A little over thirty years ago, when he was in his mid-forties, my friend David Howorth lost all hearing in his left ear, a calamity known as single-sided deafness. "It happened literally overnight," he said. "My doctor told me, 'We really don't understand why.' " At the time, he was working as a litigator in the Portland, Oregon, office of a large law firm. His hearing loss had no impact on his job--"In a courtroom, you can get along fine with one ear"--but other parts of his life were upended. The brain pinpoints sound sources in part by analyzing minute differences between left-ear and right-ear arrival times, the same process that helps bats and owls find prey they can't see.

Denise Garcia knows that her students sometimes cheat, but the situation she unearthed in February seemed different. A math teacher in West Hartford, Connecticut, Garcia had accidentally included an advanced equation in a problem set for her AP Calculus class. Yet somehow a handful of students in the 15-person class solved it correctly. Those students had also shown their work, defeating the traditional litmus test for sussing out cheating in STEM classrooms. Garcia was perplexed, until she remembered a conversation from a few years earlier.

Denise Garcia knows that her students sometimes cheat, but the situation she unearthed in February seemed different. A math teacher in West Hartford, Connecticut, Garcia had accidentally included an advanced equation in a problem set for her AP Calculus class. Yet somehow a handful of students in the 15-person class solved it correctly. Those students had also shown their work, defeating the traditional litmus test for sussing out cheating in STEM classrooms. Garcia was perplexed, until she remembered a conversation from a few years earlier.

We have implemented a simulation of a robot functioning in the domain of eldercare whose behavior is completely determined by an ethical principle. Using a subset of the perceptions and duties that will be required of such a robot, this simulation demonstrates selection of ethically preferable actions in real time using a case-supported principle-based paradigm. We believe that this work could serve as the basis for ensuring that the behavior of all eldercare robots that are created in the future will be ethically justifiable. Further, we believe that the methods used in this project can be employed in other domains as well, to ensure that the robots that humans interact with in these domains will behave ethically.

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.

In this paper, we examine Robot Defense, a computer game that serves as a pedagogical platform for students to explore methods typically covered in an Introductory Artificial Intelligence course. Robot Defense is the synergistic outcome of two NSF funded Course, Curriculum, and Laboratory Improvement (CCLI) projects and was first presented in (Wallace, Russell and Markov 2008). The primary contribution of this paper is to discuss the implementation of the Robot Defense platform and the outcome of its first use in the classroom.