•  1298
    Fundamental to Computer Science is the distinction between abstractions and implementations. When that distinction is applied to various philosophical questions it yields the following conclusions. • EMERGENCE. It isn’t as mysterious as it’s made out to be; the possibility of strong emergence is not a threat to science. • INTERACTIONS BETWEEN HIGHER-LEVEL ENTITIES. Physical interaction among higher-level entities is illusory. Abstract interactions are the source of emergence, new domains of kn…Read more
  •  764
    What Makes Complex Systems Complex?
    Journal on Policy and Complex Systems 4 (2): 77-113. 2018.
    This paper explores some of the factors that make complex systems complex. We first examine the history of complex systems. It was Aristotle’s insight that how elements are joined together helps determine the properties of the resulting whole. We find (a) that scientific reductionism does not provide a sufficient explanation; (b) that to understand complex systems, one must identify and trace energy flows; and (c) that disproportionate causality, including global tipping points, are all around u…Read more
  •  707
    Meaning, autonomy, symbolic causality, and free will
    Review of General Psychology 22 (1): 85-94. 2018.
    As physical entities that translate symbols into physical actions, computers offer insights into the nature of meaning and agency. • Physical symbol systems, generically known as agents, link abstractions to material actions. The meaning of a symbol is defined as the physical actions an agent takes when the symbol is encountered. • An agent has autonomy when it has the power to select actions based on internal decision processes. Autonomy offers a partial escape from constraints imposed by direc…Read more
  •  599
    Modern computing is generally taken to consist primarily of symbol manipulation. But symbols are abstract, and computers are physical. How can a physical device manipulate abstract symbols? Neither Church nor Turing considered this question. My answer is that the bit, as a hardware-implemented abstract data type, serves as a bridge between materiality and abstraction. Computing also relies on three other primitive—but more straightforward—abstractions: Sequentiality, State, and Transition. These…Read more
  •  306
    I discuss two categories of causal relationships: primitive causal interactions of the sort characterized by Phil Dowe and the more general manipulable causal relationships as defined by James Woodward. All primitive causal interactions are manipulable causal relationships, but there are manipulable causal relationships that are not primitive causal interactions. I’ll call the latter constructed causal relationships, and I’ll argue that constructed causal relationships serve as a foundation for …Read more
  •  228
    The reductionist blind spot
    Complexity 14 (5): 10-22. 2008.
    Can there be higher level laws of nature even though everything is reducible to the fundamental laws of physics? The computer science notion of level of abstraction explains how there can be
  •  38
    How engineering enabled abstraction—in computer science.
  •  25
    Putting complex systems to work
    Complexity 13 (2): 30-49. 2007.
  •  4
    A Software-Inspired Constructive View of Nature
    In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence, Springer Verlag. pp. 123-146. 2019.
    In their review article on “Scientific Reduction” Van Riel and Van Gulick The Stanford encyclopedia of philosophy. Stanford University, Stanford, 2016) write,Saying that x reduces to y typically implies that x is nothing more thany or nothing over and abovey.The y to which an x reduces consists most often of x’s components. But virtually nothing can be reduced if to be “nothing more than” or “nothing over and above” its components means to have no properties other than those of its components, i…Read more