von Neumann-Morgenstern and Savage Theorems for Causal Decision Making

Causal thinking and decision making under uncertainty are fundamental aspects of intelligent reasoning. Decision making under uncertainty has been well studied when information is considered at the associative (probabilistic) level. The classical Theorems of von Neumann-Morgenstern and Savage provide a formal criterion for rational choice using purely associative information. Causal inference often yields uncertainty about the exact causal structure, so we consider what kinds of decisions are possible in those conditions. In this work, we consider decision problems in which available actions and consequences are causally connected. After recalling a previous causal decision making result, which relies on a known causal model, we consider the case in which the causal mechanism that controls some environment is unknown to a rational decision maker. In this setting we state and prove a causal version of Savage's Theorem, which we then use to develop a notion of causal games with its respective causal Nash equilibrium. These results highlight the importance of causal models in decision making and the variety of potential applications.Comment: Submitted to Journal of Causal Inferenc

Temporal and causal reasoning in deaf and hearing novice readers

Temporal and causal information in text are crucial in helping the reader form a coherent representation of a narrative. Deaf novice readers are generally poor at processing linguistic markers of causal/temporal information (i.e., connectives), but what is unclear is whether this is indicative of a more general deficit in reasoning about temporal/causal information. In Study 1, 10 deaf and 63 hearing children, matched for comprehension ability and age, were compared on a range of tasks tapping temporal/causal reasoning skills. In Study 2, 20 deaf and 32 hearing children, matched for age but not reading comprehension ability, were compared on revised versions of the tasks. The pattern of performance of the deaf was different from that of the hearing; they had difficulties when temporal and causal reasoning was text-based, but not when it was nonverbal, indicating that their global temporal/causal reasoning skills are comparable with those of their hearing counterparts

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Causal Interfaces

The interaction of two binary variables, assumed to be empirical observations, has three degrees of freedom when expressed as a matrix of frequencies. Usually, the size of causal influence of one variable on the other is calculated as a single value, as increase in recovery rate for a medical treatment, for example. We examine what is lost in this simplification, and propose using two interface constants to represent positive and negative implications separately. Given certain assumptions about non-causal outcomes, the set of resulting epistemologies is a continuum. We derive a variety of particular measures and contrast them with the one-dimensional index.Comment: 20 pages, 3 figure

Causes that Make a Difference

Biologists studying complex causal systems typically identify some factors as causes and treat other factors as background conditions. For example, when geneticists explain biological phenomena, they often foreground genes and relegate the cellular milieu to the background. But factors in the milieu are as causally necessary as genes for the production of phenotypic traits, even traits at the molecular level such as amino acid sequences. Gene-centered biology has been criticized on the grounds that because there is parity among causes, the “privileging” of genes reflects a reductionist bias, not an ontological difference. The idea that there is an ontological parity among causes is related to a philosophical puzzle identified by John Stuart Mill: what, other than our interests or biases, could possibly justify identifying some causes as the actual or operative ones, and other causes as mere background? The aim of this paper is to solve this conceptual puzzle and to explain why there is not an ontological parity among genes and the other factors. It turns out that solving this puzzle helps answer a seemingly unrelated philosophical question: what kind of causal generality matters in biology

Necessitarianism and Dispositions

In this paper, I argue in favor of necessitarianism, the view that dispositions, when stimulated, necessitate their manifestations. After introducing and clarifying what necessitarianism does and does not amount to, I provide reasons to support the view that dispositions once stimulated necessitate their manifestations according to the stimulating conditions and the relevant properties at stake. In this framework, I will propose a principle of causal relevance and some conditions for the possibility of interference that allow us to avoid the use of ceteris paribus clauses. I then defend necessitarianism from recent attacks raised by, among others, Mumford and Anjum, noting that the antecedent strengthening test is a test for causal relevance that raises no difficulties for necessitarianism

Causality, causality, causality: the view of education inputs and outputs from economics

Educators and policy makers are increasingly intent on using scientifically-based evidence when making decisions about education policy. Thus, education research today must necessarily be focused on identifying the causal relationships between education inputs and student outcomes. In this paper we discuss methodologies for estimating the causal effect of resources on education outcomes; we also review what we believe to be the best evidence from economics on a few important inputs: spending, class size, teacher quality, the length of the school year, and technology. We conclude that while the number of papers using credible identification strategies is thin, the body of credible research on causal relationships is growing, and we have started to gather evidence that some school inputs matter while others do not.Education - Economic aspects ; Technology - Economic aspects