  An important step in the development of value alignment (VA) systems in AI is
understanding how values can interrelate with facts. Designers of future VA
systems will need to utilize a hybrid approach in which ethical reasoning and
empirical observation interrelate successfully in machine behavior. In this
article we identify two problems about this interrelation that have been
overlooked by AI discussants and designers. The first problem is that many AI
designers commit inadvertently a version of what has been called by moral
philosophers the "naturalistic fallacy," that is, they attempt to derive an
"ought" from an "is." We illustrate when and why this occurs. The second
problem is that AI designers adopt training routines that fail fully to
simulate human ethical reasoning in the integration of ethical principles and
facts. Using concepts of quantified modal logic, we proceed to offer an
approach that promises to simulate ethical reasoning in humans by connecting
ethical principles on the one hand and propositions about states of affairs on
the other.
