The paper provides a selective analysis of the main theories of trust and e-trust (that is, trust in digital environments) provided in the last twenty years, with the goal of preparing the ground for a new philosophical approach to solve the problems facing them. It is divided into two parts. The first part is functional toward the analysis of e-trust: it focuses on trust and its definition and foundation and describes the general background on which the analysis of e-trust rests. (...) The second part focuses on e-trust, its foundation and ethical implications. The paper ends by synthesising the analysis of the two parts. (shrink)

A program for the simulation of rational social normative trust, predictive `trust,' and predictive reliance between agents will be introduced. It offers a tool for social scientists or a trust component for multi-agent simulations/multi-agent systems, which need to include trust between agents to guide the decisions about the course of action. It is based on an analysis of rational social normative trust (RSNTR) (revised version of M. Tuomela 2002), which is presented and briefly argued. For collective agents, belief conditions for (...) collective agency should be added. For the various forms of trust agents must have (at least) subjectively rational reasons to believe that the conditions of the trust account are fulfilled. A list of such reasons (of varied weights), e.g., given by empirical research, can manually be built into a parameter file or be generated by a calling program in a fixed format. From this list of reasons the program randomly generates a belief base for the agents of the artificial society. Reasons can be chained together so that one set of reasons satisfies several belief conditions. The program checks if the conditions are fulfilled for the artificial agents' social normative trust/predictive `trust'/`predictive reliance' in another agent that he will perform an action X. Each outcome is logged to a result file. In conclusion we discuss various aspects of the application of a trust component of the suggested kind in empirical research, social simulation, and multi-agent systems. (shrink)

Ethics is ordinarily understood as being concerned with questions of responsibility for and in the face of an other. This other is more often than not conceived of as another human being and, as such, necessarily excludes others – most notably animals and machines. This essay examines the ethics of such exclusivity. It is divided into three parts. The first part investigates the exclusive anthropocentrism of traditional forms of moral␣thinking and, following the example of recent innovations in animal rights philosophy, (...) questions the mechanisms of such exclusion. Although recent work in animal- and bio-ethics has successfully implemented strategies for the inclusion of the animal as a legitimate subject of moral consideration, its other, the machine, has remained conspicuously excluded. The second part looks at recent attempts to include these machinic others in moral thinking and critiques the assumptions, values, and strategies that have been employed by these various innovations. And the third part proposes a means for thinking otherwise. That is, it introduces an alternative way to consider these other forms of otherness that is not simply reducible to the conceptual order that has structured and limited moral philosophy’s own concern with and for others. (shrink)

Artificial agents (AAs), particularly but not only those in Cyberspace, extend the class of entities that can be involved in moral situations. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil). In this paper, we clarify the concept of agent and go on to separate the concerns of morality and responsibility of agents (most (...) interestingly for us, of AAs). We conclude that there is substantial and important scope, particularly in Computer Ethics, for the concept of moral agent not necessarily exhibiting free will, mental states or responsibility. This complements the more traditional approach, common at least since Montaigne and Descartes, which considers whether or not (artificial) agents have mental states, feelings, emotions and so on. By focussing directly on mind-less morality we are able to avoid that question and also many of the concerns of Artificial Intelligence. A vital component in our approach is the Method of Abstraction for analysing the level of abstraction (LoA) at which an agent is considered to act. The LoA is determined by the way in which one chooses to describe, analyse and discuss a system and its context. The Method of Abstraction is explained in terms of an interface or set of features or observables at a given LoA. Agenthood, and in particular moral agenthood, depends on a LoA. Our guidelines for agenthood are: interactivity (response to stimulus by change of state), autonomy (ability to change state without stimulus) and adaptability (ability to change the transition rules by which state is changed) at a given LoA. Morality may be thought of as a threshold defined on the observables in the interface determining the LoA under consideration. An agent is morally good if its actions all respect that threshold; and it is morally evil if some action violates it. That view is particularly informative when the agent constitutes a software or digital system, and the observables are numerical. Finally we review the consequences for Computer Ethics of our approach. In conclusion, this approach facilitates the discussion of the morality of agents not only in Cyberspace but also in the biosphere, where animals can be considered moral agents without their having to display free will, emotions or mental states, and in social contexts, where systems like organizations can play the role of moral agents. The primary cost of this facility is the extension of the class of agents and moral agents to embrace AAs. (shrink)

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. (shrink)

There is a growing literature on the concept of e-trust and on the feasibility and advisability of “trusting” artificial agents. In this paper we present an object-oriented model for thinking about trust in both face-to-face and digitally mediated environments. We review important recent contributions to this literature regarding e-trust in conjunction with presenting our model. We identify three important types of trust interactions and examine trust from the perspective of a software developer. Too often, the primary focus of research in (...) this area has been on the artificial agents and the humans they may encounter after they are deployed. We contend that the humans who design, implement, and deploy the artificial agents are crucial to any discussion of e-trust and to understanding the distinctions among the concepts of trust, e-trust and face-to-face trust. (shrink)