Christopher Michael Cloos

As autonomous mobile robots (AMRs) begin living in the home, performing service tasks and assisting with daily activities, their actions will have profound ethical implications. Consequently, AMRs need to be outfitted with the ability to act morally with regard to human life and safety. Yet, in the area of robotics where morality is a relevant field of endeavor (i.e. human-robot interaction) the sub-discipline of morality does not exist. In response, the Utilibot project seeks to provide a point of initiation for the implementation of ethics in an AMR. The Utilibot is a decision-theoretic AMR guided by the utilitarian notion of the maximization of human well-being. The core ethical decision-making capacity of the Utilibot consists of two dynamic Bayesian networks that model human and environmental health, a dynamic decision network that accounts for decisions and utilities, and a Markov decision process (MDP) that decomposes the planning problem to solve for the optimal course of action to maximize human safety and well-being.

When is a person justified in believing a proposition? In this paper, I defend a view according to which a person is justified in believing a proposition just in case the person’s evidence sufficiently supports the proposition and the person responsibly acquired and sustained the evidence that supports the proposition. This view overcomes a deficiency in a prominent theory of epistemic justification. As championed by Earl Conee and Richard Feldman, Evidentialism is a theory subject to counterexamples at the hands of cases involving epistemic irresponsibility. I critically discuss such a case as put forward by Jason Baehr. After providing an argument that clarifies why the case is problematic for Evidentialism, I defend my argument from a response by Earl Conee. Then I develop a theory of epistemic justification capable of handling cases involving epistemic irresponsibility, and I defend this theory from evidentialist objections