Online research in philosophy

Abstract An examination of John Pollock's theory of artificial intelligence and philosophy of mind raises difficulties for his mechanist concept of person. Token physicalism, agent materialism, and strong artificial intelligence are so related that if the first two propositions are not well?established, then there is no justification for believing that an artificial consciousness can be designed and built. Pollock's arguments are shown to be inconclusive in upholding a functionalist theory of persons as supervenient but purely physical entities. In part this is the result of Pollock's thin definition of the concept of supervenience, according to which any complex supervenes on its proper parts. The limitations of this account are apparent when contrasted with richer conceptions of supervenience, such as Joseph Margolis?. But on Margolis? theory, the mind and its expressions supervene on or rise above their material embodiments in the sense that they cannot be fully explained in physical terms, which contradicts Pollock's token physicalism and agent materialism. The consequence for Pollock's project to explain the mind as mechanical, and to manufacture artificial persons, is that these systems can at best aspire to impressive innovations in weak artificial intelligence, but realistically cannot aspire to strong or mentalistic artificial intelligence.

Overview. Consciousness is often considered to have a "hard" part and a not-so-hard part. With the help of work in artificial intelligence and more recently in embodied robotics, there is hope that we shall be able solve the not-so-hard part and make artificial agents that understand their environment, communicate with their friends, and most importantly, have a notion of "self" and "others". But will such agents feel anything? Building the feel into the agent will be the "hard" part.

The ultimate goal of research into computational intelligence is the construction of a fully embodied and fully autonomous artificial agent. This ultimate artificial agent must not only be able to act, but it must be able to act morally. In order to realize this goal, a number of challenges must be met, and a number of questions must be answered, the upshot being that, in doing so, the form of agency to which we must aim in developing artificial agents comes into focus. This chapter explores these issues, and from its results details a novel approach to meeting the given conditions in a simple architecture of information processing.

1. WHAT IS ARTIFICIAL INTELLIGENCE? One of the fascinating aspects of the field of artificial intelligence (AI) is that the precise nature of its subject ..

This paper provides a new analysis of e - trust , trust occurring in digital contexts, among the artificial agents of a distributed artificial system. The analysis endorses a non-psychological approach and rests on a Kantian regulative ideal of a rational agent, able to choose the best option for itself, given a specific scenario and a goal to achieve. The paper first introduces e-trust describing its relevance for the contemporary society and then presents a new theoretical analysis of this phenomenon. The analysis first focuses on an agent’s trustworthiness , this one is presented as the necessary requirement for e-trust to occur. Then, a new definition of e-trust as a second-order-property of first-order relations is presented. It is shown that the second-order-property of e-trust has the effect of minimising an agent’s effort and commitment in the achievement of a given goal. On this basis, a method is provided for the objective assessment of the levels of e-trust occurring among the artificial agents of a distributed artificial system.

Currently, electronic agents are being designed and implemented that, unprecedentedly, will be capable of performing legally binding actions. These advances necessitate a thorough treatment of their legal consequences. In our paper, we first demonstrate that electronic agents behave structurally similar to human agents. Then we study how declarations of intention stated by an electronic agent are related to ordinary declarations of intention given by natural persons or legal entities, and also how the actions of electronic agents in this respect have to be classified under German law. We discuss four different approaches of classifying agent declarations. As one of these, we propose the concept of an electronic person (i.e., agents with limited liability), enrolment of agents into an agent register, and agent liability funds as means to serve the needs of all contracting parties.

A method for forcing norms onto individual agents in a multi-agent system is presented. The agents under study are supersoft agents: autonomous artificial agents programmed to represent and evaluate vague and imprecise information. Agents are further assumed to act in accordance with advice obtained from a normative decision module, with which they can communicate. Norms act as global constraints on the evaluations performed in the decision module and hence no action that violates a norm will be suggested to any agent. Further constraints on action may then be added locally. The method strives to characterise real-time decision making in agents, in the presence of risk and uncertainty.

In their important paper “Autonomous Agents”, Floridi and Sanders use “levels of abstraction” to argue that computers are or may soon be moral agents. In this paper we use the same levels of abstraction to illuminate differences between human moral agents and computers. In their paper, Floridi and Sanders contributed definitions of autonomy, moral accountability and responsibility, but they have not explored deeply some essential questions that need to be answered by computer scientists who design artificial agents. One such question is, “Can an artificial agent that changes its own programming become so autonomous that the original designer is no longer responsible for the behavior of the artificial agent?” To explore this question, we distinguish between LoA1 (the user view) and LoA2 (the designer view) by exploring the concepts of unmodifiable, modifiable and fully modifiable tables that control artificial agents. We demonstrate that an agent with an unmodifiable table, when viewed at LoA2, distinguishes an artificial agent from a human one. This distinction supports our first counter-claim to Floridi and Sanders, namely, that such an agent is not a moral agent, and the designer bears full responsibility for its behavior. We also demonstrate that even if there is an artificial agent with a fully modifiable table capable of learning* and intentionality* that meets the conditions set by Floridi and Sanders for ascribing moral agency to an artificial agent, the designer retains strong moral responsibility.

In their important paper “Autonomous Agents”, Floridi and Sanders use “levels of abstraction” to argue that computers are or may soon be moral agents. In this paper we use the same levels of abstraction to illuminate differences between human moral agents and computers. In their paper, Floridi and Sanders contributed definitions of autonomy, moral accountability and responsibility, but they have not explored deeply some essential questions that need to be answered by computer scientists who design artificial agents. One such question is, “Can an artificial agent that changes its own programming become so autonomous that the original designer is no longer responsible for the behavior of the artificial agent?” To explore this question, we distinguish between LoA1 (the user view) and LoA2 (the designer view) by exploring the concepts of unmodifiable, modifiable and fully modifiable tables that control artificial agents. We demonstrate that an agent with an unmodifiable table, when viewed at LoA2, distinguishes an artificial agent from a human one. This distinction supports our first counter-claim to Floridi and Sanders, namely, that such an agent is not a moral agent, and the designer bears full responsibility for its behavior. We also demonstrate that even if there is an artificial agent with a fully modifiable table capable of learning* and intentionality* that meets the conditions set by Floridi and Sanders for ascribing moral agency to an artificial agent, the designer retains strong moral responsibility.

Unlike natural agents, artificial agents are, to varying extent, designed according to sets of principles or assumptions. We argue that the designers philosophical position on truth, belief and knowledge has far reaching implications for the design and performance of the resulting agents. Of the many sources of design information and background we believe philosophical theories are under-rated as valuable influences on the design process. To explore this idea we have implemented some computer-based agents with their control algorithms inspired by two strongly contrasting philosophical positions. A series of experiments on these agents shows that, despite having common tasks and goals, the behaviour of the agents is markedly different and this can be attributed to their individual approaches to belief and knowledge. We discuss these findings and their support for the view that epistemological theories have a particular relevance for artificial agent design.