STORRS, Connecticut--The prospect of artificial intelligence (AI) has long been a source of knotty ethical questions. But the focus has often been on how we, the creators, can and should use advanced robots. What is missing from the discussion is the need to develop a set of ethics for the machines themselves, together with a means for machines to resolve ethical dilemmas as they arise. Only then can intelligent machines function autonomously, making ethical choices as they fulfill their tasks, without human intervention. There are many activities that we would like to be able to turn over entirely to autonomously functioning machines.

But the focus has often been on how we, the creators, can and should use advanced robots. What is missing from the discussion is the need to develop a set of ethics for the machines themselves, together with a means for machines to resolve ethical dilemmas as they arise. Only then can intelligent machines function autonomously, making ethical choices as they fulfill their tasks, without human intervention. There are many activities that we would like to be able to turn over entirely to autonomously functioning machines. Robots can do jobs that are highly dangerous or exceedingly unpleasant.

We advocate a case-supported principle-based behavior paradigm coupled with the Fractal robot architecture as a means to control an eldercare robot. The most ethically preferable action at any given moment is determined using a principle, abstracted from cases where a consensus of ethicists exists.

A paradigm of case-supported principle-based behavior (CPB) is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake, as we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles needed for ethical guidance of the behavior of autonomous systems. Such principles help ensure the ethical behavior of complex and dynamic systems and further serve as a basis for justification of their actions as well as a control abstraction for managing unanticipated behavior. The requirements, methods, implementation, and evaluation components of the CPB paradigm are detailed.

A paradigm of case-supported principle-based behavior (CPB) is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake, as we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles needed for ethical guidance of the behavior of autonomous systems. Such principles help ensure the ethical behavior of complex and dynamic systems and further serve as a basis for justification of their actions as well as a control abstraction for managing unanticipated behavior. The requirements, methods, implementation, and evaluation components of the CPB paradigm are detailed.

We contend that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. To provide assistance in developing these ethical principles, we have developed GenEth, a general ethical dilemma analyzer that, through a dialog with ethicists, codifies ethical principles in any given domain. GenEth has been used to codify principles in a number of domains pertinent to the behavior of autonomous systems and these principles have been verified using an Ethical Turing Test.

Having discovered a decision principle for a well-known prima facie duty theory in biomedical ethics to resolve particular cases of a common type of ethical dilemma, we developed three applications: a medical ethics advisor system, a medication reminder system and an instantiation of this system in a Nao robot. We are now developing a general, automated method for generating from scratch the ethics needed for a machine to function in a particular domain, without making the assumptions used in our prototype systems.