Online research in philosophy

Despite receiving considerable philosophical attention, the concept of autonomy remains contested. In this paper, we diagnose one source of the continuing problem—an excessive emphasis on reflective self-appraisal in the dominant procedural models of autonomy—and suggest a solution. We argue that minimalist conceptions of rational self-appraisal are subject to fatal counterexamples. Yet, attempts to provide a more robust account of rational self-appraisal are too demanding to capture our intuitions about who counts as an autonomous agent. We argue that no procedure of rational reflection will confer autonomy; rather autonomy is a matter of an agent’s actions flowing from her substantive commitments. Instead of rational self-reflection, autonomous actions are the product of the motive of care, which anchors an agent’s occurent desires to her system of value.

Does category theory provide a foundation for mathematics that is autonomous with respect to the orthodox foundation in a set theory such as ZFC? We distinguish three types of autonomy : logical, conceptual, and justificatory. We argue that, while a strong case can be made for its logical and conceptual autonomy, its justificatory autonomy turns on whether or not mathematical theories can be justified by appeal to mathematical practice. If they can, a category-theoretical approach will be fully autonomous; if not, the most natural route to justificatory autonomy is blocked.

What does it mean to say that the discipline of psychology is autonomous? Jerry Fodor (1998, p. 9) says that ‘a law or theory that figures in bona fide empirical explanations but that is not reducible to a law or theory of physics is ipso facto autonomous’. F-autonomy is irreducibility. The Churchlands mean more than this by autonomy; for them, to regard a discipline as autonomous is to ‘try to conduct the affairs of [that discipline] independently of the affairs of its immediate neighbours, both upward and downward in level’ (Churchland and Churchland, 1996, p. 220). We take it that this is not just a matter of pragmatic choices about conducting research with limited resources; rather, a discipline is autonomous when it is not governed or constrained by other disciplines. In this sense, C-autonomy is independence. On the face of it, the two doctrines are distinct and C-autonomy entails F- autonomy.

From Hippocrates to paternalism to autonomy : the new hegemony -- From autonomy to consent -- Consent, autonomy, and the law -- Autonomy at the end of life -- Autonomy and pregnancy -- Autonomy and genetic information -- Autonomy and organ transplantation -- Autonomy, consent, and the law.

This paper explores the assumption of autonomy. Several arguments are presented against the assumption of runtime autonomy as a principle of design for artificial intelligence systems. The arguments vary from being theoretical, to practical, and to analytic. The latter parts of the paper focus on one strategy for building non-autonomous systems (the practice view). One critical theme is that intelligence is not located in the system alone, it emerges from a history of interactions among user, builder, and designer over a given set of data as mediated by the system. A second critical theme is that artificially intelligent systems are ongoing projects that must be continuously adapted and revised using joint person-machine efforts.

This book addresses two related topics: self-control and individual autonomy. In approaching these issues, Mele develops a conception of an ideally self-controlled person, and argues that even such a person can fall short of personal autonomy. He then examines what needs to be added to such a person to yield an autonomous agent and develops two overlapping answers: one for compatibilist believers in human autonomy and one for incompatibilists. While remaining neutral between those who hold that autonomy is compatible with determinism and those who deny this, Mele shows that belief that there are autonomous agents is better grounded than belief that there are not.

Although there are many variations on the theme, so much is made of the good of moral autonomy that it is difficult not to suppose that there is everything to be said for being morally autonomous and nothing at all to be said for being morally nonautonomous. However, this view of moral autonomy cannot be made to square with the well-received fact that most people are morally nonautonomous — not, at any rate, unless one is prepared to maintain that most people are irrational in this respect. I am not. Thus, I reject what I take to be the prevailing view of moral autonomy. I argue that it is false that (1) moral autonomy is such that it is rational for every person to prefer being morally autonomous to being morally nonautonomous, but true that (2) moral autonomy is such that if anyone is morally autonomous, then it is rational for him to prefer being morally autonomous to being morally nonautonomous.

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control the conditions of their own existence so as to increase their overall viability. This paper will first give minimal necessary and sufficient conditions for autonomous anticipation, followed by a taxonomy of autonomous anticipation. In more complex systems, there can be semi-autonomous subsystems that can anticipate and adapt on their own. Such subsystems can be integrated into a system’s overall autonomy, typically with greater efficiency due to modularity and specialization of function. However, it is also possible that semi-autonomous subsystems can act against the viability of the overall system, and have their own functions that conflict with overall system functions.

Anticipation allows a system to adapt to conditions that have not yet come to be, either externally to the system or internally. Autonomous systems actively control their own conditions so as to increase their functionality (they self-regulate). Living systems self-regulate in order to increase their own viability. These increasingly stronger conditions, anticipation, autonomy and viability, can give an insight into progressively stronger classes of models of autonomy. I will argue that stronger forms are the relevant ones for Artificial Life. This has consequences for the design of and accurate simulation of living systems. Keywords: autonomy, modelling, function, simulation, anticipation, emergence DUBOIS’ CONJECTURE Autonomy basically means self-regulation. Self-regulation implies internal control of system states to achieve greater functionality, either internally or interactively with the environment. Functionality, as a teleological notion, implies that the system must be directed by likely future states; that is, it must anticipate and (possibly) adapt to likely future states. Functionality does not require autonomy (assuming functional goals are externally set), but merely that current states of the system can select suitable future states on the basis of suitable input. In this..

Abstract Many anticipatory systems cannot in themselves act meaningfully or represent intentionally. This stems largely from the derivative nature of their functionality. All current artificial control systems, and many living systems such as organs and cellular parts of organisms derive any intentionality they might have from their designers or possessors. Derivative functionality requires reference to some external autonomously functional system, and derivative intentionality similarly requires reference to an external autonomous intentional system. The importance of autonomy can be summed up in the following slogan: No meaning without intention; no intention without function; no function without autonomy. This paper develops the role of autonomy to show how learning new tasks is facilitated by autonomy, and further by representational capacities that are functional for autonomy.