Modeling Responsibility Attribution in a Group

2019-08-08T18:30:12Z (GMT) by Yishan Zhou
Attributing responsibilities to a group of agents who contribute to a collective cause
is common in our daily life. While we as humans could relatively efficiently assign
responsibility to others using our intuition, the wide range of possible scenarios and
complexity of our cognitive mechanisms should not be overlooked. Understanding
of how rational responsibility judgments are made could expand our knowledge
about human causal and moral reasoning. Over recent years, a few theories have
been developed to account for responsibility attribution, but they have various theoretical
and empirical limitations. In this thesis, an extended computational model
is proposed in an effort to expand the explanatory power of previous models. We
devised two sets of experiments to test the performance of this newmodel, especially
with regards to aspects including (1) epistemic state of rater, (2) perceived autonomy
of agents, and (3) value range of contributions. Our results suggest that the new
model demonstrated reasonable power in predicting responsibility attribution, albeit
with several unexpected inaccuracies. The close relationship among responsibility,
criticality, and pivotality is nonetheless supported.