Learning Futures with Mixed Sentience

People with disabilities have benefited from the use of assistive technologies that compensate for, or augment functioning.  Socially assistive robots (SAR) both assist with functioning, and engage users socially, often as service, co- robots and companions.  Trends in networked learning communities suggest that membership and rules of exchange will define function, engagement and experiences.  Future communities will likely be characterized by high degrees of interdependence within and varying degrees of openness to outside exchanges.  The ethics of human-robot exchanges within mixed learning communities are undergirded by respect for the interdependence of robots and humans.