# Grounds for trust: Essential Epistemic Opacity and Computational Reliabilism

## TL;DR

This paper argues that computer simulation results can be trusted when they are reliable, emphasizing the importance of computational reliabilism and analyzing sources like verification, validation, and expert knowledge.

## Contribution

It develops the concept of computational reliabilism, connecting epistemic trust in simulations to their reliability and exploring key sources for establishing this reliability.

## Key findings

- Simulation reliability is crucial for trusting results.
- Verification, validation, and robustness analysis support reliability.
- Expert knowledge plays a significant role in trustworthy simulations.

## Abstract

Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations \cite{Parker2009, Morrison2009}, the nature of computer data \cite{Barberousse2013, Humphreys2013}, and the explanatory power of computer simulations \cite{Krohs2008, Duran2017}. The aim of this article is to show that these authors are right in assuming that the results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of \textit{epistemic opacity}, the article elaborates extensively on \textit{computational reliabilism}, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of (un)successful implementations, and the role of expert knowledge in simulations.