George Kampis

In contemporary literature, the fact that there is negative causation is the primary motivation for rejecting the physical connection view, and arguing for alternative accounts of causation. In this paper we insist that such a conclusion is too fast. We present two frameworks, which help the proponent of the physical connection view to resist the anti-connectionist conclusion. According to the first framework, there are positive causal claims, which co-refer with at least some negative causal claims. According to the second framework, negative causal claims are generated from mapping and comparing different scenarios, which can fully be accounted for in purely positive terms. Since the positive causal claims evoked by both frameworks pose no obvious difficulties for the physical connection view, these frameworks make it possible for the connectionists to accommodate negative causal claims into their theory. Once these strategies are available, the connectionists become able to render all the arguments starting from the observation that there are negative causal claims in our causal discourse inconclusive with regard to the viability of the physical connection view.

Semantic systems are sytems with an inherent semantics. An example would be systems showing intrinsic intentionality: if a system is genuinely intentional, it must be able to define its own meanings. Searle was a forerunner of the modern idea of semantic systems in his oft-cited “Chinese Room” paper in 1980. The current author has approached the problem from a different angle 30 years ago in his book Self-Modifying Systems, claiming that minds can define their own meanings by virtue of being “material”, in the sense of freely generating new properties on the fly, as do material objects. In the course of the process, meaning should arise because syntax does not fully describe the rich functioning of such systems, so goes the argument. While still attractive, the author has in the meantime abandoned the idea, for at least two reasons. One, fundamentals-seeking has itself been largely abandoned, because the study of questions like “is the mind computational”? has turned out to be non-productive. Two, brute force approaches such as ANN-based deep learning have been “unreasonably” successful, and this fact puts aside arguments about the limits of computational systems. The paper provides an overview of these developments.