Requisite Variety in Ethical Utility Functions for AI Value Alignment
  Being a complex subject of major importance in AI Safety research, value
alignment has been studied from various perspectives in the last years.
However, no final consensus on the design of ethical utility functions
facilitating AI value alignment has been achieved yet. Given the urgency to
identify systematic solutions, we postulate that it might be useful to start
with the simple fact that for the utility function of an AI not to violate
human ethical intuitions, it trivially has to be a model of these intuitions
and reflect their variety $ - $ whereby the most accurate models pertaining to
human entities being biological organisms equipped with a brain constructing
concepts like moral judgements, are scientific models. Thus, in order to better
assess the variety of human morality, we perform a transdisciplinary analysis
applying a security mindset to the issue and summarizing variety-relevant
background knowledge from neuroscience and psychology. We complement this
information by linking it to augmented utilitarianism as a suitable ethical
framework. Based on that, we propose first practical guidelines for the design
of approximate ethical goal functions that might better capture the variety of
human moral judgements. Finally, we conclude and address future possible
challenges.
