Many of our decisions pertain to causal systems. Nevertheless, only recently has it been claimed that people use causal models when making judgments, decisions and predictions, and that causal Bayes nets allow us to formally describe these inferences. Experimental research has been limited to simple, artificial problems, which are unrepresentative of the complex dynamic systems we successfully deal with in everyday life. For instance, in social interactions, we can explain the actions of other's on the fly and we can generalize (...) from limited observations to predict future actions and their consequences. Our main argument is that none of these inferences (i.e., induction, generalization, explanation, and prediction) can be achieved without causal reasoning. As a case in point we use the popular television series desperate housewives and show how causal Bayes nets are able to explain the inferences made in social contexts. Crucially, causal Bayes nets also allow us to understand why we can infer so much from so little when making sense of a protagonist's behavior. (shrink)

The nature of linguistic understanding is a much-debated topic. Among the issues that have been discussed, two questions have recently received a lot of attention: (Q1) ‘Are states of understanding direct (i.e. represent solely what is said) or indirect (i.e. represent what is said as being said/asserted)?’ and (Q2) ‘What kind of mental attitude is linguistic understanding (e.g. knowledge, belief, seeming)?’ This paper argues that, contrary to what is commonly assumed, there is no straightforward answer to either of these questions. (...) This is because linguistic understanding cannot be identified with a single mental attitude towards a particular representation. Instead, we should characterize states of linguistic understanding as involving complex representational structures generated by a dual-stream process. The first stream operates on direct representations of what is said, while the second operates on representations of what is said as being said/asserted by a given source. Both these streams feed a situation model, i.e. a complex representation of a state of affairs described by a given piece of discourse. (shrink)