Machine wanting.

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2013-12

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Abstract

Wants, preferences, and cares are physical things or events, not ideas or propositions, and therefore no chain of pure logic can conclude with a want, preference, or care. It follows that no pure-logic machine will ever want, prefer, or care. And its behavior will never be driven in the way that deliberate human behavior is driven, in other words, it will not be motivated or goal directed. Therefore, if we want to simulate human-style interactions with the world, we will need to first understand the physical structure of goal-directed systems. I argue that all such systems share a common nested structure, consisting of a smaller entity that moves within and is driven by a larger field that contains it. In such systems, the smaller contained entity is directed by the field, but also moves to some degree independently of it, allowing the entity to deviate and return, to show the plasticity and persistence that is characteristic of goal direction. If all this is right, then human want-driven behavior probably involves a behavior-generating mechanism that is contained within a neural field of some kind. In principle, for goal directedness generally, the containment can be virtual, raising the possibility that want-driven behavior could be simulated in standard computational systems. But there are also reasons to believe that goal-direction works better when containment is also physical, suggesting that a new kind of hardware may be necessary.

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10.1016/j.shpsc.2013.05.015

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McShea, Daniel W (2013). Machine wanting. Studies in history and philosophy of biological and biomedical sciences, 44(4 Pt B). pp. 679–687. 10.1016/j.shpsc.2013.05.015 Retrieved from https://hdl.handle.net/10161/29573.

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Scholars@Duke

McShea

Daniel W. McShea

Professor of Biology

My main research interest is hierarchy theory, especially the causal relationship between higher-level wholes and their components (Spencer, Simon, Campbell, Salthe, Wimsatt). In biology, for example, we might want to know how large-scale processes within a multicellular organism act to control the smaller-scale processes within its component cells. Or, in the area of my current research, how do the emotions in mammals (and perhaps other animals) act to initiate and control conscious thought and behavior? It seems clear from the philosophical work of Hume (A Treatise of Human Nature) that the preferencing or valuing that motivates or drives conscious thought and behavior, and in particular conscious decision-making, must arise from the emotions. This is true because the only alternative, reason (in the sense of pure rationality), is value-neutral, and utterly incapable of motivating anything. As Hume put it, "Reason is and ought to be the slave of the passions and can never pretend to any other office than to serve and obey them."

But what is the nature of the causal process by which emotion drives thought and behavior? I argue that it is a form of downward causation, of a sort that occurs in many hierarchical systems. Consider a neutrally buoyant balloon filled with gas and hanging in a room. If the balloon as a whole is moved -- say 2 inches to the left -- this large-scale movement causes all of the gas molecules within it (as well as the molecules in the plastic skin of the balloon) to move, on average, 2 inches to the left. A similar sort of top-down causation occurs, it seems, in the emotion-behavior and emotion-thought relationship. The evidence is that these relationships seem to follow certain key principles of hierarchy theory. 1. Rates. Lower levels move quickly relative to the higher level. The gas molecules in a balloon typically move quickly relative to the balloon as a whole. Likewise, thought and behavior are fast relative to change in emotional state. 2. Causal asymmetry. Lower-level units cannot, as individuals, much affect the higher level. A single gas molecule cannot much affect a whole balloon. Likewise, individual thoughts and behaviors ordinarily do not much affect an emotion. Rather, an emotion hovers more or less unchanging, in the background, while thoughts and behaviors aimed at satisfying that emotion play out. 3. Vagueness. Lower-level units do not directly interact with higher levels and therefore "perceive" them only "vaguely." Thus, thoughts and behaviors are clear and distinct, but we perceive our emotions only vaguely. 4. Downward causation. Higher levels exert their causal influence on lower-level units via boundary conditions, and therefore higher-level control is not precise, with the result that lower-level units have considerable freedom. Consistent with this, in two similar higher-level systems, the sequence of behaviors of lower-level units could be very different. The movements of individual gas molecules in two very similar balloons will be very different. Likewise, the same emotion, the same motivation, in two different people is consistent with their thinking and behaving very differently. (Although presumably some very general similarities can be found. To the extent that the two share the same emotion, the goals they are pursuing are similar. Analogously, the movements of the gas molecules in the balloon share a general similarity, in that they all move two inches to the left on average.)

My past work has been mainly on large-scale evolutionary trends, that is, trends that include a number of higher taxa and that span a large portion of the history of life. Features that have been said to show such trends include complexity, size, fitness, and others. In my research, I worked mainly on developing operational measures of these features, devising methods for testing empirically whether trends have occurred, and studying the causes and correlates of trends. Most of this work so far has been on trends in complexity. In a recent book (Biology’s First Law 2010) with the philosopher Robert Brandon, we argue that complexity change in evolution is partly governed by what we call the Zero-Force Evolutionary Law (ZFEL). The law says that in the absence of selection and constraint, complexity – in the sense of differentiation among parts – will tend to increase. Further, we argue, even when forces and constraints are present, a tendency for complexity to increase is always present. The rationale is simply that in the absence of selection or constraint, the parts of an organism will tend spontaneously to accumulate variation, and therefore to become more different from each other. Thus, for example, in a multicellular organism, in the absence of selection and constraint, the degree of differentiation among cells should increase, leading eventually to an increase in the number of cell types. As we argue in the book, the law applies at all hierarchical levels (molecules, organelles, cells, etc.). It also applies above the level of the organism, to differences among individuals in populations, and to differences among species and among higher taxa. In other words, the ZFEL says that diversity also tends spontaneously to increase. The ZFEL is universal, applying to all evolutionary lineages, at all times, in all places, everywhere life occurs. A consequence is that any complete evolutionary explanation for change in complexity or diversity will necessarily include the ZFEL as one component.

Other interests include the philosophy of biology generally. (See my textbook coauthored with philosopher Alex Rosenberg, Philosophy Of Biology: A Contemporary Introduction 2009.) More specifically: 1. The connections among the various evolutionary forces acting on animal form -- functional, formal, and phylogenetic. 2. Animal psychology generally. 3. The relationship between morality and human nature.


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