Litcius/Paper detail

On the Opacity of Deep Neural Networks

Anders Søgaard

2023Canadian Journal of Philosophy22 citationsDOIOpen Access PDF

Abstract

Abstract Deep neural networks are said to be opaque, impeding the development of safe and trustworthy artificial intelligence, but where this opacity stems from is less clear. What are the sufficient properties for neural network opacity? Here, I discuss five common properties of deep neural networks and two different kinds of opacity. Which of these properties are sufficient for what type of opacity? I show how each kind of opacity stems from only one of these five properties, and then discuss to what extent the two kinds of opacity can be mitigated by explainability methods.

Topics & Concepts

OpacityArtificial intelligenceComputer sciencePhysicsOpticsExplainable Artificial Intelligence (XAI)Adversarial Robustness in Machine LearningNeural Networks and Applications