedure. Although a criterion of rightness provides a valuable theoretical ideal, proposed criteria rarely can be (nor are they intended to be) directly translated into a feasible decision-making procedure. This paper applies the computational framework of bounded rationality to moral decision-making to ask: how ought a bounded…Read more
  •  102
    Causal discovery algorithms: A practical guide
    Philosophy Compass 13 (1). 2018.
    Many investigations into the world, including philosophical ones, aim to discover causal knowledge, and many experimental methods have been developed to assist in causal discovery. More recently, algorithms have emerged that can also learn causal structure from purely or mostly observational data, as well as experimental data. These methods have started to be applied in various philosophical contexts, such as debates about our concepts of free will and determinism. This paper provides a “user's …Read more
  •  86
    Goal-dependence in ontology
    Synthese 192 (11): 3601-3616. 2015.
    Our best sciences are frequently held to be one way, perhaps the optimal way, to learn about the world’s higher-level ontology and structure. I first argue that which scientific theory is “best” depends in part on our goals or purposes. As a result, it is theoretically possible to have two scientific theories of the same domain, where each theory is best for some goal, but where the two theories posit incompatible ontologies. That is, it is possible for us to have goal-dependent pluralism in our…Read more
  •  80
    ABSTRACTAutonomous weapons systems pose many challenges in complex battlefield environments. Previous discussions of them have largely focused on technological or policy issues. In contrast, we focus here on the challenge of trust in an AWS. One type of human trust depends only on judgments about the predictability or reliability of the trustee, and so are suitable for all manner of artifacts. However, AWSs that are worthy of the descriptor “autonomous” will not exhibit the required strong predi…Read more
  •  79
    Erratum to: Synthese DOI 10.1007/s11229-014-0408-3Appendix 1: NotationLet \(X\) represent a sequence of data, and let \(X_B^t\) represent an i.i.d. subsequence of length \(t\) of data generated from distribution \(B\).We conjecture that the i.i.d. assumption could be eliminated by defining probability distributions over sequences of arbitrary length, though this complication would not add conceptual clarity. Let \(\mathbf{F}\) be a framework (in this case, a set of probability distributions or d…Read more
  •  74
    It is “well known” that in linear models: (1) testable constraints on the marginal distribution of observed variables distinguish certain cases in which an unobserved cause jointly influences several observed variables; (2) the technique of “instrumental variables” sometimes permits an estimation of the influence of one variable on another even when the association between the variables may be confounded by unobserved common causes; (3) the association (or conditional probability distribution of…Read more
  •  71
    Environmental Epistemology
    Synthese 203 (81): 1-24. 2024.
    We argue that there is a large class of questions—specifically questions about how to epistemically evaluate environments that currently available epistemic theories are not well-suited for answering, precisely because these questions are not about the epistemic state of particular agents or groups. For example, if we critique Facebook for being conducive to the spread of misinformation, then we are not thereby critiquing Facebook for being irrational, or lacking knowledge, or failing to testify…Read more
  •  70
    Biological codes and topological causation
    Philosophy of Science 75 (3): 259-277. 2008.
    Various causal details of the genetic process of translation have been singled out to account for its privileged status as a ‘code'. We explicate the biological uses of coding talk by characterizing a class of special causal processes in which topological properties are the causally relevant ones. This class contains both the process of translation and communication theoretic coding processes as special cases. We propose a formalism in terms of graphs for expressing our theory of biological code…Read more
  •  66
    A Modern Pascal's Wager for Mass Electronic Surveillance
    Télos 2014 (169): 155-161. 2014.
    Debates about the moral permissibility of mass electronic surveillance often turn on whether consequentialist considerations legitimately trump relevant deontological rights and principles. In order to establish such overriding consequences, many proponents of mass surveillance employ a modern analogue of Pascal’s wager: they contend that the consequences of no surveillance are so severe that any probability of such outcomes legitimates the abrogation of the relevant rights. In this paper, I bri…Read more
  •  62
    Algorithmic Fairness and the Situated Dynamics of Justice
    Canadian Journal of Philosophy 52 (1): 44-60. 2022.
    Machine learning algorithms are increasingly used to shape high-stake allocations, sparking research efforts to orient algorithm design towards ideals of justice and fairness. In this research on algorithmic fairness, normative theorizing has primarily focused on identification of “ideally fair” target states. In this paper, we argue that this preoccupation with target states in abstraction from the situated dynamics of deployment is misguided. We propose a framework that takes dynamic trajector…Read more
  •  62
    Our concept of actual causation plays a deep, ever-present role in our experiences. I first argue that traditional philosophical methods for understanding this concept are unlikely to be successful. I contend that we should instead use functional analyses and an understanding of the cognitive bases of causal cognition to gain insight into the concept of actual causation. I additionally provide initial, programmatic steps towards carrying out such analyses. The characterization of the concept of …Read more
  •  55
    Teaching the normative theory of causal reasoning
    with Richard Scheines and Matt Easterday
    In Alison Gopnik & Laura Schulz (eds.), Causal Learning: Psychology, Philosophy, and Computation, Oxford University Press. pp. 119--38. 2007.
    There is now substantial agreement about the representational component of a normative theory of causal reasoning: Causal Bayes Nets. There is less agreement about a normative theory of causal discovery from data, either computationally or cognitively, and almost no work investigating how teaching the Causal Bayes Nets representational apparatus might help individuals faced with a causal learning task. Psychologists working to describe how naïve participants represent and learn causal structure …Read more
  •  51
    Newsome ((2003). The debate between current versions of covariation and mechanism approaches to causal inference. Philosophical Psychology, 16, 87-107.) recently published a critical review of psychological theories of human causal inference. In that review, he characterized covariation and mechanism theories, the two dominant theory types, as competing, and offered possible ways to integrate them. I argue that Newsome has misunderstood the theoretical landscape, and that covariation and mechani…Read more
  •  49
    Model change and reliability in scientific inference
    Synthese 191 (12): 2673-2693. 2014.
    One persistent challenge in scientific practice is that the structure of the world can be unstable: changes in the broader context can alter which model of a phenomenon is preferred, all without any overt signal. Scientific discovery becomes much harder when we have a moving target, and the resulting incorrect understandings of relationships in the world can have significant real-world and practical consequences. In this paper, we argue that it is common (in certain sciences) to have changes of …Read more
  •  42
    In many people, caffeine causes slight muscle tremors, particularly in their hands. In general, the Caffeine → Muscle Tremors causal connection is a noisy one: someone can drink coffee and experience no hand shaking, and there are many other factors that can lead to muscle tremors. Now suppose that Jane drinks several cups of coffee and then notices that her hands are trembling; an obvious question is: did this instance of coffee drinking cause this instance of hand-trembling? Structurally simil…Read more
  •  39
    Mixtures and Psychological Inference with Resting State fMRI
    British Journal for the Philosophy of Science 73 (3): 583-611. 2022.
    In this essay, we examine the use of resting state fMRI data for psychological inferences. We argue that resting state studies hold the paired promises of discovering novel functional brain networks, and of avoiding some of the limitations of task-based fMRI. However, we argue that the very features of experimental design that enable resting state fMRI to support exploratory science also generate a novel confound. We argue that seemingly key features of resting state functional connectivity netw…Read more