Abstract/Summary

In this paper, I outline and investigate the notion of computational beliefs: beliefs formed on the basis of a deliverance from a machine learning algorithm. Given the increased usage of such algorithms through smart devices, such beliefs are becoming increasingly common in everyday life. First, I argue that such beliefs can be successful (i.e. justified and true) by outlining particular examples that possess epistemic properties taken to be indicative of successful beliefs (i.e. being a reason for action, being reliable, being safe, and being sensitive). I then outline how computational beliefs are best understood as a form of what Sosa (2006) describes as instrumental beliefs. As such, it may be thought that computational beliefs hold little epistemological interest insofar as they are reducible to more basic epistemic processes that are already the focus of epistemological attention. However, in the final section, I argue that computational beliefs hold epistemological importance insofar as they have specific epistemically normative repercussions i.e. they give rise to epistemic responsibility gaps.