  As AI technologies increase in capability and ubiquity, AI accidents are
becoming more common. Based on normal accident theory, high reliability theory,
and open systems theory, we create a framework for understanding the risks
associated with AI applications. In addition, we also use AI safety principles
to quantify the unique risks of increased intelligence and human-like qualities
in AI. Together, these two fields give a more complete picture of the risks of
contemporary AI. By focusing on system properties near accidents instead of
seeking a root cause of accidents, we identify where attention should be paid
to safety for current generation AI systems.
